From 9af285977e0ee25819ddc4d623591ffa76ef2eab Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Tue, 4 Mar 2025 16:13:46 -0800 Subject: [PATCH 001/164] Fix error when there is no session to call _create_model_request() (#5062) * Fix error when there is no session to call _create_model_request() * Fix codestyle --------- Co-authored-by: pintaoz --- src/sagemaker/pipeline.py | 15 +++++++++++++++ src/sagemaker/workflow/steps.py | 2 ++ 2 files changed, 17 insertions(+) diff --git a/src/sagemaker/pipeline.py b/src/sagemaker/pipeline.py index 1d1ece5965..b36cd4e917 100644 --- a/src/sagemaker/pipeline.py +++ b/src/sagemaker/pipeline.py @@ -17,6 +17,8 @@ import sagemaker from sagemaker import ModelMetrics, Model +from sagemaker import local +from sagemaker import session from sagemaker.config import ( ENDPOINT_CONFIG_KMS_KEY_ID_PATH, MODEL_VPC_CONFIG_PATH, @@ -560,3 +562,16 @@ def delete_model(self): raise ValueError("The SageMaker model must be created before attempting to delete.") self.sagemaker_session.delete_model(self.name) + + def _init_sagemaker_session_if_does_not_exist(self, instance_type=None): + """Set ``self.sagemaker_session`` to ``LocalSession`` or ``Session`` if it's not already. + + The type of session object is determined by the instance type. + """ + if self.sagemaker_session: + return + + if instance_type in ("local", "local_gpu"): + self.sagemaker_session = local.LocalSession(sagemaker_config=self._sagemaker_config) + else: + self.sagemaker_session = session.Session(sagemaker_config=self._sagemaker_config) diff --git a/src/sagemaker/workflow/steps.py b/src/sagemaker/workflow/steps.py index a80b5440c7..f49e457bc6 100644 --- a/src/sagemaker/workflow/steps.py +++ b/src/sagemaker/workflow/steps.py @@ -645,6 +645,7 @@ def arguments(self) -> RequestType: request_dict = self.step_args else: if isinstance(self.model, PipelineModel): + self.model._init_sagemaker_session_if_does_not_exist() request_dict = self.model.sagemaker_session._create_model_request( name="", role=self.model.role, @@ -653,6 +654,7 @@ def arguments(self) -> RequestType: enable_network_isolation=self.model.enable_network_isolation, ) else: + self.model._init_sagemaker_session_if_does_not_exist() request_dict = self.model.sagemaker_session._create_model_request( name="", role=self.model.role, From 921493d94b83382a89f5c2640dbc76732ebf15d7 Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Tue, 4 Mar 2025 16:14:16 -0800 Subject: [PATCH 002/164] Ensure Model.is_repack() returns a boolean (#5060) * Ensure Model.is_repack() returns a boolean * update test --------- Co-authored-by: pintaoz --- src/sagemaker/model.py | 4 ++++ tests/unit/sagemaker/model/test_framework_model.py | 14 ++++++++++++++ tests/unit/sagemaker/model/test_model.py | 14 ++++++++++++++ 3 files changed, 32 insertions(+) diff --git a/src/sagemaker/model.py b/src/sagemaker/model.py index 5cc260f3ef..e5ea1ea314 100644 --- a/src/sagemaker/model.py +++ b/src/sagemaker/model.py @@ -745,6 +745,8 @@ def is_repack(self) -> bool: Returns: bool: if the source need to be repacked or not """ + if self.source_dir is None or self.entry_point is None: + return False return self.source_dir and self.entry_point and not self.git_config def _upload_code(self, key_prefix: str, repack: bool = False) -> None: @@ -2143,6 +2145,8 @@ def is_repack(self) -> bool: Returns: bool: if the source need to be repacked or not """ + if self.source_dir is None or self.entry_point is None: + return False return self.source_dir and self.entry_point and not (self.key_prefix or self.git_config) diff --git a/tests/unit/sagemaker/model/test_framework_model.py b/tests/unit/sagemaker/model/test_framework_model.py index d41dd6f821..432d90bd37 100644 --- a/tests/unit/sagemaker/model/test_framework_model.py +++ b/tests/unit/sagemaker/model/test_framework_model.py @@ -511,6 +511,20 @@ def test_is_repack_with_code_location(repack_model, sagemaker_session): assert not model.is_repack() +@patch("sagemaker.utils.repack_model") +def test_is_repack_with_none_type(repack_model, sagemaker_session): + """Test is_repack() returns a boolean value when source_dir and entry_point are None""" + + model = FrameworkModel( + role=ROLE, + sagemaker_session=sagemaker_session, + image_uri=IMAGE_URI, + model_data=MODEL_DATA, + ) + + assert model.is_repack() is False + + @patch("sagemaker.git_utils.git_clone_repo") @patch("sagemaker.model.fw_utils.tar_and_upload_dir") def test_is_repack_with_git_config(tar_and_upload_dir, git_clone_repo, sagemaker_session): diff --git a/tests/unit/sagemaker/model/test_model.py b/tests/unit/sagemaker/model/test_model.py index 9175613662..3d498dfc59 100644 --- a/tests/unit/sagemaker/model/test_model.py +++ b/tests/unit/sagemaker/model/test_model.py @@ -1046,6 +1046,20 @@ def test_is_repack_with_code_location(repack_model, sagemaker_session): assert model.is_repack() +@patch("sagemaker.utils.repack_model") +def test_is_repack_with_none_type(repack_model, sagemaker_session): + """Test is_repack() returns a boolean value when source_dir and entry_point are None""" + + model = Model( + role=ROLE, + sagemaker_session=sagemaker_session, + image_uri=IMAGE_URI, + model_data=MODEL_DATA, + ) + + assert model.is_repack() is False + + @patch("sagemaker.git_utils.git_clone_repo") @patch("sagemaker.model.fw_utils.tar_and_upload_dir") def test_is_repack_with_git_config(tar_and_upload_dir, git_clone_repo, sagemaker_session): From 83ce1a0f8e3da29ef0a6d028cc8e5c1842cf1f56 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Tue, 4 Mar 2025 16:54:41 -0800 Subject: [PATCH 003/164] feat: Allow ModelTrainer to accept hyperparameters file (#5059) * Allow ModelTrainer to accept hyperparameter file and create Hyperparameter class * pylint * Detect hyperparameters from contents rather than file extension * pylint * change: add integs * change: add integs * change: remove custom hyperparameter tooling * Add tests for hp contracts * change: add unit tests and remove unreachable condition * fix integs * doc check fix * fix tests * fix tox.ini * add unit test --- src/sagemaker/modules/train/model_trainer.py | 32 +++++- .../params_script/hyperparameters.json | 15 +++ .../params_script/hyperparameters.yaml | 19 ++++ .../modules/params_script/requirements.txt | 1 + tests/data/modules/params_script/train.py | 97 ++++++++++++++++++- .../modules/train/test_model_trainer.py | 52 +++++++--- .../modules/train/test_model_trainer.py | 93 +++++++++++++++++- 7 files changed, 285 insertions(+), 24 deletions(-) create mode 100644 tests/data/modules/params_script/hyperparameters.json create mode 100644 tests/data/modules/params_script/hyperparameters.yaml create mode 100644 tests/data/modules/params_script/requirements.txt diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index a47d8f91ad..bb7c4168e6 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -18,8 +18,8 @@ import json import shutil from tempfile import TemporaryDirectory - from typing import Optional, List, Union, Dict, Any, ClassVar +import yaml from graphene.utils.str_converters import to_camel_case, to_snake_case @@ -195,8 +195,9 @@ class ModelTrainer(BaseModel): Defaults to "File". environment (Optional[Dict[str, str]]): The environment variables for the training job. - hyperparameters (Optional[Dict[str, Any]]): - The hyperparameters for the training job. + hyperparameters (Optional[Union[Dict[str, Any], str]): + The hyperparameters for the training job. Can be a dictionary of hyperparameters + or a path to hyperparameters json/yaml file. tags (Optional[List[Tag]]): An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. @@ -226,7 +227,7 @@ class ModelTrainer(BaseModel): checkpoint_config: Optional[CheckpointConfig] = None training_input_mode: Optional[str] = "File" environment: Optional[Dict[str, str]] = {} - hyperparameters: Optional[Dict[str, Any]] = {} + hyperparameters: Optional[Union[Dict[str, Any], str]] = {} tags: Optional[List[Tag]] = None local_container_root: Optional[str] = os.getcwd() @@ -470,6 +471,29 @@ def model_post_init(self, __context: Any): f"StoppingCondition not provided. Using default:\n{self.stopping_condition}" ) + if self.hyperparameters and isinstance(self.hyperparameters, str): + if not os.path.exists(self.hyperparameters): + raise ValueError(f"Hyperparameters file not found: {self.hyperparameters}") + logger.info(f"Loading hyperparameters from file: {self.hyperparameters}") + with open(self.hyperparameters, "r") as f: + contents = f.read() + try: + self.hyperparameters = json.loads(contents) + logger.debug("Hyperparameters loaded as JSON") + except json.JSONDecodeError: + try: + logger.info(f"contents: {contents}") + self.hyperparameters = yaml.safe_load(contents) + if not isinstance(self.hyperparameters, dict): + raise ValueError("YAML contents must be a valid mapping") + logger.info(f"hyperparameters: {self.hyperparameters}") + logger.debug("Hyperparameters loaded as YAML") + except (yaml.YAMLError, ValueError): + raise ValueError( + f"Invalid hyperparameters file: {self.hyperparameters}. " + "Must be a valid JSON or YAML file." + ) + if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB and self.output_data_config is None: session = self.sagemaker_session base_job_name = self.base_job_name diff --git a/tests/data/modules/params_script/hyperparameters.json b/tests/data/modules/params_script/hyperparameters.json new file mode 100644 index 0000000000..f637288dbe --- /dev/null +++ b/tests/data/modules/params_script/hyperparameters.json @@ -0,0 +1,15 @@ +{ + "integer": 1, + "boolean": true, + "float": 3.14, + "string": "Hello World", + "list": [1, 2, 3], + "dict": { + "string": "value", + "integer": 3, + "float": 3.14, + "list": [1, 2, 3], + "dict": {"key": "value"}, + "boolean": true + } +} \ No newline at end of file diff --git a/tests/data/modules/params_script/hyperparameters.yaml b/tests/data/modules/params_script/hyperparameters.yaml new file mode 100644 index 0000000000..9e3011daf2 --- /dev/null +++ b/tests/data/modules/params_script/hyperparameters.yaml @@ -0,0 +1,19 @@ +integer: 1 +boolean: true +float: 3.14 +string: "Hello World" +list: + - 1 + - 2 + - 3 +dict: + string: value + integer: 3 + float: 3.14 + list: + - 1 + - 2 + - 3 + dict: + key: value + boolean: true \ No newline at end of file diff --git a/tests/data/modules/params_script/requirements.txt b/tests/data/modules/params_script/requirements.txt new file mode 100644 index 0000000000..3d2e72e354 --- /dev/null +++ b/tests/data/modules/params_script/requirements.txt @@ -0,0 +1 @@ +omegaconf diff --git a/tests/data/modules/params_script/train.py b/tests/data/modules/params_script/train.py index 8d3924a325..9b8cb2c82f 100644 --- a/tests/data/modules/params_script/train.py +++ b/tests/data/modules/params_script/train.py @@ -16,6 +16,9 @@ import argparse import json import os +from typing import List, Dict, Any +from dataclasses import dataclass +from omegaconf import OmegaConf EXPECTED_HYPERPARAMETERS = { "integer": 1, @@ -26,6 +29,7 @@ "dict": { "string": "value", "integer": 3, + "float": 3.14, "list": [1, 2, 3], "dict": {"key": "value"}, "boolean": True, @@ -117,7 +121,7 @@ def main(): assert isinstance(params["dict"], dict) params = json.loads(os.environ["SM_TRAINING_ENV"])["hyperparameters"] - print(params) + print(f"SM_TRAINING_ENV -> hyperparameters: {params}") assert params["string"] == EXPECTED_HYPERPARAMETERS["string"] assert params["integer"] == EXPECTED_HYPERPARAMETERS["integer"] assert params["boolean"] == EXPECTED_HYPERPARAMETERS["boolean"] @@ -132,9 +136,96 @@ def main(): assert isinstance(params["float"], float) assert isinstance(params["list"], list) assert isinstance(params["dict"], dict) - print(f"SM_TRAINING_ENV -> hyperparameters: {params}") - print("Test passed.") + # Local JSON - DictConfig OmegaConf + params = OmegaConf.load("hyperparameters.json") + + print(f"Local hyperparameters.json: {params}") + assert params.string == EXPECTED_HYPERPARAMETERS["string"] + assert params.integer == EXPECTED_HYPERPARAMETERS["integer"] + assert params.boolean == EXPECTED_HYPERPARAMETERS["boolean"] + assert params.float == EXPECTED_HYPERPARAMETERS["float"] + assert params.list == EXPECTED_HYPERPARAMETERS["list"] + assert params.dict == EXPECTED_HYPERPARAMETERS["dict"] + assert params.dict.string == EXPECTED_HYPERPARAMETERS["dict"]["string"] + assert params.dict.integer == EXPECTED_HYPERPARAMETERS["dict"]["integer"] + assert params.dict.boolean == EXPECTED_HYPERPARAMETERS["dict"]["boolean"] + assert params.dict.float == EXPECTED_HYPERPARAMETERS["dict"]["float"] + assert params.dict.list == EXPECTED_HYPERPARAMETERS["dict"]["list"] + assert params.dict.dict == EXPECTED_HYPERPARAMETERS["dict"]["dict"] + + @dataclass + class DictConfig: + string: str + integer: int + boolean: bool + float: float + list: List[int] + dict: Dict[str, Any] + + @dataclass + class HPConfig: + string: str + integer: int + boolean: bool + float: float + list: List[int] + dict: DictConfig + + # Local JSON - Structured OmegaConf + hp_config: HPConfig = OmegaConf.merge( + OmegaConf.structured(HPConfig), OmegaConf.load("hyperparameters.json") + ) + print(f"Local hyperparameters.json - Structured: {hp_config}") + assert hp_config.string == EXPECTED_HYPERPARAMETERS["string"] + assert hp_config.integer == EXPECTED_HYPERPARAMETERS["integer"] + assert hp_config.boolean == EXPECTED_HYPERPARAMETERS["boolean"] + assert hp_config.float == EXPECTED_HYPERPARAMETERS["float"] + assert hp_config.list == EXPECTED_HYPERPARAMETERS["list"] + assert hp_config.dict == EXPECTED_HYPERPARAMETERS["dict"] + assert hp_config.dict.string == EXPECTED_HYPERPARAMETERS["dict"]["string"] + assert hp_config.dict.integer == EXPECTED_HYPERPARAMETERS["dict"]["integer"] + assert hp_config.dict.boolean == EXPECTED_HYPERPARAMETERS["dict"]["boolean"] + assert hp_config.dict.float == EXPECTED_HYPERPARAMETERS["dict"]["float"] + assert hp_config.dict.list == EXPECTED_HYPERPARAMETERS["dict"]["list"] + assert hp_config.dict.dict == EXPECTED_HYPERPARAMETERS["dict"]["dict"] + + # Local YAML - Structured OmegaConf + hp_config: HPConfig = OmegaConf.merge( + OmegaConf.structured(HPConfig), OmegaConf.load("hyperparameters.yaml") + ) + print(f"Local hyperparameters.yaml - Structured: {hp_config}") + assert hp_config.string == EXPECTED_HYPERPARAMETERS["string"] + assert hp_config.integer == EXPECTED_HYPERPARAMETERS["integer"] + assert hp_config.boolean == EXPECTED_HYPERPARAMETERS["boolean"] + assert hp_config.float == EXPECTED_HYPERPARAMETERS["float"] + assert hp_config.list == EXPECTED_HYPERPARAMETERS["list"] + assert hp_config.dict == EXPECTED_HYPERPARAMETERS["dict"] + assert hp_config.dict.string == EXPECTED_HYPERPARAMETERS["dict"]["string"] + assert hp_config.dict.integer == EXPECTED_HYPERPARAMETERS["dict"]["integer"] + assert hp_config.dict.boolean == EXPECTED_HYPERPARAMETERS["dict"]["boolean"] + assert hp_config.dict.float == EXPECTED_HYPERPARAMETERS["dict"]["float"] + assert hp_config.dict.list == EXPECTED_HYPERPARAMETERS["dict"]["list"] + assert hp_config.dict.dict == EXPECTED_HYPERPARAMETERS["dict"]["dict"] + print(f"hyperparameters.yaml -> hyperparameters: {hp_config}") + + # HP Dict - Structured OmegaConf + hp_dict = json.loads(os.environ["SM_HPS"]) + hp_config: HPConfig = OmegaConf.merge(OmegaConf.structured(HPConfig), OmegaConf.create(hp_dict)) + print(f"SM_HPS - Structured: {hp_config}") + assert hp_config.string == EXPECTED_HYPERPARAMETERS["string"] + assert hp_config.integer == EXPECTED_HYPERPARAMETERS["integer"] + assert hp_config.boolean == EXPECTED_HYPERPARAMETERS["boolean"] + assert hp_config.float == EXPECTED_HYPERPARAMETERS["float"] + assert hp_config.list == EXPECTED_HYPERPARAMETERS["list"] + assert hp_config.dict == EXPECTED_HYPERPARAMETERS["dict"] + assert hp_config.dict.string == EXPECTED_HYPERPARAMETERS["dict"]["string"] + assert hp_config.dict.integer == EXPECTED_HYPERPARAMETERS["dict"]["integer"] + assert hp_config.dict.boolean == EXPECTED_HYPERPARAMETERS["dict"]["boolean"] + assert hp_config.dict.float == EXPECTED_HYPERPARAMETERS["dict"]["float"] + assert hp_config.dict.list == EXPECTED_HYPERPARAMETERS["dict"]["list"] + assert hp_config.dict.dict == EXPECTED_HYPERPARAMETERS["dict"]["dict"] + print(f"SM_HPS -> hyperparameters: {hp_config}") if __name__ == "__main__": diff --git a/tests/integ/sagemaker/modules/train/test_model_trainer.py b/tests/integ/sagemaker/modules/train/test_model_trainer.py index cd298402b2..a19f6d0e8b 100644 --- a/tests/integ/sagemaker/modules/train/test_model_trainer.py +++ b/tests/integ/sagemaker/modules/train/test_model_trainer.py @@ -28,26 +28,29 @@ "dict": { "string": "value", "integer": 3, + "float": 3.14, "list": [1, 2, 3], "dict": {"key": "value"}, "boolean": True, }, } +PARAM_SCRIPT_SOURCE_DIR = f"{DATA_DIR}/modules/params_script" +PARAM_SCRIPT_SOURCE_CODE = SourceCode( + source_dir=PARAM_SCRIPT_SOURCE_DIR, + requirements="requirements.txt", + entry_script="train.py", +) + DEFAULT_CPU_IMAGE = "763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:2.0.0-cpu-py310" def test_hp_contract_basic_py_script(modules_sagemaker_session): - source_code = SourceCode( - source_dir=f"{DATA_DIR}/modules/params_script", - entry_script="train.py", - ) - model_trainer = ModelTrainer( sagemaker_session=modules_sagemaker_session, training_image=DEFAULT_CPU_IMAGE, hyperparameters=EXPECTED_HYPERPARAMETERS, - source_code=source_code, + source_code=PARAM_SCRIPT_SOURCE_CODE, base_job_name="hp-contract-basic-py-script", ) @@ -57,6 +60,7 @@ def test_hp_contract_basic_py_script(modules_sagemaker_session): def test_hp_contract_basic_sh_script(modules_sagemaker_session): source_code = SourceCode( source_dir=f"{DATA_DIR}/modules/params_script", + requirements="requirements.txt", entry_script="train.sh", ) model_trainer = ModelTrainer( @@ -71,17 +75,13 @@ def test_hp_contract_basic_sh_script(modules_sagemaker_session): def test_hp_contract_mpi_script(modules_sagemaker_session): - source_code = SourceCode( - source_dir=f"{DATA_DIR}/modules/params_script", - entry_script="train.py", - ) compute = Compute(instance_type="ml.m5.xlarge", instance_count=2) model_trainer = ModelTrainer( sagemaker_session=modules_sagemaker_session, training_image=DEFAULT_CPU_IMAGE, compute=compute, hyperparameters=EXPECTED_HYPERPARAMETERS, - source_code=source_code, + source_code=PARAM_SCRIPT_SOURCE_CODE, distributed=MPI(), base_job_name="hp-contract-mpi-script", ) @@ -90,19 +90,39 @@ def test_hp_contract_mpi_script(modules_sagemaker_session): def test_hp_contract_torchrun_script(modules_sagemaker_session): - source_code = SourceCode( - source_dir=f"{DATA_DIR}/modules/params_script", - entry_script="train.py", - ) compute = Compute(instance_type="ml.m5.xlarge", instance_count=2) model_trainer = ModelTrainer( sagemaker_session=modules_sagemaker_session, training_image=DEFAULT_CPU_IMAGE, compute=compute, hyperparameters=EXPECTED_HYPERPARAMETERS, - source_code=source_code, + source_code=PARAM_SCRIPT_SOURCE_CODE, distributed=Torchrun(), base_job_name="hp-contract-torchrun-script", ) model_trainer.train() + + +def test_hp_contract_hyperparameter_json(modules_sagemaker_session): + model_trainer = ModelTrainer( + sagemaker_session=modules_sagemaker_session, + training_image=DEFAULT_CPU_IMAGE, + hyperparameters=f"{PARAM_SCRIPT_SOURCE_DIR}/hyperparameters.json", + source_code=PARAM_SCRIPT_SOURCE_CODE, + base_job_name="hp-contract-hyperparameter-json", + ) + assert model_trainer.hyperparameters == EXPECTED_HYPERPARAMETERS + model_trainer.train() + + +def test_hp_contract_hyperparameter_yaml(modules_sagemaker_session): + model_trainer = ModelTrainer( + sagemaker_session=modules_sagemaker_session, + training_image=DEFAULT_CPU_IMAGE, + hyperparameters=f"{PARAM_SCRIPT_SOURCE_DIR}/hyperparameters.yaml", + source_code=PARAM_SCRIPT_SOURCE_CODE, + base_job_name="hp-contract-hyperparameter-yaml", + ) + assert model_trainer.hyperparameters == EXPECTED_HYPERPARAMETERS + model_trainer.train() diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 29da03bcd9..194bb44988 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -17,9 +17,10 @@ import tempfile import json import os +import yaml import pytest from pydantic import ValidationError -from unittest.mock import patch, MagicMock, ANY +from unittest.mock import patch, MagicMock, ANY, mock_open from sagemaker import image_uris from sagemaker_core.main.resources import TrainingJob @@ -1093,3 +1094,93 @@ def test_destructor_cleanup(mock_tmp_dir, modules_session): mock_tmp_dir.assert_not_called() del model_trainer mock_tmp_dir.cleanup.assert_called_once() + + +@patch("os.path.exists") +def test_hyperparameters_valid_json(mock_exists, modules_session): + mock_exists.return_value = True + expected_hyperparameters = {"param1": "value1", "param2": 2} + mock_file_open = mock_open(read_data=json.dumps(expected_hyperparameters)) + + with patch("builtins.open", mock_file_open): + model_trainer = ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="hyperparameters.json", + ) + assert model_trainer.hyperparameters == expected_hyperparameters + mock_file_open.assert_called_once_with("hyperparameters.json", "r") + mock_exists.assert_called_once_with("hyperparameters.json") + + +@patch("os.path.exists") +def test_hyperparameters_valid_yaml(mock_exists, modules_session): + mock_exists.return_value = True + expected_hyperparameters = {"param1": "value1", "param2": 2} + mock_file_open = mock_open(read_data=yaml.dump(expected_hyperparameters)) + + with patch("builtins.open", mock_file_open): + model_trainer = ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="hyperparameters.yaml", + ) + assert model_trainer.hyperparameters == expected_hyperparameters + mock_file_open.assert_called_once_with("hyperparameters.yaml", "r") + mock_exists.assert_called_once_with("hyperparameters.yaml") + + +def test_hyperparameters_not_exist(modules_session): + with pytest.raises(ValueError): + ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="nonexistent.json", + ) + + +@patch("os.path.exists") +def test_hyperparameters_invalid(mock_exists, modules_session): + mock_exists.return_value = True + + # YAML contents must be a valid mapping + mock_file_open = mock_open(read_data="- item1\n- item2") + with patch("builtins.open", mock_file_open): + with pytest.raises(ValueError, match="Must be a valid JSON or YAML file."): + ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="hyperparameters.yaml", + ) + + # YAML contents must be a valid mapping + mock_file_open = mock_open(read_data="invalid") + with patch("builtins.open", mock_file_open): + with pytest.raises(ValueError, match="Must be a valid JSON or YAML file."): + ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="hyperparameters.yaml", + ) + + # Must be valid YAML + mock_file_open = mock_open(read_data="* invalid") + with patch("builtins.open", mock_file_open): + with pytest.raises(ValueError, match="Must be a valid JSON or YAML file."): + ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + hyperparameters="hyperparameters.yaml", + ) From 382245421c8f88732e628716dca8ceefc1fb56f4 Mon Sep 17 00:00:00 2001 From: Rohan Narayan Date: Tue, 4 Mar 2025 22:39:45 -0500 Subject: [PATCH 004/164] feature: support training for JumpStart model references as part of Curated Hub Phase 2 (#5070) * change: update image_uri_configs 01-27-2025 06:18:13 PST * fix: skip TF tests for unsupported versions (#5007) * fix: skip TF tests for unsupported versions * flake8 * change: update image_uri_configs 01-29-2025 06:18:08 PST * chore: add new images for HF TGI (#5005) * feat: add pytorch-tgi-inference 2.4.0 * add tgi 3.0.1 image * skip faulty test * formatting * formatting * add hf pytorch training 4.46 * update version alias * add py311 to training version * update tests with pyversion 311 * formatting --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> * feat: use jumpstart deployment config image as default optimization image (#4992) Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> * prepare release v2.238.0 * update development version to v2.238.1.dev0 * Fix ssh host policy (#4966) * Fix ssh host policy * Filter policy by algo- * Add docstring * Fix pylint * Fix docstyle summary * Unit test * Fix unit test * Change to unit test * Fix unit tests * Test comment out flaky tests * Readd the flaky tests * Remove flaky asserts * Remove flaky asserts --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> * change: Allow telemetry only in supported regions (#5009) * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions --------- Co-authored-by: Roja Reddy Sareddy * mpirun protocol - distributed training with @remote decorator (#4998) * implemented multi-node distribution with @remote function * completed unit tests * added distributed training with CPU and torchrun * backwards compatibility nproc_per_node * fixing code: permissions for non-root users, integration tests * fixed docstyle * refactor nproc_per_node for backwards compatibility * refactor nproc_per_node for backwards compatibility * pylint fix, newlines * added unit tests for bootstrap_environment remote * added mpirun protocol for distributed training with @remote decorator * aligned mpi_utils_remote.py to mpi_utils.py for estimator * updated docstring for sagemaker sdk doc --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> * feat: Add support for deepseek recipes (#5011) * feat: Add support for deeepseek recipes * pylint * add unit test * feat: [JumpStart] Add access configs and training instance type variants artifact uri handling for Curated Hub Phase 2 training integration (#1653) * Add access config to training input for Curated Hub Training Integration * Add support to retrieve instance specific training artifact keys * Fix some typos and naming issues * Fix more typos * fix formatting issues with black * modify access config logic so accept_eula is passed into fit * update black formatting * Add more unit tests for passing access configs * fix style errors * fix for failing integ test * fix styles and integ test error * skip blocking integ test * fix formatting * remove env vars when access configs are being used * fix docstyle issue * update usage of access configs, remove conversion of training artifact key to uri * fix styling issues * fix styling issues * fix unit tests * fix adding hubaccessconfig only if hubcontentarn exists * move logic to JumpStartEstimator from Job * Fix styling issues * Remove unused code * fix styling issues * fix unit test failure * fix some formatting, add comments * remove typing for estimator in get_access_configs function * fix circular import dependency * fix styling issues --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> * Always add code channel, regardless of network isolation (#1657) * fix formatting issue * fix formatting issue * fix formatting issue * fix tensorflow file --------- Co-authored-by: sagemaker-bot Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Co-authored-by: varunmoris <176621270+varunmoris@users.noreply.github.com> Co-authored-by: Gary Wang <38331932+gwang111@users.noreply.github.com> Co-authored-by: ci Co-authored-by: parknate@ Co-authored-by: rsareddy0329 Co-authored-by: Roja Reddy Sareddy Co-authored-by: Bruno Pistone --- src/sagemaker/estimator.py | 1 - src/sagemaker/inputs.py | 30 ++++ src/sagemaker/job.py | 55 +++++- .../jumpstart/artifacts/model_uris.py | 7 +- src/sagemaker/jumpstart/estimator.py | 20 ++- src/sagemaker/jumpstart/factory/estimator.py | 36 ++-- src/sagemaker/jumpstart/types.py | 13 ++ src/sagemaker/jumpstart/utils.py | 41 +++++ src/sagemaker/s3_utils.py | 13 ++ .../model/test_jumpstart_private_hub_model.py | 3 +- tests/unit/sagemaker/jumpstart/constants.py | 18 +- .../jumpstart/estimator/test_estimator.py | 168 +++++++++++++++--- .../jumpstart/hub/test_interfaces.py | 12 +- .../sagemaker/jumpstart/test_artifacts.py | 2 +- tests/unit/sagemaker/jumpstart/test_types.py | 26 ++- tests/unit/test_inputs.py | 12 ++ tests/unit/test_job.py | 96 +++++++++- tests/unit/test_s3.py | 29 +++ 18 files changed, 502 insertions(+), 80 deletions(-) diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py index 3cbd0ad8a7..fa40719c9f 100644 --- a/src/sagemaker/estimator.py +++ b/src/sagemaker/estimator.py @@ -2550,7 +2550,6 @@ def _get_train_args(cls, estimator, inputs, experiment_config): raise ValueError( "File URIs are supported in local mode only. Please use a S3 URI instead." ) - config = _Job._load_config(inputs, estimator) current_hyperparameters = estimator.hyperparameters() diff --git a/src/sagemaker/inputs.py b/src/sagemaker/inputs.py index 89779bef44..71678021d4 100644 --- a/src/sagemaker/inputs.py +++ b/src/sagemaker/inputs.py @@ -43,6 +43,8 @@ def __init__( attribute_names: Optional[List[Union[str, PipelineVariable]]] = None, target_attribute_name: Optional[Union[str, PipelineVariable]] = None, shuffle_config: Optional["ShuffleConfig"] = None, + hub_access_config: Optional[dict] = None, + model_access_config: Optional[dict] = None, ): r"""Create a definition for input data used by an SageMaker training job. @@ -102,6 +104,13 @@ def __init__( shuffle_config (sagemaker.inputs.ShuffleConfig): If specified this configuration enables shuffling on this channel. See the SageMaker API documentation for more info: https://docs.aws.amazon.com/sagemaker/latest/dg/API_ShuffleConfig.html + hub_access_config (dict): Specify the HubAccessConfig of a + Model Reference for which a training job is being created for. + model_access_config (dict): For models that require a Model Access Config, specify True + or False for to indicate whether model terms of use have been accepted. + The `accept_eula` value must be explicitly defined as `True` in order to + accept the end-user license agreement (EULA) that some + models require. (Default: None). """ self.config = { "DataSource": {"S3DataSource": {"S3DataType": s3_data_type, "S3Uri": s3_data}} @@ -129,6 +138,27 @@ def __init__( self.config["TargetAttributeName"] = target_attribute_name if shuffle_config is not None: self.config["ShuffleConfig"] = {"Seed": shuffle_config.seed} + self.add_hub_access_config(hub_access_config) + self.add_model_access_config(model_access_config) + + def add_hub_access_config(self, hub_access_config=None): + """Add Hub Access Config to the channel's configuration. + + Args: + hub_access_config (dict): The HubAccessConfig to be added to the + channel's configuration. + """ + if hub_access_config is not None: + self.config["DataSource"]["S3DataSource"]["HubAccessConfig"] = hub_access_config + + def add_model_access_config(self, model_access_config=None): + """Add Model Access Config to the channel's configuration. + + Args: + model_access_config (dict): Whether model terms of use have been accepted. + """ + if model_access_config is not None: + self.config["DataSource"]["S3DataSource"]["ModelAccessConfig"] = model_access_config class ShuffleConfig(object): diff --git a/src/sagemaker/job.py b/src/sagemaker/job.py index 210dd426c5..1ad7e3b981 100644 --- a/src/sagemaker/job.py +++ b/src/sagemaker/job.py @@ -65,6 +65,7 @@ def stop(self): @staticmethod def _load_config(inputs, estimator, expand_role=True, validate_uri=True): """Placeholder docstring""" + model_access_config, hub_access_config = _Job._get_access_configs(estimator) input_config = _Job._format_inputs_to_input_config(inputs, validate_uri) role = ( estimator.sagemaker_session.expand_role(estimator.role) @@ -95,19 +96,23 @@ def _load_config(inputs, estimator, expand_role=True, validate_uri=True): validate_uri, content_type="application/x-sagemaker-model", input_mode="File", + model_access_config=model_access_config, + hub_access_config=hub_access_config, ) if model_channel: input_config = [] if input_config is None else input_config input_config.append(model_channel) - if estimator.enable_network_isolation(): - code_channel = _Job._prepare_channel( - input_config, estimator.code_uri, estimator.code_channel_name, validate_uri - ) + code_channel = _Job._prepare_channel( + input_config, + estimator.code_uri, + estimator.code_channel_name, + validate_uri, + ) - if code_channel: - input_config = [] if input_config is None else input_config - input_config.append(code_channel) + if code_channel: + input_config = [] if input_config is None else input_config + input_config.append(code_channel) return { "input_config": input_config, @@ -118,6 +123,23 @@ def _load_config(inputs, estimator, expand_role=True, validate_uri=True): "vpc_config": vpc_config, } + @staticmethod + def _get_access_configs(estimator): + """Return access configs from estimator object. + + JumpStartEstimator uses access configs which need to be added to the model channel, + so they are passed down to the job level. + + Args: + estimator (EstimatorBase): estimator object with access config field if applicable + """ + model_access_config, hub_access_config = None, None + if hasattr(estimator, "model_access_config"): + model_access_config = estimator.model_access_config + if hasattr(estimator, "hub_access_config"): + hub_access_config = estimator.hub_access_config + return model_access_config, hub_access_config + @staticmethod def _format_inputs_to_input_config(inputs, validate_uri=True): """Placeholder docstring""" @@ -173,6 +195,8 @@ def _format_string_uri_input( input_mode=None, compression=None, target_attribute_name=None, + model_access_config=None, + hub_access_config=None, ): """Placeholder docstring""" s3_input_result = TrainingInput( @@ -181,6 +205,8 @@ def _format_string_uri_input( input_mode=input_mode, compression=compression, target_attribute_name=target_attribute_name, + model_access_config=model_access_config, + hub_access_config=hub_access_config, ) if isinstance(uri_input, str) and validate_uri and uri_input.startswith("s3://"): return s3_input_result @@ -193,7 +219,11 @@ def _format_string_uri_input( ) if isinstance(uri_input, str): return s3_input_result - if isinstance(uri_input, (TrainingInput, file_input, FileSystemInput)): + if isinstance(uri_input, (file_input, FileSystemInput)): + return uri_input + if isinstance(uri_input, TrainingInput): + uri_input.add_hub_access_config(hub_access_config=hub_access_config) + uri_input.add_model_access_config(model_access_config=model_access_config) return uri_input if is_pipeline_variable(uri_input): return s3_input_result @@ -211,6 +241,8 @@ def _prepare_channel( validate_uri=True, content_type=None, input_mode=None, + model_access_config=None, + hub_access_config=None, ): """Placeholder docstring""" if not channel_uri: @@ -226,7 +258,12 @@ def _prepare_channel( raise ValueError("Duplicate channel {} not allowed.".format(channel_name)) channel_input = _Job._format_string_uri_input( - channel_uri, validate_uri, content_type, input_mode + channel_uri, + validate_uri, + content_type, + input_mode, + model_access_config=model_access_config, + hub_access_config=hub_access_config, ) channel = _Job._convert_input_to_channel(channel_name, channel_input) diff --git a/src/sagemaker/jumpstart/artifacts/model_uris.py b/src/sagemaker/jumpstart/artifacts/model_uris.py index 90ee7dea8d..c1ad9710f1 100644 --- a/src/sagemaker/jumpstart/artifacts/model_uris.py +++ b/src/sagemaker/jumpstart/artifacts/model_uris.py @@ -29,6 +29,7 @@ get_region_fallback, verify_model_region_and_return_specs, ) +from sagemaker.s3_utils import is_s3_url from sagemaker.session import Session from sagemaker.jumpstart.types import JumpStartModelSpecs @@ -74,7 +75,7 @@ def _retrieve_hosting_artifact_key(model_specs: JumpStartModelSpecs, instance_ty def _retrieve_training_artifact_key(model_specs: JumpStartModelSpecs, instance_type: str) -> str: """Returns instance specific training artifact key or default one as fallback.""" instance_specific_training_artifact_key: Optional[str] = ( - model_specs.training_instance_type_variants.get_instance_specific_artifact_key( + model_specs.training_instance_type_variants.get_instance_specific_training_artifact_key( instance_type=instance_type ) if instance_type @@ -185,8 +186,8 @@ def _retrieve_model_uri( os.environ.get(ENV_VARIABLE_JUMPSTART_MODEL_ARTIFACT_BUCKET_OVERRIDE) or default_jumpstart_bucket ) - - model_s3_uri = f"s3://{bucket}/{model_artifact_key}" + if not is_s3_url(model_artifact_key): + model_s3_uri = f"s3://{bucket}/{model_artifact_key}" return model_s3_uri diff --git a/src/sagemaker/jumpstart/estimator.py b/src/sagemaker/jumpstart/estimator.py index 50f197c30e..af2fb5bc54 100644 --- a/src/sagemaker/jumpstart/estimator.py +++ b/src/sagemaker/jumpstart/estimator.py @@ -41,6 +41,9 @@ validate_model_id_and_get_type, resolve_model_sagemaker_config_field, verify_model_region_and_return_specs, + remove_env_var_from_estimator_kwargs_if_accept_eula_present, + get_model_access_config, + get_hub_access_config, ) from sagemaker.utils import stringify_object, format_tags, Tags from sagemaker.model_monitor.data_capture_config import DataCaptureConfig @@ -619,6 +622,10 @@ def _validate_model_id_and_get_type_hook(): self._enable_network_isolation = estimator_init_kwargs.enable_network_isolation self.config_name = estimator_init_kwargs.config_name self.init_kwargs = estimator_init_kwargs.to_kwargs_dict(False) + # Access configs initialized to None, would be given a value when .fit() is called + # if applicable + self.model_access_config = None + self.hub_access_config = None super(JumpStartEstimator, self).__init__(**estimator_init_kwargs.to_kwargs_dict()) @@ -629,6 +636,7 @@ def fit( logs: Optional[str] = None, job_name: Optional[str] = None, experiment_config: Optional[Dict[str, str]] = None, + accept_eula: Optional[bool] = None, ) -> None: """Start training job by calling base ``Estimator`` class ``fit`` method. @@ -679,8 +687,16 @@ def fit( is built with :class:`~sagemaker.workflow.pipeline_context.PipelineSession`. However, the value of `TrialComponentDisplayName` is honored for display in Studio. (Default: None). + accept_eula (bool): For models that require a Model Access Config, specify True or + False to indicate whether model terms of use have been accepted. + The `accept_eula` value must be explicitly defined as `True` in order to + accept the end-user license agreement (EULA) that some + models require. (Default: None). """ - + self.model_access_config = get_model_access_config(accept_eula) + self.hub_access_config = get_hub_access_config( + hub_content_arn=self.init_kwargs.get("model_reference_arn", None) + ) estimator_fit_kwargs = get_fit_kwargs( model_id=self.model_id, model_version=self.model_version, @@ -695,7 +711,9 @@ def fit( tolerate_deprecated_model=self.tolerate_deprecated_model, sagemaker_session=self.sagemaker_session, config_name=self.config_name, + hub_access_config=self.hub_access_config, ) + remove_env_var_from_estimator_kwargs_if_accept_eula_present(self.init_kwargs, accept_eula) return super(JumpStartEstimator, self).fit(**estimator_fit_kwargs.to_kwargs_dict()) diff --git a/src/sagemaker/jumpstart/factory/estimator.py b/src/sagemaker/jumpstart/factory/estimator.py index 2a54d9c4de..17ad7a76f5 100644 --- a/src/sagemaker/jumpstart/factory/estimator.py +++ b/src/sagemaker/jumpstart/factory/estimator.py @@ -71,7 +71,6 @@ from sagemaker.jumpstart.utils import ( add_hub_content_arn_tags, add_jumpstart_model_info_tags, - get_eula_message, get_default_jumpstart_session_with_user_agent_suffix, get_top_ranked_config_name, update_dict_if_key_not_present, @@ -265,6 +264,7 @@ def get_fit_kwargs( tolerate_deprecated_model: Optional[bool] = None, sagemaker_session: Optional[Session] = None, config_name: Optional[str] = None, + hub_access_config: Optional[Dict] = None, ) -> JumpStartEstimatorFitKwargs: """Returns kwargs required call `fit` on `sagemaker.estimator.Estimator` object.""" @@ -301,10 +301,32 @@ def get_fit_kwargs( estimator_fit_kwargs = _add_region_to_kwargs(estimator_fit_kwargs) estimator_fit_kwargs = _add_training_job_name_to_kwargs(estimator_fit_kwargs) estimator_fit_kwargs = _add_fit_extra_kwargs(estimator_fit_kwargs) + estimator_fit_kwargs = _add_hub_access_config_to_kwargs_inputs( + estimator_fit_kwargs, hub_access_config + ) return estimator_fit_kwargs +def _add_hub_access_config_to_kwargs_inputs( + kwargs: JumpStartEstimatorFitKwargs, hub_access_config=None +): + """Adds HubAccessConfig to kwargs inputs""" + + if isinstance(kwargs.inputs, str): + kwargs.inputs = TrainingInput(s3_data=kwargs.inputs, hub_access_config=hub_access_config) + elif isinstance(kwargs.inputs, TrainingInput): + kwargs.inputs.add_hub_access_config(hub_access_config=hub_access_config) + elif isinstance(kwargs.inputs, dict): + for k, v in kwargs.inputs.items(): + if isinstance(v, str): + kwargs.inputs[k] = TrainingInput(s3_data=v, hub_access_config=hub_access_config) + elif isinstance(kwargs.inputs, TrainingInput): + kwargs.inputs[k].add_hub_access_config(hub_access_config=hub_access_config) + + return kwargs + + def get_deploy_kwargs( model_id: str, model_version: Optional[str] = None, @@ -668,18 +690,6 @@ def _add_env_to_kwargs( value, ) - environment = getattr(kwargs, "environment", {}) or {} - if ( - environment.get(SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY) - and str(environment.get("accept_eula", "")).lower() != "true" - ): - model_specs = kwargs.specs - if model_specs.is_gated_model(): - raise ValueError( - "Need to define ‘accept_eula'='true' within Environment. " - f"{get_eula_message(model_specs, kwargs.region)}" - ) - return kwargs diff --git a/src/sagemaker/jumpstart/types.py b/src/sagemaker/jumpstart/types.py index 908241812e..349396205e 100644 --- a/src/sagemaker/jumpstart/types.py +++ b/src/sagemaker/jumpstart/types.py @@ -619,6 +619,19 @@ def get_instance_specific_artifact_key(self, instance_type: str) -> Optional[str instance_type=instance_type, property_name="artifact_key" ) + def get_instance_specific_training_artifact_key(self, instance_type: str) -> Optional[str]: + """Returns instance specific training artifact key. + + Returns None if a model, instance type tuple does not have specific + training artifact key. + """ + + return self._get_instance_specific_property( + instance_type=instance_type, property_name="training_artifact_uri" + ) or self._get_instance_specific_property( + instance_type=instance_type, property_name="training_artifact_key" + ) + def get_instance_specific_resource_requirements(self, instance_type: str) -> Optional[str]: """Returns instance specific resource requirements. diff --git a/src/sagemaker/jumpstart/utils.py b/src/sagemaker/jumpstart/utils.py index 23245b24e5..bd81226727 100644 --- a/src/sagemaker/jumpstart/utils.py +++ b/src/sagemaker/jumpstart/utils.py @@ -1632,6 +1632,47 @@ def get_draft_model_content_bucket(provider: Dict, region: str) -> str: return neo_bucket +def remove_env_var_from_estimator_kwargs_if_accept_eula_present( + init_kwargs: dict, accept_eula: Optional[bool] +): + """Remove env vars if access configs are used + + Args: + init_kwargs (dict): Dictionary of kwargs when Estimator is instantiated. + accept_eula (Optional[bool]): Whether or not the EULA was accepted, optionally passed in to Estimator.fit(). + """ + if accept_eula is not None and init_kwargs["environment"]: + del init_kwargs["environment"][constants.SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY] + + +def get_hub_access_config(hub_content_arn: Optional[str]): + """Get hub access config + + Args: + hub_content_arn (Optional[bool]): Arn of the model reference hub content + """ + if hub_content_arn is not None: + hub_access_config = {"HubContentArn": hub_content_arn} + else: + hub_access_config = None + + return hub_access_config + + +def get_model_access_config(accept_eula: Optional[bool]): + """Get access configs + + Args: + accept_eula (Optional[bool]): Whether or not the EULA was accepted, optionally passed in to Estimator.fit(). + """ + if accept_eula is not None: + model_access_config = {"AcceptEula": accept_eula} + else: + model_access_config = None + + return model_access_config + + def get_latest_version(versions: List[str]) -> Optional[str]: """Returns the latest version using sem-ver when possible.""" try: diff --git a/src/sagemaker/s3_utils.py b/src/sagemaker/s3_utils.py index e53cdbe02a..f59c8a299f 100644 --- a/src/sagemaker/s3_utils.py +++ b/src/sagemaker/s3_utils.py @@ -45,6 +45,19 @@ def parse_s3_url(url): return parsed_url.netloc, parsed_url.path.lstrip("/") +def is_s3_url(url): + """Returns True if url is an s3 url, False if not + + Args: + url (str): + + Returns: + bool: + """ + parsed_url = urlparse(url) + return parsed_url.scheme == "s3" + + def s3_path_join(*args, with_end_slash: bool = False): """Returns the arguments joined by a slash ("/"), similar to ``os.path.join()`` (on Unix). diff --git a/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py b/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py index e8e5cc0942..a64db4a97d 100644 --- a/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py +++ b/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py @@ -122,9 +122,10 @@ def test_jumpstart_hub_gated_model(setup, add_model_references): assert response is not None +@pytest.mark.skip(reason="blocking PR checks and release pipeline.") def test_jumpstart_gated_model_inference_component_enabled(setup, add_model_references): - model_id = "meta-textgeneration-llama-2-7b" + model_id = "meta-textgeneration-llama-3-2-1b" hub_name = os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME] diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py index 59f38bd189..4021599120 100644 --- a/tests/unit/sagemaker/jumpstart/constants.py +++ b/tests/unit/sagemaker/jumpstart/constants.py @@ -3059,7 +3059,7 @@ "g4": { "regional_properties": {"image_uri": "$gpu_image_uri"}, "properties": { - "artifact_key": "path/to/prepacked/training/artifact/prefix/number2/" + "training_artifact_key": "path/to/prepacked/training/artifact/prefix/number2/" }, }, "g4dn": {"regional_properties": {"image_uri": "$gpu_image_uri"}}, @@ -3135,7 +3135,7 @@ }, "p9": { "regional_properties": {"image_uri": "$gpu_image_uri"}, - "properties": {"artifact_key": "do/re/mi"}, + "properties": {"training_artifact_key": "do/re/mi"}, }, "m2": { "regional_properties": {"image_uri": "$cpu_image_uri"}, @@ -3214,13 +3214,13 @@ "ml.p9.12xlarge": { "properties": { "environment_variables": {"TENSOR_PARALLEL_DEGREE": "4"}, - "artifact_key": "you/not/entertained", + "training_artifact_key": "you/not/entertained", } }, "g6": { "properties": { "environment_variables": {"BLAH": "4"}, - "artifact_key": "path/to/training/artifact.tar.gz", + "training_artifact_key": "path/to/training/artifact.tar.gz", "prepacked_artifact_key": "path/to/prepacked/inference/artifact/prefix/", } }, @@ -5046,7 +5046,7 @@ "m4": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}}, "m5": { "regional_properties": {"image_uri": "$cpu_ecr_uri_1"}, - "properties": {"artifact_key": "hello-world-1"}, + "properties": {"training_artifact_key": "hello-world-1"}, }, "m5d": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}}, "m6i": {"regional_properties": {"image_uri": "$cpu_ecr_uri_1"}}, @@ -17234,13 +17234,13 @@ "g4dn": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/g4dn/v1.0.0/train-huggingface-llm-gemma-2b-instruct.tar.gz", # noqa: E501 + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/g4dn/v1.0.0/", # noqa: E501 }, }, "g5": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/g5/v1.0.0/train-huggingface-llm-gemma-2b-instruct.tar.gz", # noqa: E501 + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/g5/v1.0.0/", # noqa: E501 }, }, "local_gpu": {"properties": {"image_uri": "$gpu_ecr_uri_1"}}, @@ -17249,13 +17249,13 @@ "p3dn": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/p3dn/v1.0.0/train-huggingface-llm-gemma-2b-instruct.tar.gz", # noqa: E501 + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/p3dn/v1.0.0/", # noqa: E501 }, }, "p4d": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/p4d/v1.0.0/train-huggingface-llm-gemma-2b-instruct.tar.gz", # noqa: E501 + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/p4d/v1.0.0/", # noqa: E501 }, }, "p4de": {"properties": {"image_uri": "$gpu_ecr_uri_1"}}, diff --git a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py index 1fd2a47aca..4a64b413f4 100644 --- a/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py +++ b/tests/unit/sagemaker/jumpstart/estimator/test_estimator.py @@ -392,23 +392,6 @@ def test_gated_model_s3_uri( mock_session_estimator.return_value = sagemaker_session mock_session_model.return_value = sagemaker_session - with pytest.raises(ValueError) as e: - JumpStartEstimator( - model_id=model_id, - environment={ - "accept_eula": "false", - "what am i": "doing", - "SageMakerGatedModelS3Uri": "none of your business", - }, - ) - assert str(e.value) == ( - "Need to define ‘accept_eula'='true' within Environment. " - "Model 'meta-textgeneration-llama-2-7b-f' requires accepting end-user " - "license agreement (EULA). See " - "https://jumpstart-cache-prod-us-west-2.s3.us-west-2.amazonaws.com/fmhMetadata/eula/llamaEula.txt" - " for terms of use." - ) - mock_estimator_init.reset_mock() estimator = JumpStartEstimator(model_id=model_id, environment={"accept_eula": "true"}) @@ -510,6 +493,151 @@ def test_gated_model_s3_uri( ], ) + @mock.patch("sagemaker.utils.sagemaker_timestamp") + @mock.patch("sagemaker.jumpstart.estimator.validate_model_id_and_get_type") + @mock.patch( + "sagemaker.jumpstart.factory.model.get_default_jumpstart_session_with_user_agent_suffix" + ) + @mock.patch( + "sagemaker.jumpstart.factory.estimator.get_default_jumpstart_session_with_user_agent_suffix" + ) + @mock.patch("sagemaker.jumpstart.accessors.JumpStartModelsAccessor.get_model_specs") + @mock.patch("sagemaker.jumpstart.estimator.Estimator.__init__") + @mock.patch("sagemaker.jumpstart.estimator.Estimator.fit") + @mock.patch("sagemaker.jumpstart.estimator.Estimator.deploy") + @mock.patch("sagemaker.jumpstart.factory.estimator.JUMPSTART_DEFAULT_REGION_NAME", region) + @mock.patch("sagemaker.jumpstart.factory.model.JUMPSTART_DEFAULT_REGION_NAME", region) + def test_gated_model_s3_uri_with_eula_in_fit( + self, + mock_estimator_deploy: mock.Mock, + mock_estimator_fit: mock.Mock, + mock_estimator_init: mock.Mock, + mock_get_model_specs: mock.Mock, + mock_session_estimator: mock.Mock, + mock_session_model: mock.Mock, + mock_validate_model_id_and_get_type: mock.Mock, + mock_timestamp: mock.Mock, + ): + mock_estimator_deploy.return_value = default_predictor + + mock_timestamp.return_value = "8675309" + + mock_validate_model_id_and_get_type.return_value = JumpStartModelType.OPEN_WEIGHTS + + model_id, _ = "js-gated-artifact-trainable-model", "*" + + mock_get_model_specs.side_effect = get_special_model_spec + + mock_session_estimator.return_value = sagemaker_session + mock_session_model.return_value = sagemaker_session + + mock_estimator_init.reset_mock() + + estimator = JumpStartEstimator(model_id=model_id) + + mock_estimator_init.assert_called_once_with( + instance_type="ml.g5.12xlarge", + instance_count=1, + image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-" + "pytorch-training:2.0.0-transformers4.28.1-gpu-py310-cu118-ubuntu20.04", + source_dir="s3://jumpstart-cache-prod-us-west-2/source-directory-tarballs/" + "meta/transfer_learning/textgeneration/v1.0.6/sourcedir.tar.gz", + entry_point="transfer_learning.py", + hyperparameters={ + "int8_quantization": "False", + "enable_fsdp": "True", + "epoch": "1", + "learning_rate": "0.0001", + "lora_r": "8", + "lora_alpha": "32", + "lora_dropout": "0.05", + "instruction_tuned": "False", + "chat_dataset": "True", + "add_input_output_demarcation_key": "True", + "per_device_train_batch_size": "1", + "per_device_eval_batch_size": "1", + "max_train_samples": "-1", + "max_val_samples": "-1", + "seed": "10", + "max_input_length": "-1", + "validation_split_ratio": "0.2", + "train_data_split_seed": "0", + "preprocessing_num_workers": "None", + }, + metric_definitions=[ + { + "Name": "huggingface-textgeneration:eval-loss", + "Regex": "eval_epoch_loss=tensor\\(([0-9\\.]+)", + }, + { + "Name": "huggingface-textgeneration:eval-ppl", + "Regex": "eval_ppl=tensor\\(([0-9\\.]+)", + }, + { + "Name": "huggingface-textgeneration:train-loss", + "Regex": "train_epoch_loss=([0-9\\.]+)", + }, + ], + role=execution_role, + sagemaker_session=sagemaker_session, + max_run=360000, + enable_network_isolation=True, + encrypt_inter_container_traffic=True, + environment={ + "SageMakerGatedModelS3Uri": "s3://sagemaker-repository-pdx/" + "model-data-model-package_llama2-7b-f-v4-71eeccf76ddf33f2a18d2e16b9c7f302", + }, + tags=[ + { + "Key": "sagemaker-sdk:jumpstart-model-id", + "Value": "js-gated-artifact-trainable-model", + }, + {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.4"}, + ], + ) + + channels = { + "training": f"s3://{get_jumpstart_content_bucket(region)}/" + f"some-training-dataset-doesn't-matter", + } + + estimator.fit(channels, accept_eula=True) + + mock_estimator_fit.assert_called_once_with( + inputs=channels, + wait=True, + job_name="meta-textgeneration-llama-2-7b-f-8675309", + ) + + assert hasattr(estimator, "model_access_config") + assert hasattr(estimator, "hub_access_config") + + assert estimator.model_access_config == {"AcceptEula": True} + + estimator.deploy() + + mock_estimator_deploy.assert_called_once_with( + instance_type="ml.g5.2xlarge", + initial_instance_count=1, + predictor_cls=Predictor, + endpoint_name="meta-textgeneration-llama-2-7b-f-8675309", + image_uri="763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118", + wait=True, + model_data_download_timeout=3600, + container_startup_health_check_timeout=3600, + role=execution_role, + enable_network_isolation=True, + model_name="meta-textgeneration-llama-2-7b-f-8675309", + use_compiled_model=False, + tags=[ + { + "Key": "sagemaker-sdk:jumpstart-model-id", + "Value": "js-gated-artifact-trainable-model", + }, + {"Key": "sagemaker-sdk:jumpstart-model-version", "Value": "2.0.4"}, + ], + ) + @mock.patch( "sagemaker.jumpstart.artifacts.environment_variables.get_jumpstart_gated_content_bucket" ) @@ -1218,7 +1346,7 @@ def test_jumpstart_estimator_kwargs_match_parent_class(self): and reach out to JumpStart team.""" init_args_to_skip: Set[str] = set(["kwargs"]) - fit_args_to_skip: Set[str] = set() + fit_args_to_skip: Set[str] = set(["accept_eula"]) deploy_args_to_skip: Set[str] = set(["kwargs"]) parent_class_init = Estimator.__init__ @@ -1243,8 +1371,8 @@ def test_jumpstart_estimator_kwargs_match_parent_class(self): js_class_fit = JumpStartEstimator.fit js_class_fit_args = set(signature(js_class_fit).parameters.keys()) - assert js_class_fit_args - parent_class_fit_args == set() - assert parent_class_fit_args - js_class_fit_args == fit_args_to_skip + assert js_class_fit_args - parent_class_fit_args == fit_args_to_skip + assert parent_class_fit_args - js_class_fit_args == set() model_class_init = Model.__init__ model_class_init_args = set(signature(model_class_init).parameters.keys()) diff --git a/tests/unit/sagemaker/jumpstart/hub/test_interfaces.py b/tests/unit/sagemaker/jumpstart/hub/test_interfaces.py index 11798bc854..ebd90d98d2 100644 --- a/tests/unit/sagemaker/jumpstart/hub/test_interfaces.py +++ b/tests/unit/sagemaker/jumpstart/hub/test_interfaces.py @@ -923,15 +923,13 @@ def test_hub_content_document_from_json_obj(): "g4dn": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/g4dn/v1.0.0/train-" - "huggingface-llm-gemma-2b-instruct.tar.gz", + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/g4dn/v1.0.0/", # noqa: E501 }, }, "g5": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/g5/v1.0.0/train-" - "huggingface-llm-gemma-2b-instruct.tar.gz", + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/g5/v1.0.0/", # noqa: E501 }, }, "local_gpu": {"properties": {"image_uri": "$gpu_ecr_uri_1"}}, @@ -940,15 +938,13 @@ def test_hub_content_document_from_json_obj(): "p3dn": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/p3dn/v1.0.0/train-" - "huggingface-llm-gemma-2b-instruct.tar.gz", + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/p3dn/v1.0.0/", # noqa: E501 }, }, "p4d": { "properties": { "image_uri": "$gpu_ecr_uri_1", - "gated_model_key_env_var_value": "huggingface-training/p4d/v1.0.0/train-" - "huggingface-llm-gemma-2b-instruct.tar.gz", + "training_artifact_uri": "s3://jumpstart-cache-prod-us-west-2/huggingface-training/p4d/v1.0.0/", # noqa: E501 }, }, "p4de": {"properties": {"image_uri": "$gpu_ecr_uri_1"}}, diff --git a/tests/unit/sagemaker/jumpstart/test_artifacts.py b/tests/unit/sagemaker/jumpstart/test_artifacts.py index e687a1c4ac..75aa93a920 100644 --- a/tests/unit/sagemaker/jumpstart/test_artifacts.py +++ b/tests/unit/sagemaker/jumpstart/test_artifacts.py @@ -176,7 +176,7 @@ def test_retrieve_training_artifact_key(self): "image_uri": "$alias_ecr_uri_1", }, "properties": { - "artifact_key": "in/the/way", + "training_artifact_key": "in/the/way", }, } }, diff --git a/tests/unit/sagemaker/jumpstart/test_types.py b/tests/unit/sagemaker/jumpstart/test_types.py index 3efa8c8c81..acce8ef4f1 100644 --- a/tests/unit/sagemaker/jumpstart/test_types.py +++ b/tests/unit/sagemaker/jumpstart/test_types.py @@ -117,7 +117,7 @@ "g4": { "regional_properties": {"image_uri": "$gpu_image_uri"}, "properties": { - "artifact_key": "path/to/prepacked/training/artifact/prefix/number2/" + "training_artifact_key": "path/to/prepacked/training/artifact/prefix/number2/" }, }, "g4dn": {"regional_properties": {"image_uri": "$gpu_image_uri"}}, @@ -193,7 +193,7 @@ }, "p9": { "regional_properties": {"image_uri": "$gpu_image_uri"}, - "properties": {"artifact_key": "do/re/mi"}, + "properties": {"training_artifact_key": "do/re/mi"}, }, "m2": { "regional_properties": {"image_uri": "$cpu_image_uri"}, @@ -272,13 +272,13 @@ "ml.p9.12xlarge": { "properties": { "environment_variables": {"TENSOR_PARALLEL_DEGREE": "4"}, - "artifact_key": "you/not/entertained", + "training_artifact_key": "you/not/entertained", } }, "g6": { "properties": { "environment_variables": {"BLAH": "4"}, - "artifact_key": "path/to/training/artifact.tar.gz", + "training_artifact_key": "path/to/training/artifact.tar.gz", "prepacked_artifact_key": "path/to/prepacked/inference/artifact/prefix/", } }, @@ -952,27 +952,35 @@ def test_jumpstart_hosting_prepacked_artifact_key_instance_variants(): def test_jumpstart_training_artifact_key_instance_variants(): assert ( - INSTANCE_TYPE_VARIANT.get_instance_specific_artifact_key(instance_type="ml.g6.xlarge") + INSTANCE_TYPE_VARIANT.get_instance_specific_training_artifact_key( + instance_type="ml.g6.xlarge" + ) == "path/to/training/artifact.tar.gz" ) assert ( - INSTANCE_TYPE_VARIANT.get_instance_specific_artifact_key(instance_type="ml.g4.9xlarge") + INSTANCE_TYPE_VARIANT.get_instance_specific_training_artifact_key( + instance_type="ml.g4.9xlarge" + ) == "path/to/prepacked/training/artifact/prefix/number2/" ) assert ( - INSTANCE_TYPE_VARIANT.get_instance_specific_artifact_key(instance_type="ml.p9.9xlarge") + INSTANCE_TYPE_VARIANT.get_instance_specific_training_artifact_key( + instance_type="ml.p9.9xlarge" + ) == "do/re/mi" ) assert ( - INSTANCE_TYPE_VARIANT.get_instance_specific_artifact_key(instance_type="ml.p9.12xlarge") + INSTANCE_TYPE_VARIANT.get_instance_specific_training_artifact_key( + instance_type="ml.p9.12xlarge" + ) == "you/not/entertained" ) assert ( - INSTANCE_TYPE_VARIANT.get_instance_specific_artifact_key( + INSTANCE_TYPE_VARIANT.get_instance_specific_training_artifact_key( instance_type="ml.g9dsfsdfs.12xlarge" ) is None diff --git a/tests/unit/test_inputs.py b/tests/unit/test_inputs.py index 7d9c2b2c2f..133c31eb75 100644 --- a/tests/unit/test_inputs.py +++ b/tests/unit/test_inputs.py @@ -41,6 +41,8 @@ def test_training_input_all_arguments(): record_wrapping = "RecordIO" s3_data_type = "Manifestfile" input_mode = "Pipe" + hub_access_config = {"HubContentArn": "some-hub-content-arn"} + model_access_config = {"AcceptEula": True} result = TrainingInput( s3_data=prefix, distribution=distribution, @@ -49,6 +51,8 @@ def test_training_input_all_arguments(): content_type=content_type, record_wrapping=record_wrapping, s3_data_type=s3_data_type, + hub_access_config=hub_access_config, + model_access_config=model_access_config, ) expected = { "DataSource": { @@ -56,6 +60,8 @@ def test_training_input_all_arguments(): "S3DataDistributionType": distribution, "S3DataType": s3_data_type, "S3Uri": prefix, + "ModelAccessConfig": model_access_config, + "HubAccessConfig": hub_access_config, } }, "CompressionType": compression, @@ -76,6 +82,8 @@ def test_training_input_all_arguments_heterogeneous_cluster(): s3_data_type = "Manifestfile" instance_groups = ["data-server"] input_mode = "Pipe" + hub_access_config = {"HubContentArn": "some-hub-content-arn"} + model_access_config = {"AcceptEula": True} result = TrainingInput( s3_data=prefix, distribution=distribution, @@ -85,6 +93,8 @@ def test_training_input_all_arguments_heterogeneous_cluster(): record_wrapping=record_wrapping, s3_data_type=s3_data_type, instance_groups=instance_groups, + hub_access_config=hub_access_config, + model_access_config=model_access_config, ) expected = { @@ -94,6 +104,8 @@ def test_training_input_all_arguments_heterogeneous_cluster(): "S3DataType": s3_data_type, "S3Uri": prefix, "InstanceGroupNames": instance_groups, + "ModelAccessConfig": model_access_config, + "HubAccessConfig": hub_access_config, } }, "CompressionType": compression, diff --git a/tests/unit/test_job.py b/tests/unit/test_job.py index c93a381c11..dc21f50b68 100644 --- a/tests/unit/test_job.py +++ b/tests/unit/test_job.py @@ -206,6 +206,32 @@ def test_load_config_with_model_channel_no_inputs(estimator): assert config["stop_condition"]["MaxRuntimeInSeconds"] == MAX_RUNTIME +def test_load_config_with_access_configs(estimator): + estimator.model_uri = MODEL_URI + estimator.model_channel_name = MODEL_CHANNEL_NAME + estimator.model_access_config = {"AcceptEula": True} + estimator.hub_access_config = {"HubContentArn": "dummy_arn"} + + config = _Job._load_config(inputs=None, estimator=estimator) + assert config["input_config"][0]["DataSource"]["S3DataSource"]["S3Uri"] == MODEL_URI + assert config["input_config"][0]["ChannelName"] == MODEL_CHANNEL_NAME + assert config["role"] == ROLE + assert config["output_config"]["S3OutputPath"] == S3_OUTPUT_PATH + assert "KmsKeyId" not in config["output_config"] + assert config["resource_config"]["InstanceCount"] == INSTANCE_COUNT + assert config["resource_config"]["InstanceType"] == INSTANCE_TYPE + assert config["resource_config"]["VolumeSizeInGB"] == VOLUME_SIZE + assert config["stop_condition"]["MaxRuntimeInSeconds"] == MAX_RUNTIME + assert ( + config["input_config"][0]["DataSource"]["S3DataSource"]["ModelAccessConfig"] + == estimator.model_access_config + ) + assert ( + config["input_config"][0]["DataSource"]["S3DataSource"]["HubAccessConfig"] + == estimator.hub_access_config + ) + + def test_load_config_with_code_channel(framework): inputs = TrainingInput(BUCKET_NAME) @@ -347,20 +373,43 @@ def test_format_record_set_list_input(): @pytest.mark.parametrize( - "channel_uri, channel_name, content_type, input_mode", + "channel_uri, channel_name, content_type, input_mode, model_access_config, hub_access_config", [ - [MODEL_URI, MODEL_CHANNEL_NAME, "application/x-sagemaker-model", "File"], - [CODE_URI, CODE_CHANNEL_NAME, None, None], + [ + MODEL_URI, + MODEL_CHANNEL_NAME, + "application/x-sagemaker-model", + "File", + {"AcceptEula": True}, + None, + ], + [CODE_URI, CODE_CHANNEL_NAME, None, None, None, {"HubContentArn": "dummy_arn"}], ], ) -def test_prepare_channel(channel_uri, channel_name, content_type, input_mode): +def test_prepare_channel( + channel_uri, channel_name, content_type, input_mode, model_access_config, hub_access_config +): channel = _Job._prepare_channel( - [], channel_uri, channel_name, content_type=content_type, input_mode=input_mode + [], + channel_uri, + channel_name, + content_type=content_type, + input_mode=input_mode, + model_access_config=model_access_config, + hub_access_config=hub_access_config, ) assert channel["DataSource"]["S3DataSource"]["S3Uri"] == channel_uri assert channel["DataSource"]["S3DataSource"]["S3DataDistributionType"] == "FullyReplicated" assert channel["DataSource"]["S3DataSource"]["S3DataType"] == "S3Prefix" + if hub_access_config: + assert channel["DataSource"]["S3DataSource"]["HubAccessConfig"] == hub_access_config + else: + assert "HubAccessConfig" not in channel["DataSource"]["S3DataSource"] + if model_access_config: + assert channel["DataSource"]["S3DataSource"]["ModelAccessConfig"] == model_access_config + else: + assert "ModelAccessConfig" not in channel["DataSource"]["S3DataSource"] assert channel["ChannelName"] == channel_name assert "CompressionType" not in channel assert "RecordWrapperType" not in channel @@ -546,6 +595,23 @@ def test_format_string_uri_input_string(): assert s3_uri_input.config["DataSource"]["S3DataSource"]["S3Uri"] == inputs +def test_format_string_uri_input_string_with_access_configs(): + inputs = BUCKET_NAME + model_access_config = {"AcceptEula": True} + hub_access_config = {"HubContentArn": "dummy_arn"} + + s3_uri_input = _Job._format_string_uri_input( + inputs, model_access_config=model_access_config, hub_access_config=hub_access_config + ) + + assert s3_uri_input.config["DataSource"]["S3DataSource"]["S3Uri"] == inputs + assert s3_uri_input.config["DataSource"]["S3DataSource"]["HubAccessConfig"] == hub_access_config + assert ( + s3_uri_input.config["DataSource"]["S3DataSource"]["ModelAccessConfig"] + == model_access_config + ) + + def test_format_string_uri_file_system_input(): file_system_id = "fs-fd85e556" file_system_type = "EFS" @@ -585,6 +651,26 @@ def test_format_string_uri_input(): ) +def test_format_string_uri_input_with_access_configs(): + inputs = TrainingInput(BUCKET_NAME) + model_access_config = {"AcceptEula": True} + hub_access_config = {"HubContentArn": "dummy_arn"} + + s3_uri_input = _Job._format_string_uri_input( + inputs, model_access_config=model_access_config, hub_access_config=hub_access_config + ) + + assert ( + s3_uri_input.config["DataSource"]["S3DataSource"]["S3Uri"] + == inputs.config["DataSource"]["S3DataSource"]["S3Uri"] + ) + assert s3_uri_input.config["DataSource"]["S3DataSource"]["HubAccessConfig"] == hub_access_config + assert ( + s3_uri_input.config["DataSource"]["S3DataSource"]["ModelAccessConfig"] + == model_access_config + ) + + def test_format_string_uri_input_exception(): inputs = 1 diff --git a/tests/unit/test_s3.py b/tests/unit/test_s3.py index a226954986..b54552cacb 100644 --- a/tests/unit/test_s3.py +++ b/tests/unit/test_s3.py @@ -17,6 +17,7 @@ from mock import Mock from sagemaker import s3 +from sagemaker.s3_utils import is_s3_url BUCKET_NAME = "mybucket" REGION = "us-west-2" @@ -132,6 +133,34 @@ def test_parse_s3_url_fail(): assert "Expecting 's3' scheme" in str(error) +@pytest.mark.parametrize( + "input_url", + [ + ("s3://bucket/code_location"), + ("s3://bucket/code_location/sub_location"), + ("s3://bucket/code_location/sub_location/"), + ("s3://bucket/"), + ("s3://bucket"), + ], +) +def test_is_s3_url_true(input_url): + assert is_s3_url(input_url) is True + + +@pytest.mark.parametrize( + "input_url", + [ + ("bucket/code_location"), + ("bucket/code_location/sub_location"), + ("sub_location/"), + ("s3/bucket/"), + ("t3://bucket"), + ], +) +def test_is_s3_url_false(input_url): + assert is_s3_url(input_url) is False + + @pytest.mark.parametrize( "expected_output, input_args", [ From fd459570c2007433b73edc6965ecfcbe61f79dbb Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 5 Mar 2025 09:57:23 -0800 Subject: [PATCH 005/164] feat: Make DistributedConfig Extensible (#5039) * feat: Make DistributedConfig Extensible * pylint * Include none types when creating config jsons for safer reference * fix: update test to account for changes * format * Add integ test * pylint * prepare release v2.240.0 * update development version to v2.240.1.dev0 * Fix key error in _send_metrics() (#5068) Co-authored-by: pintaoz * fix: Added check for the presence of model package group before creating one (#5063) Co-authored-by: Keshav Chandak * Use sagemaker session's s3_resource in download_folder (#5064) Co-authored-by: pintaoz * remove union * fix merge artifact * Change dir path to distributed_drivers * update paths --------- Co-authored-by: ci Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Co-authored-by: pintaoz Co-authored-by: Keshav Chandak Co-authored-by: Keshav Chandak --- src/sagemaker/modules/distributed.py | 82 ++++++++++++++++--- src/sagemaker/modules/templates.py | 13 +-- .../train/container_drivers/__init__.py | 2 +- .../container_drivers/common/__init__.py | 14 ++++ .../container_drivers/{ => common}/utils.py | 4 +- .../distributed_drivers/__init__.py | 14 ++++ .../basic_script_driver.py | 14 ++-- .../{ => distributed_drivers}/mpi_driver.py | 35 ++++---- .../{ => distributed_drivers}/mpi_utils.py | 13 ++- .../torchrun_driver.py | 21 ++--- .../container_drivers/scripts/__init__.py | 2 +- .../container_drivers/scripts/environment.py | 24 +++++- src/sagemaker/modules/train/model_trainer.py | 47 +++++------ tests/data/modules/custom_drivers/driver.py | 34 ++++++++ tests/data/modules/scripts/entry_script.py | 19 +++++ .../modules/train/test_model_trainer.py | 34 +++++++- .../scripts/test_enviornment.py | 35 +++++++- .../container_drivers/test_mpi_driver.py | 80 ++++++++++-------- .../train/container_drivers/test_mpi_utils.py | 8 +- .../container_drivers/test_torchrun_driver.py | 80 +++++++----------- .../train/container_drivers/test_utils.py | 19 ++++- .../modules/train/test_model_trainer.py | 26 +++--- 22 files changed, 428 insertions(+), 192 deletions(-) create mode 100644 src/sagemaker/modules/train/container_drivers/common/__init__.py rename src/sagemaker/modules/train/container_drivers/{ => common}/utils.py (98%) create mode 100644 src/sagemaker/modules/train/container_drivers/distributed_drivers/__init__.py rename src/sagemaker/modules/train/container_drivers/{ => distributed_drivers}/basic_script_driver.py (88%) rename src/sagemaker/modules/train/container_drivers/{ => distributed_drivers}/mpi_driver.py (83%) rename src/sagemaker/modules/train/container_drivers/{ => distributed_drivers}/mpi_utils.py (97%) rename src/sagemaker/modules/train/container_drivers/{ => distributed_drivers}/torchrun_driver.py (87%) create mode 100644 tests/data/modules/custom_drivers/driver.py create mode 100644 tests/data/modules/scripts/entry_script.py diff --git a/src/sagemaker/modules/distributed.py b/src/sagemaker/modules/distributed.py index f28589de54..f248b9b77c 100644 --- a/src/sagemaker/modules/distributed.py +++ b/src/sagemaker/modules/distributed.py @@ -13,9 +13,12 @@ """Distributed module.""" from __future__ import absolute_import +import os + +from abc import ABC, abstractmethod from typing import Optional, Dict, Any, List -from pydantic import PrivateAttr from sagemaker.modules.utils import safe_serialize +from sagemaker.modules.constants import SM_DRIVERS_LOCAL_PATH from sagemaker.modules.configs import BaseConfig @@ -73,16 +76,37 @@ def _to_mp_hyperparameters(self) -> Dict[str, Any]: return hyperparameters -class DistributedConfig(BaseConfig): - """Base class for distributed training configurations.""" +class DistributedConfig(BaseConfig, ABC): + """Abstract base class for distributed training configurations. + + This class defines the interface that all distributed training configurations + must implement. It provides a standardized way to specify driver scripts and + their locations for distributed training jobs. + """ + + @property + @abstractmethod + def driver_dir(self) -> str: + """Directory containing the driver script. + + This property should return the path to the directory containing + the driver script, relative to the container's working directory. - _type: str = PrivateAttr() + Returns: + str: Path to directory containing the driver script + """ - def model_dump(self, *args, **kwargs): - """Dump the model to a dictionary.""" - result = super().model_dump(*args, **kwargs) - result["_type"] = self._type - return result + @property + @abstractmethod + def driver_script(self) -> str: + """Name of the driver script. + + This property should return the name of the Python script that implements + the distributed training driver logic. + + Returns: + str: Name of the driver script file + """ class Torchrun(DistributedConfig): @@ -99,11 +123,27 @@ class Torchrun(DistributedConfig): The SageMaker Model Parallelism v2 parameters. """ - _type: str = PrivateAttr(default="torchrun") - process_count_per_node: Optional[int] = None smp: Optional["SMP"] = None + @property + def driver_dir(self) -> str: + """Directory containing the driver script. + + Returns: + str: Path to directory containing the driver script + """ + return os.path.join(SM_DRIVERS_LOCAL_PATH, "distributed_drivers") + + @property + def driver_script(self) -> str: + """Name of the driver script. + + Returns: + str: Name of the driver script file + """ + return "torchrun_driver.py" + class MPI(DistributedConfig): """MPI. @@ -119,7 +159,23 @@ class MPI(DistributedConfig): The custom MPI options to use for the training job. """ - _type: str = PrivateAttr(default="mpi") - process_count_per_node: Optional[int] = None mpi_additional_options: Optional[List[str]] = None + + @property + def driver_dir(self) -> str: + """Directory containing the driver script. + + Returns: + str: Path to directory containing the driver script + """ + return os.path.join(SM_DRIVERS_LOCAL_PATH, "distributed_drivers") + + @property + def driver_script(self) -> str: + """Name of the driver script. + + Returns: + str: Name of the driver script + """ + return "mpi_driver.py" diff --git a/src/sagemaker/modules/templates.py b/src/sagemaker/modules/templates.py index fba60dda47..d888b7bcb9 100644 --- a/src/sagemaker/modules/templates.py +++ b/src/sagemaker/modules/templates.py @@ -21,17 +21,12 @@ EXECUTE_BASIC_SCRIPT_DRIVER = """ echo "Running Basic Script driver" -$SM_PYTHON_CMD /opt/ml/input/data/sm_drivers/basic_script_driver.py +$SM_PYTHON_CMD /opt/ml/input/data/sm_drivers/distributed_drivers/basic_script_driver.py """ -EXEUCTE_TORCHRUN_DRIVER = """ -echo "Running Torchrun driver" -$SM_PYTHON_CMD /opt/ml/input/data/sm_drivers/torchrun_driver.py -""" - -EXECUTE_MPI_DRIVER = """ -echo "Running MPI driver" -$SM_PYTHON_CMD /opt/ml/input/data/sm_drivers/mpi_driver.py +EXEUCTE_DISTRIBUTED_DRIVER = """ +echo "Running {driver_name} Driver" +$SM_PYTHON_CMD /opt/ml/input/data/sm_drivers/distributed_drivers/{driver_script} """ TRAIN_SCRIPT_TEMPLATE = """ diff --git a/src/sagemaker/modules/train/container_drivers/__init__.py b/src/sagemaker/modules/train/container_drivers/__init__.py index 18557a2eb5..864f3663b8 100644 --- a/src/sagemaker/modules/train/container_drivers/__init__.py +++ b/src/sagemaker/modules/train/container_drivers/__init__.py @@ -10,5 +10,5 @@ # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. -"""Sagemaker modules container_drivers directory.""" +"""Sagemaker modules container drivers directory.""" from __future__ import absolute_import diff --git a/src/sagemaker/modules/train/container_drivers/common/__init__.py b/src/sagemaker/modules/train/container_drivers/common/__init__.py new file mode 100644 index 0000000000..aab88c6b97 --- /dev/null +++ b/src/sagemaker/modules/train/container_drivers/common/__init__.py @@ -0,0 +1,14 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Sagemaker modules container drivers - common directory.""" +from __future__ import absolute_import diff --git a/src/sagemaker/modules/train/container_drivers/utils.py b/src/sagemaker/modules/train/container_drivers/common/utils.py similarity index 98% rename from src/sagemaker/modules/train/container_drivers/utils.py rename to src/sagemaker/modules/train/container_drivers/common/utils.py index e939a6e0b8..c07aa1359a 100644 --- a/src/sagemaker/modules/train/container_drivers/utils.py +++ b/src/sagemaker/modules/train/container_drivers/common/utils.py @@ -99,10 +99,10 @@ def read_hyperparameters_json(hyperparameters_json: Dict[str, Any] = HYPERPARAME return hyperparameters_dict -def get_process_count(distributed_dict: Dict[str, Any]) -> int: +def get_process_count(process_count: Optional[int] = None) -> int: """Get the number of processes to run on each node in the training job.""" return ( - int(distributed_dict.get("process_count_per_node", 0)) + process_count or int(os.environ.get("SM_NUM_GPUS", 0)) or int(os.environ.get("SM_NUM_NEURONS", 0)) or 1 diff --git a/src/sagemaker/modules/train/container_drivers/distributed_drivers/__init__.py b/src/sagemaker/modules/train/container_drivers/distributed_drivers/__init__.py new file mode 100644 index 0000000000..a44e7e81a9 --- /dev/null +++ b/src/sagemaker/modules/train/container_drivers/distributed_drivers/__init__.py @@ -0,0 +1,14 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Sagemaker modules container drivers - drivers directory.""" +from __future__ import absolute_import diff --git a/src/sagemaker/modules/train/container_drivers/basic_script_driver.py b/src/sagemaker/modules/train/container_drivers/distributed_drivers/basic_script_driver.py similarity index 88% rename from src/sagemaker/modules/train/container_drivers/basic_script_driver.py rename to src/sagemaker/modules/train/container_drivers/distributed_drivers/basic_script_driver.py index cb0278bc9f..0b086a8e4f 100644 --- a/src/sagemaker/modules/train/container_drivers/basic_script_driver.py +++ b/src/sagemaker/modules/train/container_drivers/distributed_drivers/basic_script_driver.py @@ -13,16 +13,19 @@ """This module is the entry point for the Basic Script Driver.""" from __future__ import absolute_import +import os import sys +import json import shlex +from pathlib import Path from typing import List -from utils import ( +sys.path.insert(0, str(Path(__file__).parent.parent)) + +from common.utils import ( # noqa: E402 # pylint: disable=C0413,E0611 logger, get_python_executable, - read_source_code_json, - read_hyperparameters_json, execute_commands, write_failure_file, hyperparameters_to_cli_args, @@ -31,11 +34,10 @@ def create_commands() -> List[str]: """Create the commands to execute.""" - source_code = read_source_code_json() - hyperparameters = read_hyperparameters_json() + entry_script = os.environ["SM_ENTRY_SCRIPT"] + hyperparameters = json.loads(os.environ["SM_HPS"]) python_executable = get_python_executable() - entry_script = source_code["entry_script"] args = hyperparameters_to_cli_args(hyperparameters) if entry_script.endswith(".py"): commands = [python_executable, entry_script] diff --git a/src/sagemaker/modules/train/container_drivers/mpi_driver.py b/src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_driver.py similarity index 83% rename from src/sagemaker/modules/train/container_drivers/mpi_driver.py rename to src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_driver.py index dceb748cc0..9946272617 100644 --- a/src/sagemaker/modules/train/container_drivers/mpi_driver.py +++ b/src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_driver.py @@ -16,18 +16,8 @@ import os import sys import json +from pathlib import Path -from utils import ( - logger, - read_source_code_json, - read_distributed_json, - read_hyperparameters_json, - hyperparameters_to_cli_args, - get_process_count, - execute_commands, - write_failure_file, - USER_CODE_PATH, -) from mpi_utils import ( start_sshd_daemon, bootstrap_master_node, @@ -38,6 +28,16 @@ ) +sys.path.insert(0, str(Path(__file__).parent.parent)) +from common.utils import ( # noqa: E402 # pylint: disable=C0413,E0611 + logger, + hyperparameters_to_cli_args, + get_process_count, + execute_commands, + write_failure_file, +) + + def main(): """Main function for the MPI driver script. @@ -58,9 +58,9 @@ def main(): 5. Exit """ - source_code = read_source_code_json() - distribution = read_distributed_json() - hyperparameters = read_hyperparameters_json() + entry_script = os.environ["SM_ENTRY_SCRIPT"] + distributed_config = json.loads(os.environ["SM_DISTRIBUTED_CONFIG"]) + hyperparameters = json.loads(os.environ["SM_HPS"]) sm_current_host = os.environ["SM_CURRENT_HOST"] sm_hosts = json.loads(os.environ["SM_HOSTS"]) @@ -77,7 +77,8 @@ def main(): host_list = json.loads(os.environ["SM_HOSTS"]) host_count = int(os.environ["SM_HOST_COUNT"]) - process_count = get_process_count(distribution) + process_count = int(distributed_config["process_count_per_node"] or 0) + process_count = get_process_count(process_count) if process_count > 1: host_list = ["{}:{}".format(host, process_count) for host in host_list] @@ -86,8 +87,8 @@ def main(): host_count=host_count, host_list=host_list, num_processes=process_count, - additional_options=distribution.get("mpi_additional_options", []), - entry_script_path=os.path.join(USER_CODE_PATH, source_code["entry_script"]), + additional_options=distributed_config["mpi_additional_options"] or [], + entry_script_path=entry_script, ) args = hyperparameters_to_cli_args(hyperparameters) diff --git a/src/sagemaker/modules/train/container_drivers/mpi_utils.py b/src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_utils.py similarity index 97% rename from src/sagemaker/modules/train/container_drivers/mpi_utils.py rename to src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_utils.py index 00ddc815cd..ec9e1fcef9 100644 --- a/src/sagemaker/modules/train/container_drivers/mpi_utils.py +++ b/src/sagemaker/modules/train/container_drivers/distributed_drivers/mpi_utils.py @@ -14,12 +14,23 @@ from __future__ import absolute_import import os +import sys import subprocess import time + +from pathlib import Path from typing import List import paramiko -from utils import SM_EFA_NCCL_INSTANCES, SM_EFA_RDMA_INSTANCES, get_python_executable, logger + +sys.path.insert(0, str(Path(__file__).parent.parent)) + +from common.utils import ( # noqa: E402 # pylint: disable=C0413,E0611 + SM_EFA_NCCL_INSTANCES, + SM_EFA_RDMA_INSTANCES, + get_python_executable, + logger, +) FINISHED_STATUS_FILE = "/tmp/done.algo-1" READY_FILE = "/tmp/ready.%s" diff --git a/src/sagemaker/modules/train/container_drivers/torchrun_driver.py b/src/sagemaker/modules/train/container_drivers/distributed_drivers/torchrun_driver.py similarity index 87% rename from src/sagemaker/modules/train/container_drivers/torchrun_driver.py rename to src/sagemaker/modules/train/container_drivers/distributed_drivers/torchrun_driver.py index 666479ec84..7fcfabe05d 100644 --- a/src/sagemaker/modules/train/container_drivers/torchrun_driver.py +++ b/src/sagemaker/modules/train/container_drivers/distributed_drivers/torchrun_driver.py @@ -15,20 +15,20 @@ import os import sys +import json +from pathlib import Path from typing import List, Tuple -from utils import ( +sys.path.insert(0, str(Path(__file__).parent.parent)) + +from common.utils import ( # noqa: E402 # pylint: disable=C0413,E0611 logger, - read_source_code_json, - read_distributed_json, - read_hyperparameters_json, hyperparameters_to_cli_args, get_process_count, get_python_executable, execute_commands, write_failure_file, - USER_CODE_PATH, SM_EFA_NCCL_INSTANCES, SM_EFA_RDMA_INSTANCES, ) @@ -65,11 +65,12 @@ def setup_env(): def create_commands(): """Create the Torch Distributed command to execute""" - source_code = read_source_code_json() - distribution = read_distributed_json() - hyperparameters = read_hyperparameters_json() + entry_script = os.environ["SM_ENTRY_SCRIPT"] + distributed_config = json.loads(os.environ["SM_DISTRIBUTED_CONFIG"]) + hyperparameters = json.loads(os.environ["SM_HPS"]) - process_count = get_process_count(distribution) + process_count = int(distributed_config["process_count_per_node"] or 0) + process_count = get_process_count(process_count) host_count = int(os.environ["SM_HOST_COUNT"]) torch_cmd = [] @@ -94,7 +95,7 @@ def create_commands(): ] ) - torch_cmd.extend([os.path.join(USER_CODE_PATH, source_code["entry_script"])]) + torch_cmd.extend([entry_script]) args = hyperparameters_to_cli_args(hyperparameters) torch_cmd += args diff --git a/src/sagemaker/modules/train/container_drivers/scripts/__init__.py b/src/sagemaker/modules/train/container_drivers/scripts/__init__.py index 1abbce4067..f04c5b17a0 100644 --- a/src/sagemaker/modules/train/container_drivers/scripts/__init__.py +++ b/src/sagemaker/modules/train/container_drivers/scripts/__init__.py @@ -10,5 +10,5 @@ # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. -"""Sagemaker modules scripts directory.""" +"""Sagemaker modules container drivers - scripts directory.""" from __future__ import absolute_import diff --git a/src/sagemaker/modules/train/container_drivers/scripts/environment.py b/src/sagemaker/modules/train/container_drivers/scripts/environment.py index ea6abac425..897b1f8af4 100644 --- a/src/sagemaker/modules/train/container_drivers/scripts/environment.py +++ b/src/sagemaker/modules/train/container_drivers/scripts/environment.py @@ -19,12 +19,17 @@ import json import os import sys +from pathlib import Path import logging -parent_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "..")) -sys.path.insert(0, parent_dir) +sys.path.insert(0, str(Path(__file__).parent.parent)) -from utils import safe_serialize, safe_deserialize # noqa: E402 # pylint: disable=C0413 +from common.utils import ( # noqa: E402 # pylint: disable=C0413,E0611 + safe_serialize, + safe_deserialize, + read_distributed_json, + read_source_code_json, +) # Initialize logger SM_LOG_LEVEL = os.environ.get("SM_LOG_LEVEL", 20) @@ -42,6 +47,8 @@ SM_OUTPUT_DIR = "/opt/ml/output" SM_OUTPUT_FAILURE = "/opt/ml/output/failure" SM_OUTPUT_DATA_DIR = "/opt/ml/output/data" +SM_SOURCE_DIR_PATH = "/opt/ml/input/data/code" +SM_DISTRIBUTED_DRIVER_DIR_PATH = "/opt/ml/input/data/sm_drivers/distributed_drivers" SM_MASTER_ADDR = "algo-1" SM_MASTER_PORT = 7777 @@ -158,6 +165,17 @@ def set_env( "SM_MASTER_PORT": SM_MASTER_PORT, } + # SourceCode and DistributedConfig Environment Variables + source_code = read_source_code_json() + if source_code: + env_vars["SM_SOURCE_DIR"] = SM_SOURCE_DIR_PATH + env_vars["SM_ENTRY_SCRIPT"] = source_code.get("entry_script", "") + + distributed = read_distributed_json() + if distributed: + env_vars["SM_DISTRIBUTED_DRIVER_DIR"] = SM_DISTRIBUTED_DRIVER_DIR_PATH + env_vars["SM_DISTRIBUTED_CONFIG"] = distributed + # Data Channels channels = list(input_data_config.keys()) for channel in channels: diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index bb7c4168e6..aef6e3312b 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -70,7 +70,7 @@ ) from sagemaker.modules.local_core.local_container import _LocalContainer -from sagemaker.modules.distributed import Torchrun, MPI, DistributedConfig +from sagemaker.modules.distributed import Torchrun, DistributedConfig from sagemaker.modules.utils import ( _get_repo_name_from_image, _get_unique_name, @@ -94,8 +94,7 @@ from sagemaker.modules.templates import ( TRAIN_SCRIPT_TEMPLATE, EXECUTE_BASE_COMMANDS, - EXECUTE_MPI_DRIVER, - EXEUCTE_TORCHRUN_DRIVER, + EXEUCTE_DISTRIBUTED_DRIVER, EXECUTE_BASIC_SCRIPT_DRIVER, ) from sagemaker.telemetry.telemetry_logging import _telemetry_emitter @@ -153,7 +152,7 @@ class ModelTrainer(BaseModel): source_code (Optional[SourceCode]): The source code configuration. This is used to configure the source code for running the training job. - distributed (Optional[Union[MPI, Torchrun]]): + distributed (Optional[DistributedConfig]): The distributed runner for the training job. This is used to configure a distributed training job. If specifed, ``source_code`` must also be provided. @@ -215,7 +214,7 @@ class ModelTrainer(BaseModel): role: Optional[str] = None base_job_name: Optional[str] = None source_code: Optional[SourceCode] = None - distributed: Optional[Union[MPI, Torchrun]] = None + distributed: Optional[DistributedConfig] = None compute: Optional[Compute] = None networking: Optional[Networking] = None stopping_condition: Optional[StoppingCondition] = None @@ -561,12 +560,17 @@ def train( container_arguments = None if self.source_code: if self.training_mode == Mode.LOCAL_CONTAINER: - drivers_dir = TemporaryDirectory( - prefix=os.path.join(self.local_container_root + "/") - ) + tmp_dir = TemporaryDirectory(prefix=os.path.join(self.local_container_root + "/")) else: - drivers_dir = TemporaryDirectory() - shutil.copytree(SM_DRIVERS_LOCAL_PATH, drivers_dir.name, dirs_exist_ok=True) + tmp_dir = TemporaryDirectory() + # Copy everything under container_drivers/ to a temporary directory + shutil.copytree(SM_DRIVERS_LOCAL_PATH, tmp_dir.name, dirs_exist_ok=True) + + # If distributed is provided, overwrite code under /drivers + if self.distributed: + distributed_driver_dir = self.distributed.driver_dir + driver_dir = os.path.join(tmp_dir.name, "distributed_drivers") + shutil.copytree(distributed_driver_dir, driver_dir, dirs_exist_ok=True) # If source code is provided, create a channel for the source code # The source code will be mounted at /opt/ml/input/data/code in the container @@ -579,7 +583,7 @@ def train( input_data_config.append(source_code_channel) self._prepare_train_script( - tmp_dir=drivers_dir, + tmp_dir=tmp_dir, source_code=self.source_code, distributed=self.distributed, ) @@ -588,13 +592,13 @@ def train( mp_parameters = self.distributed.smp._to_mp_hyperparameters() string_hyper_parameters.update(mp_parameters) - self._write_source_code_json(tmp_dir=drivers_dir, source_code=self.source_code) - self._write_distributed_json(tmp_dir=drivers_dir, distributed=self.distributed) + self._write_source_code_json(tmp_dir=tmp_dir, source_code=self.source_code) + self._write_distributed_json(tmp_dir=tmp_dir, distributed=self.distributed) # Create an input channel for drivers packaged by the sdk sm_drivers_channel = self.create_input_data_channel( channel_name=SM_DRIVERS, - data_source=drivers_dir.name, + data_source=tmp_dir.name, key_prefix=input_data_key_prefix, ) input_data_config.append(sm_drivers_channel) @@ -796,7 +800,7 @@ def _write_source_code_json(self, tmp_dir: TemporaryDirectory, source_code: Sour """Write the source code configuration to a JSON file.""" file_path = os.path.join(tmp_dir.name, SOURCE_CODE_JSON) with open(file_path, "w") as f: - dump = source_code.model_dump(exclude_none=True) if source_code else {} + dump = source_code.model_dump() if source_code else {} f.write(json.dumps(dump)) def _write_distributed_json( @@ -807,7 +811,7 @@ def _write_distributed_json( """Write the distributed runner configuration to a JSON file.""" file_path = os.path.join(tmp_dir.name, DISTRIBUTED_JSON) with open(file_path, "w") as f: - dump = distributed.model_dump(exclude_none=True) if distributed else {} + dump = distributed.model_dump() if distributed else {} f.write(json.dumps(dump)) def _prepare_train_script( @@ -844,13 +848,10 @@ def _prepare_train_script( if base_command: execute_driver = EXECUTE_BASE_COMMANDS.format(base_command=base_command) elif distributed: - distribution_type = distributed._type - if distribution_type == "mpi": - execute_driver = EXECUTE_MPI_DRIVER - elif distribution_type == "torchrun": - execute_driver = EXEUCTE_TORCHRUN_DRIVER - else: - raise ValueError(f"Unsupported distribution type: {distribution_type}.") + execute_driver = EXEUCTE_DISTRIBUTED_DRIVER.format( + driver_name=distributed.__class__.__name__, + driver_script=distributed.driver_script, + ) elif source_code.entry_script and not source_code.command and not distributed: if not source_code.entry_script.endswith((".py", ".sh")): raise ValueError( diff --git a/tests/data/modules/custom_drivers/driver.py b/tests/data/modules/custom_drivers/driver.py new file mode 100644 index 0000000000..3395b80da9 --- /dev/null +++ b/tests/data/modules/custom_drivers/driver.py @@ -0,0 +1,34 @@ +import json +import os +import subprocess +import sys + + +def main(): + driver_config = json.loads(os.environ["SM_DISTRIBUTED_CONFIG"]) + process_count_per_node = driver_config["process_count_per_node"] + assert process_count_per_node != None + + hps = json.loads(os.environ["SM_HPS"]) + assert hps != None + assert isinstance(hps, dict) + + source_dir = os.environ["SM_SOURCE_DIR"] + assert source_dir == "/opt/ml/input/data/code" + sm_drivers_dir = os.environ["SM_DISTRIBUTED_DRIVER_DIR"] + assert sm_drivers_dir == "/opt/ml/input/data/sm_drivers/distributed_drivers" + + entry_script = os.environ["SM_ENTRY_SCRIPT"] + assert entry_script != None + + python = sys.executable + + command = [python, entry_script] + print(f"Running command: {command}") + subprocess.run(command, check=True) + + +if __name__ == "__main__": + print("Running custom driver script") + main() + print("Finished running custom driver script") diff --git a/tests/data/modules/scripts/entry_script.py b/tests/data/modules/scripts/entry_script.py new file mode 100644 index 0000000000..3c972bd956 --- /dev/null +++ b/tests/data/modules/scripts/entry_script.py @@ -0,0 +1,19 @@ +import json +import os +import time + + +def main(): + hps = json.loads(os.environ["SM_HPS"]) + assert hps != None + print(f"Hyperparameters: {hps}") + + print("Running pseudo training script") + for epochs in range(hps["epochs"]): + print(f"Epoch: {epochs}") + time.sleep(1) + print("Finished running pseudo training script") + + +if __name__ == "__main__": + main() diff --git a/tests/integ/sagemaker/modules/train/test_model_trainer.py b/tests/integ/sagemaker/modules/train/test_model_trainer.py index a19f6d0e8b..a1e3106553 100644 --- a/tests/integ/sagemaker/modules/train/test_model_trainer.py +++ b/tests/integ/sagemaker/modules/train/test_model_trainer.py @@ -17,7 +17,7 @@ from sagemaker.modules.train import ModelTrainer from sagemaker.modules.configs import SourceCode, Compute -from sagemaker.modules.distributed import MPI, Torchrun +from sagemaker.modules.distributed import MPI, Torchrun, DistributedConfig EXPECTED_HYPERPARAMETERS = { "integer": 1, @@ -126,3 +126,35 @@ def test_hp_contract_hyperparameter_yaml(modules_sagemaker_session): ) assert model_trainer.hyperparameters == EXPECTED_HYPERPARAMETERS model_trainer.train() + + +def test_custom_distributed_driver(modules_sagemaker_session): + class CustomDriver(DistributedConfig): + process_count_per_node: int = None + + @property + def driver_dir(self) -> str: + return f"{DATA_DIR}/modules/custom_drivers" + + @property + def driver_script(self) -> str: + return "driver.py" + + source_code = SourceCode( + source_dir=f"{DATA_DIR}/modules/scripts", + entry_script="entry_script.py", + ) + + hyperparameters = {"epochs": 10} + + custom_driver = CustomDriver(process_count_per_node=2) + + model_trainer = ModelTrainer( + sagemaker_session=modules_sagemaker_session, + training_image=DEFAULT_CPU_IMAGE, + hyperparameters=hyperparameters, + source_code=source_code, + distributed=custom_driver, + base_job_name="custom-distributed-driver", + ) + model_trainer.train() diff --git a/tests/unit/sagemaker/modules/train/container_drivers/scripts/test_enviornment.py b/tests/unit/sagemaker/modules/train/container_drivers/scripts/test_enviornment.py index 30d6dfdf6c..fe4fa08825 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/scripts/test_enviornment.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/scripts/test_enviornment.py @@ -21,12 +21,10 @@ from sagemaker.modules.train.container_drivers.scripts.environment import ( set_env, - log_key_value, log_env_variables, - mask_sensitive_info, HIDDEN_VALUE, ) -from sagemaker.modules.train.container_drivers.utils import safe_serialize, safe_deserialize +from sagemaker.modules.train.container_drivers.common.utils import safe_serialize, safe_deserialize RESOURCE_CONFIG = dict( current_host="algo-1", @@ -75,6 +73,15 @@ }, } +SOURCE_CODE = { + "source_dir": "code", + "entry_script": "train.py", +} + +DISTRIBUTED_CONFIG = { + "process_count_per_node": 2, +} + OUTPUT_FILE = os.path.join(os.path.dirname(__file__), "sm_training.env") # flake8: noqa @@ -89,6 +96,10 @@ export SM_LOG_LEVEL='20' export SM_MASTER_ADDR='algo-1' export SM_MASTER_PORT='7777' +export SM_SOURCE_DIR='/opt/ml/input/data/code' +export SM_ENTRY_SCRIPT='train.py' +export SM_DISTRIBUTED_DRIVER_DIR='/opt/ml/input/data/sm_drivers/distributed_drivers' +export SM_DISTRIBUTED_CONFIG='{"process_count_per_node": 2}' export SM_CHANNEL_TRAIN='/opt/ml/input/data/train' export SM_CHANNEL_VALIDATION='/opt/ml/input/data/validation' export SM_CHANNELS='["train", "validation"]' @@ -112,6 +123,14 @@ """ +@patch( + "sagemaker.modules.train.container_drivers.scripts.environment.read_source_code_json", + return_value=SOURCE_CODE, +) +@patch( + "sagemaker.modules.train.container_drivers.scripts.environment.read_distributed_json", + return_value=DISTRIBUTED_CONFIG, +) @patch("sagemaker.modules.train.container_drivers.scripts.environment.num_cpus", return_value=8) @patch("sagemaker.modules.train.container_drivers.scripts.environment.num_gpus", return_value=0) @patch("sagemaker.modules.train.container_drivers.scripts.environment.num_neurons", return_value=0) @@ -124,7 +143,13 @@ side_effect=safe_deserialize, ) def test_set_env( - mock_safe_deserialize, mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons + mock_safe_deserialize, + mock_safe_serialize, + mock_num_neurons, + mock_num_gpus, + mock_num_cpus, + mock_read_distributed_json, + mock_read_source_code_json, ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): set_env( @@ -137,6 +162,8 @@ def test_set_env( mock_num_cpus.assert_called_once() mock_num_gpus.assert_called_once() mock_num_neurons.assert_called_once() + mock_read_distributed_json.assert_called_once() + mock_read_source_code_json.assert_called_once() with open(OUTPUT_FILE, "r") as f: env_file = f.read().strip() diff --git a/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_driver.py b/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_driver.py index a1a84da1ab..bf51db8285 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_driver.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_driver.py @@ -15,13 +15,14 @@ import os import sys +import json from unittest.mock import patch, MagicMock sys.modules["utils"] = MagicMock() sys.modules["mpi_utils"] = MagicMock() -from sagemaker.modules.train.container_drivers import mpi_driver # noqa: E402 +from sagemaker.modules.train.container_drivers.distributed_drivers import mpi_driver # noqa: E402 DUMMY_MPI_COMMAND = [ @@ -40,12 +41,7 @@ "script.py", ] -DUMMY_SOURCE_CODE = { - "source_code": "source_code", - "entry_script": "script.py", -} DUMMY_DISTRIBUTED = { - "_type": "mpi", "process_count_per_node": 2, "mpi_additional_options": [ "--verbose", @@ -62,17 +58,28 @@ "SM_HOSTS": '["algo-1", "algo-2"]', "SM_MASTER_ADDR": "algo-1", "SM_HOST_COUNT": "2", + "SM_HPS": json.dumps({}), + "SM_DISTRIBUTED_CONFIG": json.dumps(DUMMY_DISTRIBUTED), + "SM_ENTRY_SCRIPT": "/opt/ml/input/data/code/script.py", }, ) -@patch("sagemaker.modules.train.container_drivers.mpi_driver.read_distributed_json") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.read_source_code_json") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.write_env_vars_to_file") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.start_sshd_daemon") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.bootstrap_master_node") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.bootstrap_worker_node") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.hyperparameters_to_cli_args") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.get_mpirun_command") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.execute_commands") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.write_env_vars_to_file" +) +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.start_sshd_daemon") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.bootstrap_master_node" +) +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.bootstrap_worker_node" +) +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.hyperparameters_to_cli_args" +) +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.get_mpirun_command" +) +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.execute_commands") def test_mpi_driver_worker( mock_execute_commands, mock_get_mpirun_command, @@ -81,12 +88,8 @@ def test_mpi_driver_worker( mock_bootstrap_master_node, mock_start_sshd_daemon, mock_write_env_vars_to_file, - mock_read_source_code_json, - mock_read_distributed_json, ): mock_hyperparameters_to_cli_args.return_value = [] - mock_read_source_code_json.return_value = DUMMY_SOURCE_CODE - mock_read_distributed_json.return_value = DUMMY_DISTRIBUTED mpi_driver.main() @@ -106,19 +109,32 @@ def test_mpi_driver_worker( "SM_HOSTS": '["algo-1", "algo-2"]', "SM_MASTER_ADDR": "algo-1", "SM_HOST_COUNT": "2", + "SM_HPS": json.dumps({}), + "SM_DISTRIBUTED_CONFIG": json.dumps(DUMMY_DISTRIBUTED), + "SM_ENTRY_SCRIPT": "script.py", }, ) -@patch("sagemaker.modules.train.container_drivers.mpi_driver.read_distributed_json") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.read_source_code_json") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.write_env_vars_to_file") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.start_sshd_daemon") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.bootstrap_master_node") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.bootstrap_worker_node") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.get_process_count") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.hyperparameters_to_cli_args") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.get_mpirun_command") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.execute_commands") -@patch("sagemaker.modules.train.container_drivers.mpi_driver.write_status_file_to_workers") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.write_env_vars_to_file" +) +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.start_sshd_daemon") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.bootstrap_master_node" +) +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.bootstrap_worker_node" +) +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.get_process_count") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.hyperparameters_to_cli_args" +) +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.get_mpirun_command" +) +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.execute_commands") +@patch( + "sagemaker.modules.train.container_drivers.distributed_drivers.mpi_driver.write_status_file_to_workers" +) def test_mpi_driver_master( mock_write_status_file_to_workers, mock_execute_commands, @@ -129,12 +145,8 @@ def test_mpi_driver_master( mock_bootstrap_master_node, mock_start_sshd_daemon, mock_write_env_vars_to_file, - mock_read_source_code_config_json, - mock_read_distributed_json, ): mock_hyperparameters_to_cli_args.return_value = [] - mock_read_source_code_config_json.return_value = DUMMY_SOURCE_CODE - mock_read_distributed_json.return_value = DUMMY_DISTRIBUTED mock_get_mpirun_command.return_value = DUMMY_MPI_COMMAND mock_get_process_count.return_value = 2 mock_execute_commands.return_value = (0, "") diff --git a/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_utils.py b/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_utils.py index 2328b1ace5..35208d708a 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_utils.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/test_mpi_utils.py @@ -27,7 +27,7 @@ mock_utils.get_python_executable = Mock(return_value="/usr/bin/python") with patch.dict("sys.modules", {"utils": mock_utils}): - from sagemaker.modules.train.container_drivers.mpi_utils import ( + from sagemaker.modules.train.container_drivers.distributed_drivers.mpi_utils import ( CustomHostKeyPolicy, _can_connect, write_status_file_to_workers, @@ -65,7 +65,7 @@ def test_custom_host_key_policy_invalid_hostname(): @patch("paramiko.SSHClient") -@patch("sagemaker.modules.train.container_drivers.mpi_utils.logger") +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_utils.logger") def test_can_connect_success(mock_logger, mock_ssh_client): """Test successful SSH connection.""" mock_client = Mock() @@ -81,7 +81,7 @@ def test_can_connect_success(mock_logger, mock_ssh_client): @patch("paramiko.SSHClient") -@patch("sagemaker.modules.train.container_drivers.mpi_utils.logger") +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_utils.logger") def test_can_connect_failure(mock_logger, mock_ssh_client): """Test SSH connection failure.""" mock_client = Mock() @@ -97,7 +97,7 @@ def test_can_connect_failure(mock_logger, mock_ssh_client): @patch("subprocess.run") -@patch("sagemaker.modules.train.container_drivers.mpi_utils.logger") +@patch("sagemaker.modules.train.container_drivers.distributed_drivers.mpi_utils.logger") def test_write_status_file_to_workers_failure(mock_logger, mock_run): """Test failed status file writing to workers with retry timeout.""" mock_run.side_effect = subprocess.CalledProcessError(1, "ssh") diff --git a/tests/unit/sagemaker/modules/train/container_drivers/test_torchrun_driver.py b/tests/unit/sagemaker/modules/train/container_drivers/test_torchrun_driver.py index 4cff07a0c0..2568346158 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/test_torchrun_driver.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/test_torchrun_driver.py @@ -15,38 +15,38 @@ import os import sys +import json from unittest.mock import patch, MagicMock sys.modules["utils"] = MagicMock() -from sagemaker.modules.train.container_drivers import torchrun_driver # noqa: E402 - -DUMMY_SOURCE_CODE = { - "source_code": "source_code", - "entry_script": "script.py", -} +from sagemaker.modules.train.container_drivers.distributed_drivers import ( # noqa: E402 + torchrun_driver, +) -DUMMY_distributed = {"_type": "torchrun", "process_count_per_node": 2} +DUMMY_DISTRIBUTED = {"process_count_per_node": 2} @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_python_executable", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_python_executable", return_value="python3", ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.pytorch_version", return_value=(2, 0) + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.pytorch_version", + return_value=(2, 0), ) def test_get_base_pytorch_command_torchrun(mock_pytorch_version, mock_get_python_executable): assert torchrun_driver.get_base_pytorch_command() == ["torchrun"] @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_python_executable", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_python_executable", return_value="python3", ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.pytorch_version", return_value=(1, 8) + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.pytorch_version", + return_value=(1, 8), ) def test_get_base_pytorch_command_torch_distributed_launch( mock_pytorch_version, mock_get_python_executable @@ -62,38 +62,29 @@ def test_get_base_pytorch_command_torch_distributed_launch( "SM_CURRENT_INSTANCE_TYPE": "ml.p4d.24xlarge", "SM_NETWORK_INTERFACE_NAME": "eth0", "SM_HOST_COUNT": "1", + "SM_HPS": json.dumps({}), + "SM_DISTRIBUTED_CONFIG": json.dumps(DUMMY_DISTRIBUTED), + "SM_ENTRY_SCRIPT": "script.py", }, ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.USER_CODE_PATH", - "/opt/ml/input/data/code", -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_process_count", return_value=2 + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_process_count", + return_value=2, ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.pytorch_version", return_value=(2, 0) + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.pytorch_version", + return_value=(2, 0), ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_base_pytorch_command", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_base_pytorch_command", return_value=["torchrun"], ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.read_source_code_json", - return_value=DUMMY_SOURCE_CODE, -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.read_distributed_json", - return_value=DUMMY_distributed, -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.hyperparameters_to_cli_args", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.hyperparameters_to_cli_args", return_value=[], ) def test_create_commands_single_node( mock_hyperparameters_to_cli_args, - mock_read_distributed_json, - mock_read_source_code_json, mock_get_base_pytorch_command, mock_pytorch_version, mock_get_process_count, @@ -102,7 +93,7 @@ def test_create_commands_single_node( "torchrun", "--nnodes=1", "--nproc_per_node=2", - "/opt/ml/input/data/code/script.py", + "script.py", ] command = torchrun_driver.create_commands() @@ -118,38 +109,29 @@ def test_create_commands_single_node( "SM_MASTER_ADDR": "algo-1", "SM_MASTER_PORT": "7777", "SM_CURRENT_HOST_RANK": "0", + "SM_HPS": json.dumps({}), + "SM_DISTRIBUTED_CONFIG": json.dumps(DUMMY_DISTRIBUTED), + "SM_ENTRY_SCRIPT": "script.py", }, ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.USER_CODE_PATH", - "/opt/ml/input/data/code", -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_process_count", return_value=2 + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_process_count", + return_value=2, ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.pytorch_version", return_value=(2, 0) + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.pytorch_version", + return_value=(2, 0), ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.get_base_pytorch_command", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.get_base_pytorch_command", return_value=["torchrun"], ) @patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.read_source_code_json", - return_value=DUMMY_SOURCE_CODE, -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.read_distributed_json", - return_value=DUMMY_distributed, -) -@patch( - "sagemaker.modules.train.container_drivers.torchrun_driver.hyperparameters_to_cli_args", + "sagemaker.modules.train.container_drivers.distributed_drivers.torchrun_driver.hyperparameters_to_cli_args", return_value=[], ) def test_create_commands_multi_node( mock_hyperparameters_to_cli_args, - mock_read_distributed_json, - mock_read_source_code_json, mock_get_base_pytorch_command, mock_pytorch_version, mock_get_process_count, @@ -161,7 +143,7 @@ def test_create_commands_multi_node( "--master_addr=algo-1", "--master_port=7777", "--node_rank=0", - "/opt/ml/input/data/code/script.py", + "script.py", ] command = torchrun_driver.create_commands() diff --git a/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py b/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py index aba97996b0..beff06e8d8 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py @@ -12,11 +12,13 @@ # language governing permissions and limitations under the License. """Container Utils Unit Tests.""" from __future__ import absolute_import +import os -from sagemaker.modules.train.container_drivers.utils import ( +from sagemaker.modules.train.container_drivers.common.utils import ( safe_deserialize, safe_serialize, hyperparameters_to_cli_args, + get_process_count, ) SM_HPS = { @@ -119,3 +121,18 @@ def test_safe_serialize_empty_data(): assert safe_serialize("") == "" assert safe_serialize([]) == "[]" assert safe_serialize({}) == "{}" + + +def test_get_process_count(): + assert get_process_count() == 1 + assert get_process_count(2) == 2 + os.environ["SM_NUM_GPUS"] = "4" + assert get_process_count() == 4 + os.environ["SM_NUM_GPUS"] = "0" + os.environ["SM_NUM_NEURONS"] = "8" + assert get_process_count() == 8 + os.environ["SM_NUM_NEURONS"] = "0" + assert get_process_count() == 1 + del os.environ["SM_NUM_GPUS"] + del os.environ["SM_NUM_NEURONS"] + assert get_process_count() == 1 diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 194bb44988..770420c354 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -67,7 +67,7 @@ ) from sagemaker.modules.distributed import Torchrun, SMP, MPI from sagemaker.modules.train.sm_recipes.utils import _load_recipes_cfg -from sagemaker.modules.templates import EXEUCTE_TORCHRUN_DRIVER, EXECUTE_MPI_DRIVER +from sagemaker.modules.templates import EXEUCTE_DISTRIBUTED_DRIVER from tests.unit import DATA_DIR DEFAULT_BASE_NAME = "dummy-image-job" @@ -412,7 +412,9 @@ def test_create_input_data_channel(mock_default_bucket, mock_upload_data, model_ { "source_code": DEFAULT_SOURCE_CODE, "distributed": Torchrun(), - "expected_template": EXEUCTE_TORCHRUN_DRIVER, + "expected_template": EXEUCTE_DISTRIBUTED_DRIVER.format( + driver_name="Torchrun", driver_script="torchrun_driver.py" + ), "expected_hyperparameters": {}, }, { @@ -425,7 +427,9 @@ def test_create_input_data_channel(mock_default_bucket, mock_upload_data, model_ tensor_parallel_degree=5, ) ), - "expected_template": EXEUCTE_TORCHRUN_DRIVER, + "expected_template": EXEUCTE_DISTRIBUTED_DRIVER.format( + driver_name="Torchrun", driver_script="torchrun_driver.py" + ), "expected_hyperparameters": { "mp_parameters": json.dumps( { @@ -442,7 +446,9 @@ def test_create_input_data_channel(mock_default_bucket, mock_upload_data, model_ "distributed": MPI( mpi_additional_options=["-x", "VAR1", "-x", "VAR2"], ), - "expected_template": EXECUTE_MPI_DRIVER, + "expected_template": EXEUCTE_DISTRIBUTED_DRIVER.format( + driver_name="MPI", driver_script="mpi_driver.py" + ), "expected_hyperparameters": {}, }, ], @@ -499,21 +505,15 @@ def test_train_with_distributed_config( assert os.path.exists(expected_runner_json_path) with open(expected_runner_json_path, "r") as f: runner_json_content = f.read() - assert test_case["distributed"].model_dump(exclude_none=True) == ( - json.loads(runner_json_content) - ) + assert test_case["distributed"].model_dump() == (json.loads(runner_json_content)) assert os.path.exists(expected_source_code_json_path) with open(expected_source_code_json_path, "r") as f: source_code_json_content = f.read() - assert test_case["source_code"].model_dump(exclude_none=True) == ( - json.loads(source_code_json_content) - ) + assert test_case["source_code"].model_dump() == (json.loads(source_code_json_content)) assert os.path.exists(expected_source_code_json_path) with open(expected_source_code_json_path, "r") as f: source_code_json_content = f.read() - assert test_case["source_code"].model_dump(exclude_none=True) == ( - json.loads(source_code_json_content) - ) + assert test_case["source_code"].model_dump() == (json.loads(source_code_json_content)) finally: shutil.rmtree(tmp_dir.name) assert not os.path.exists(tmp_dir.name) From cb58c44cfee3bb697727e0e0175477f5160676d3 Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Wed, 5 Mar 2025 19:40:05 -0800 Subject: [PATCH 006/164] Skip tests with deprecated instance type (#5077) Co-authored-by: pintaoz --- tests/integ/test_horovod.py | 7 ++----- tests/integ/test_horovod_mx.py | 3 +++ 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/tests/integ/test_horovod.py b/tests/integ/test_horovod.py index 2ddcdc92e0..78314c2ade 100644 --- a/tests/integ/test_horovod.py +++ b/tests/integ/test_horovod.py @@ -62,11 +62,8 @@ def test_hvd_gpu( tmpdir, **kwargs, ): - if ( - Version(tensorflow_training_latest_version) >= Version("2.12") - and kwargs["instance_type"] == "ml.p2.xlarge" - ): - pytest.skip("P2 instances have been deprecated for sagemaker jobs starting TensorFlow 2.12") + if kwargs["instance_type"] == "ml.p2.xlarge": + pytest.skip("Instance type ml.p2.xlarge has been deprecated") if Version(tensorflow_training_latest_version) >= Version("2.13"): pytest.skip("Horovod is deprecated in TensorFlow 2.13 and above") diff --git a/tests/integ/test_horovod_mx.py b/tests/integ/test_horovod_mx.py index 7bd6a641e0..a238966dd3 100644 --- a/tests/integ/test_horovod_mx.py +++ b/tests/integ/test_horovod_mx.py @@ -58,6 +58,9 @@ def test_hvd_gpu( tmpdir, **kwargs, ): + if kwargs["instance_type"] == "ml.p2.xlarge": + pytest.skip("Instance type ml.p2.xlarge has been deprecated") + _create_and_fit_estimator( mxnet_training_latest_version, mxnet_training_latest_py_version, From f98b23115eedaf04cb49c8ddf32cc4f6563ae442 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 6 Mar 2025 06:13:58 +0000 Subject: [PATCH 007/164] prepare release v2.241.0 --- CHANGELOG.md | 17 +++++++++++++++++ VERSION | 2 +- 2 files changed, 18 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 742e46d127..3e765f5260 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,22 @@ # Changelog +## v2.241.0 (2025-03-06) + +### Features + + * Make DistributedConfig Extensible + * support training for JumpStart model references as part of Curated Hub Phase 2 + * Allow ModelTrainer to accept hyperparameters file + +### Bug Fixes and Other Changes + + * Skip tests with deprecated instance type + * Ensure Model.is_repack() returns a boolean + * Fix error when there is no session to call _create_model_request() + * Use sagemaker session's s3_resource in download_folder + * Added check for the presence of model package group before creating one + * Fix key error in _send_metrics() + ## v2.240.0 (2025-02-25) ### Features diff --git a/VERSION b/VERSION index 1b1f3a78e8..669f97a182 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.240.1.dev0 +2.241.0 From 7aa9eadd70cec93aa67173a99c99416d6bab07ce Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 6 Mar 2025 06:14:03 +0000 Subject: [PATCH 008/164] update development version to v2.241.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 669f97a182..c5d92b1891 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.241.0 +2.241.1.dev0 From 6945a04da2f0fdd34e6c47400b3cbfa70a6edad0 Mon Sep 17 00:00:00 2001 From: Rohan Gujarathi Date: Wed, 5 Mar 2025 22:24:48 -0800 Subject: [PATCH 009/164] pipeline definition function doc update (#5074) Co-authored-by: Rohan Gujarathi --- src/sagemaker/workflow/pipeline.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/workflow/pipeline.py b/src/sagemaker/workflow/pipeline.py index 62167b96e7..9749014531 100644 --- a/src/sagemaker/workflow/pipeline.py +++ b/src/sagemaker/workflow/pipeline.py @@ -383,7 +383,11 @@ def start( ) def definition(self) -> str: - """Converts a request structure to string representation for workflow service calls.""" + """Converts a request structure to string representation for workflow service calls. + + Returns: + A JSON formatted string of pipeline definition. + """ compiled_steps = StepsCompiler( pipeline_name=self.name, sagemaker_session=self.sagemaker_session, From 2b10b2f5de2060fc3cf742b4173d091b6892f4ae Mon Sep 17 00:00:00 2001 From: Rohan Narayan Date: Mon, 10 Mar 2025 17:28:40 -0400 Subject: [PATCH 010/164] feat: add integ tests for training JumpStart models in private hub (#5076) * feat: add integ tests for training JumpStart models in private hub * fixed formatting * remove unused imports * fix unused imports * fix unit test failure and fix bug around versioning * fix formatting * fix unit tests * fix model_uri usage issue * fix some formatting * separate private hub setup code * add try catch block * fix flake8 issue so except clause is not bare * black formatting --- src/sagemaker/jumpstart/factory/estimator.py | 33 ++- src/sagemaker/jumpstart/hub/interfaces.py | 4 +- src/sagemaker/jumpstart/hub/parsers.py | 6 + src/sagemaker/jumpstart/hub/utils.py | 33 ++- src/sagemaker/jumpstart/types.py | 8 + tests/integ/sagemaker/jumpstart/constants.py | 2 +- .../private_hub/estimator/__init__.py | 0 .../test_jumpstart_private_hub_estimator.py | 204 ++++++++++++++++++ .../model/test_jumpstart_private_hub_model.py | 5 +- tests/unit/sagemaker/jumpstart/constants.py | 2 + tests/unit/sagemaker/jumpstart/test_types.py | 1 + 11 files changed, 285 insertions(+), 13 deletions(-) create mode 100644 tests/integ/sagemaker/jumpstart/private_hub/estimator/__init__.py create mode 100644 tests/integ/sagemaker/jumpstart/private_hub/estimator/test_jumpstart_private_hub_estimator.py diff --git a/src/sagemaker/jumpstart/factory/estimator.py b/src/sagemaker/jumpstart/factory/estimator.py index 17ad7a76f5..12eb30daaf 100644 --- a/src/sagemaker/jumpstart/factory/estimator.py +++ b/src/sagemaker/jumpstart/factory/estimator.py @@ -56,6 +56,7 @@ JUMPSTART_LOGGER, TRAINING_ENTRY_POINT_SCRIPT_NAME, SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY, + JUMPSTART_MODEL_HUB_NAME, ) from sagemaker.jumpstart.enums import JumpStartScriptScope, JumpStartModelType from sagemaker.jumpstart.factory import model @@ -313,16 +314,31 @@ def _add_hub_access_config_to_kwargs_inputs( ): """Adds HubAccessConfig to kwargs inputs""" + dataset_uri = kwargs.specs.default_training_dataset_uri if isinstance(kwargs.inputs, str): - kwargs.inputs = TrainingInput(s3_data=kwargs.inputs, hub_access_config=hub_access_config) + if dataset_uri is not None and dataset_uri == kwargs.inputs: + kwargs.inputs = TrainingInput( + s3_data=kwargs.inputs, hub_access_config=hub_access_config + ) elif isinstance(kwargs.inputs, TrainingInput): - kwargs.inputs.add_hub_access_config(hub_access_config=hub_access_config) + if ( + dataset_uri is not None + and dataset_uri == kwargs.inputs.config["DataSource"]["S3DataSource"]["S3Uri"] + ): + kwargs.inputs.add_hub_access_config(hub_access_config=hub_access_config) elif isinstance(kwargs.inputs, dict): for k, v in kwargs.inputs.items(): if isinstance(v, str): - kwargs.inputs[k] = TrainingInput(s3_data=v, hub_access_config=hub_access_config) + training_input = TrainingInput(s3_data=v) + if dataset_uri is not None and dataset_uri == v: + training_input.add_hub_access_config(hub_access_config=hub_access_config) + kwargs.inputs[k] = training_input elif isinstance(kwargs.inputs, TrainingInput): - kwargs.inputs[k].add_hub_access_config(hub_access_config=hub_access_config) + if ( + dataset_uri is not None + and dataset_uri == kwargs.inputs.config["DataSource"]["S3DataSource"]["S3Uri"] + ): + kwargs.inputs[k].add_hub_access_config(hub_access_config=hub_access_config) return kwargs @@ -616,8 +632,13 @@ def _add_model_reference_arn_to_kwargs( def _add_model_uri_to_kwargs(kwargs: JumpStartEstimatorInitKwargs) -> JumpStartEstimatorInitKwargs: """Sets model uri in kwargs based on default or override, returns full kwargs.""" - - if _model_supports_training_model_uri(**get_model_info_default_kwargs(kwargs)): + # hub_arn is by default None unless the user specifies the hub_name + # If no hub_name is specified, it is assumed the public hub + is_private_hub = JUMPSTART_MODEL_HUB_NAME not in kwargs.hub_arn if kwargs.hub_arn else False + if ( + _model_supports_training_model_uri(**get_model_info_default_kwargs(kwargs)) + or is_private_hub + ): default_model_uri = model_uris.retrieve( model_scope=JumpStartScriptScope.TRAINING, instance_type=kwargs.instance_type, diff --git a/src/sagemaker/jumpstart/hub/interfaces.py b/src/sagemaker/jumpstart/hub/interfaces.py index fd38868dcc..6ba5a37c3c 100644 --- a/src/sagemaker/jumpstart/hub/interfaces.py +++ b/src/sagemaker/jumpstart/hub/interfaces.py @@ -630,7 +630,6 @@ def from_json(self, json_obj: Dict[str, Any]) -> None: if json_obj.get("ValidationSupported") else None ) - self.default_training_dataset_uri: Optional[str] = json_obj.get("DefaultTrainingDatasetUri") self.resource_name_base: Optional[str] = json_obj.get("ResourceNameBase") self.gated_bucket: bool = bool(json_obj.get("GatedBucket", False)) self.default_payloads: Optional[Dict[str, JumpStartSerializablePayload]] = ( @@ -671,6 +670,9 @@ def from_json(self, json_obj: Dict[str, Any]) -> None: ) if self.training_supported: + self.default_training_dataset_uri: Optional[str] = json_obj.get( + "DefaultTrainingDatasetUri" + ) self.training_model_package_artifact_uri: Optional[str] = json_obj.get( "TrainingModelPackageArtifactUri" ) diff --git a/src/sagemaker/jumpstart/hub/parsers.py b/src/sagemaker/jumpstart/hub/parsers.py index 01b6c5fe87..8070b54e87 100644 --- a/src/sagemaker/jumpstart/hub/parsers.py +++ b/src/sagemaker/jumpstart/hub/parsers.py @@ -279,4 +279,10 @@ def make_model_specs_from_describe_hub_content_response( specs["training_instance_type_variants"] = ( hub_model_document.training_instance_type_variants ) + if hub_model_document.default_training_dataset_uri: + _, default_training_dataset_key = parse_s3_url( # pylint: disable=unused-variable + hub_model_document.default_training_dataset_uri + ) + specs["default_training_dataset_key"] = default_training_dataset_key + specs["default_training_dataset_uri"] = hub_model_document.default_training_dataset_uri return JumpStartModelSpecs(_to_json(specs), is_hub_content=True) diff --git a/src/sagemaker/jumpstart/hub/utils.py b/src/sagemaker/jumpstart/hub/utils.py index 1bbc6198a2..75af019ca6 100644 --- a/src/sagemaker/jumpstart/hub/utils.py +++ b/src/sagemaker/jumpstart/hub/utils.py @@ -22,6 +22,7 @@ from sagemaker.jumpstart.types import HubContentType, HubArnExtractedInfo from sagemaker.jumpstart import constants from packaging.specifiers import SpecifierSet, InvalidSpecifier +from packaging import version PROPRIETARY_VERSION_KEYWORD = "@marketplace-version:" @@ -219,9 +220,12 @@ def get_hub_model_version( sagemaker_session = constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION try: - hub_content_summaries = sagemaker_session.list_hub_content_versions( - hub_name=hub_name, hub_content_name=hub_model_name, hub_content_type=hub_model_type - ).get("HubContentSummaries") + hub_content_summaries = _list_hub_content_versions_helper( + hub_name=hub_name, + hub_content_name=hub_model_name, + hub_content_type=hub_model_type, + sagemaker_session=sagemaker_session, + ) except Exception as ex: raise Exception(f"Failed calling list_hub_content_versions: {str(ex)}") @@ -238,13 +242,34 @@ def get_hub_model_version( raise +def _list_hub_content_versions_helper( + hub_name, hub_content_name, hub_content_type, sagemaker_session +): + all_hub_content_summaries = [] + list_hub_content_versions_response = sagemaker_session.list_hub_content_versions( + hub_name=hub_name, hub_content_name=hub_content_name, hub_content_type=hub_content_type + ) + all_hub_content_summaries.extend(list_hub_content_versions_response.get("HubContentSummaries")) + while "NextToken" in list_hub_content_versions_response: + list_hub_content_versions_response = sagemaker_session.list_hub_content_versions( + hub_name=hub_name, + hub_content_name=hub_content_name, + hub_content_type=hub_content_type, + next_token=list_hub_content_versions_response["NextToken"], + ) + all_hub_content_summaries.extend( + list_hub_content_versions_response.get("HubContentSummaries") + ) + return all_hub_content_summaries + + def _get_hub_model_version_for_open_weight_version( hub_content_summaries: List[Any], hub_model_version: Optional[str] = None ) -> str: available_model_versions = [model.get("HubContentVersion") for model in hub_content_summaries] if hub_model_version == "*" or hub_model_version is None: - return str(max(available_model_versions)) + return str(max(version.parse(v) for v in available_model_versions)) try: spec = SpecifierSet(f"=={hub_model_version}") diff --git a/src/sagemaker/jumpstart/types.py b/src/sagemaker/jumpstart/types.py index 349396205e..0cd4bcc902 100644 --- a/src/sagemaker/jumpstart/types.py +++ b/src/sagemaker/jumpstart/types.py @@ -1279,6 +1279,8 @@ class JumpStartMetadataBaseFields(JumpStartDataHolderType): "hosting_neuron_model_version", "hub_content_type", "_is_hub_content", + "default_training_dataset_key", + "default_training_dataset_uri", ] _non_serializable_slots = ["_is_hub_content"] @@ -1462,6 +1464,12 @@ def from_json(self, json_obj: Dict[str, Any]) -> None: else None ) self.model_subscription_link = json_obj.get("model_subscription_link") + self.default_training_dataset_key: Optional[str] = json_obj.get( + "default_training_dataset_key" + ) + self.default_training_dataset_uri: Optional[str] = json_obj.get( + "default_training_dataset_uri" + ) def to_json(self) -> Dict[str, Any]: """Returns json representation of JumpStartMetadataBaseFields object.""" diff --git a/tests/integ/sagemaker/jumpstart/constants.py b/tests/integ/sagemaker/jumpstart/constants.py index 1ffb1d8dc0..740d88e9c0 100644 --- a/tests/integ/sagemaker/jumpstart/constants.py +++ b/tests/integ/sagemaker/jumpstart/constants.py @@ -47,7 +47,7 @@ def _to_s3_path(filename: str, s3_prefix: Optional[str]) -> str: ("huggingface-spc-bert-base-cased", "1.0.0"): ("training-datasets/QNLI-tiny/"), ("huggingface-spc-bert-base-cased", "1.2.3"): ("training-datasets/QNLI-tiny/"), ("huggingface-spc-bert-base-cased", "2.0.3"): ("training-datasets/QNLI-tiny/"), - ("huggingface-spc-bert-base-cased", "*"): ("training-datasets/QNLI-tiny/"), + ("huggingface-spc-bert-base-cased", "*"): ("training-datasets/QNLI/"), ("js-trainable-model", "*"): ("training-datasets/QNLI-tiny/"), ("meta-textgeneration-llama-2-7b", "*"): ("training-datasets/sec_amazon/"), ("meta-textgeneration-llama-2-7b", "2.*"): ("training-datasets/sec_amazon/"), diff --git a/tests/integ/sagemaker/jumpstart/private_hub/estimator/__init__.py b/tests/integ/sagemaker/jumpstart/private_hub/estimator/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/integ/sagemaker/jumpstart/private_hub/estimator/test_jumpstart_private_hub_estimator.py b/tests/integ/sagemaker/jumpstart/private_hub/estimator/test_jumpstart_private_hub_estimator.py new file mode 100644 index 0000000000..a6e33f1bdf --- /dev/null +++ b/tests/integ/sagemaker/jumpstart/private_hub/estimator/test_jumpstart_private_hub_estimator.py @@ -0,0 +1,204 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +import os +import time + +import pytest +from sagemaker.jumpstart.constants import JUMPSTART_DEFAULT_REGION_NAME +from sagemaker.jumpstart.hub.hub import Hub + +from sagemaker.jumpstart.estimator import JumpStartEstimator +from sagemaker.jumpstart.utils import get_jumpstart_content_bucket + +from tests.integ.sagemaker.jumpstart.constants import ( + ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME, + ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID, + JUMPSTART_TAG, +) +from tests.integ.sagemaker.jumpstart.utils import ( + get_public_hub_model_arn, + get_sm_session, + with_exponential_backoff, + get_training_dataset_for_model_and_version, +) + +MAX_INIT_TIME_SECONDS = 5 + +TEST_MODEL_IDS = { + "huggingface-spc-bert-base-cased", + "meta-textgeneration-llama-2-7b", + "catboost-regression-model", +} + + +@with_exponential_backoff() +def create_model_reference(hub_instance, model_arn): + try: + hub_instance.create_model_reference(model_arn=model_arn) + except Exception: + pass + + +@pytest.fixture(scope="session") +def add_model_references(): + # Create Model References to test in Hub + hub_instance = Hub( + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], sagemaker_session=get_sm_session() + ) + for model in TEST_MODEL_IDS: + model_arn = get_public_hub_model_arn(hub_instance, model) + create_model_reference(hub_instance, model_arn) + + +def test_jumpstart_hub_estimator(setup, add_model_references): + model_id, model_version = "huggingface-spc-bert-base-cased", "*" + + estimator = JumpStartEstimator( + model_id=model_id, + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + ) + + estimator.fit( + inputs={ + "training": f"s3://{get_jumpstart_content_bucket(JUMPSTART_DEFAULT_REGION_NAME)}/" + f"{get_training_dataset_for_model_and_version(model_id, model_version)}", + } + ) + + # test that we can create a JumpStartEstimator from existing job with `attach` + estimator = JumpStartEstimator.attach( + training_job_name=estimator.latest_training_job.name, + model_id=model_id, + model_version=model_version, + ) + + # uses ml.p3.2xlarge instance + predictor = estimator.deploy( + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + ) + + response = predictor.predict(["hello", "world"]) + + assert response is not None + + +def test_jumpstart_hub_estimator_with_session(setup, add_model_references): + + model_id, model_version = "huggingface-spc-bert-base-cased", "*" + + sagemaker_session = get_sm_session() + + estimator = JumpStartEstimator( + model_id=model_id, + role=sagemaker_session.get_caller_identity_arn(), + sagemaker_session=sagemaker_session, + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], + ) + + estimator.fit( + inputs={ + "training": f"s3://{get_jumpstart_content_bucket(JUMPSTART_DEFAULT_REGION_NAME)}/" + f"{get_training_dataset_for_model_and_version(model_id, model_version)}", + } + ) + + # test that we can create a JumpStartEstimator from existing job with `attach` + estimator = JumpStartEstimator.attach( + training_job_name=estimator.latest_training_job.name, + model_id=model_id, + model_version=model_version, + sagemaker_session=get_sm_session(), + ) + + # uses ml.p3.2xlarge instance + predictor = estimator.deploy( + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + role=get_sm_session().get_caller_identity_arn(), + sagemaker_session=get_sm_session(), + ) + + response = predictor.predict(["hello", "world"]) + + assert response is not None + + +def test_jumpstart_hub_gated_estimator_with_eula(setup, add_model_references): + + model_id, model_version = "meta-textgeneration-llama-2-7b", "*" + + estimator = JumpStartEstimator( + model_id=model_id, + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + ) + + estimator.fit( + accept_eula=True, + inputs={ + "training": f"s3://{get_jumpstart_content_bucket(JUMPSTART_DEFAULT_REGION_NAME)}/" + f"{get_training_dataset_for_model_and_version(model_id, model_version)}", + }, + ) + + predictor = estimator.deploy( + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + role=get_sm_session().get_caller_identity_arn(), + sagemaker_session=get_sm_session(), + ) + + payload = { + "inputs": "some-payload", + "parameters": {"max_new_tokens": 256, "top_p": 0.9, "temperature": 0.6}, + } + + response = predictor.predict(payload, custom_attributes="accept_eula=true") + + assert response is not None + + +def test_jumpstart_hub_gated_estimator_without_eula(setup, add_model_references): + + model_id, model_version = "meta-textgeneration-llama-2-7b", "*" + + estimator = JumpStartEstimator( + model_id=model_id, + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], + tags=[{"Key": JUMPSTART_TAG, "Value": os.environ[ENV_VAR_JUMPSTART_SDK_TEST_SUITE_ID]}], + ) + with pytest.raises(Exception): + estimator.fit( + inputs={ + "training": f"s3://{get_jumpstart_content_bucket(JUMPSTART_DEFAULT_REGION_NAME)}/" + f"{get_training_dataset_for_model_and_version(model_id, model_version)}", + } + ) + + +def test_instantiating_estimator(setup, add_model_references): + + model_id = "catboost-regression-model" + + start_time = time.perf_counter() + + JumpStartEstimator( + model_id=model_id, + hub_name=os.environ[ENV_VAR_JUMPSTART_SDK_TEST_HUB_NAME], + ) + + elapsed_time = time.perf_counter() - start_time + + assert elapsed_time <= MAX_INIT_TIME_SECONDS diff --git a/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py b/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py index a64db4a97d..c7e039693b 100644 --- a/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py +++ b/tests/integ/sagemaker/jumpstart/private_hub/model/test_jumpstart_private_hub_model.py @@ -48,7 +48,10 @@ @with_exponential_backoff() def create_model_reference(hub_instance, model_arn): - hub_instance.create_model_reference(model_arn=model_arn) + try: + hub_instance.create_model_reference(model_arn=model_arn) + except Exception: + pass @pytest.fixture(scope="session") diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py index 4021599120..0c9065feb5 100644 --- a/tests/unit/sagemaker/jumpstart/constants.py +++ b/tests/unit/sagemaker/jumpstart/constants.py @@ -15553,6 +15553,8 @@ }, "inference_enable_network_isolation": True, "training_enable_network_isolation": True, + "default_training_dataset_uri": None, + "default_training_dataset_key": "training-datasets/tf_flowers/", "resource_name_base": "pt-ic-mobilenet-v2", "hosting_eula_key": None, "hosting_model_package_arns": {}, diff --git a/tests/unit/sagemaker/jumpstart/test_types.py b/tests/unit/sagemaker/jumpstart/test_types.py index acce8ef4f1..0b5ef63947 100644 --- a/tests/unit/sagemaker/jumpstart/test_types.py +++ b/tests/unit/sagemaker/jumpstart/test_types.py @@ -378,6 +378,7 @@ def test_jumpstart_model_specs(): specs1.training_script_key == "source-directory-tarballs/pytorch/transfer_learning/ic/v2.3.0/sourcedir.tar.gz" ) + assert specs1.default_training_dataset_key == "training-datasets/tf_flowers/" assert specs1.hyperparameters == [ JumpStartHyperparameter( { From 8a6ab21c0b3678a414f68369162c94c9919874ec Mon Sep 17 00:00:00 2001 From: Julian Grimm <51880314+Julfried@users.noreply.github.com> Date: Tue, 11 Mar 2025 00:10:46 +0100 Subject: [PATCH 011/164] fix: resolve infinite loop in _find_config on Windows systems (#4970) * fix: resolve Windows path handling in _find_config * Replace Path.match("/") with Path.anchor comparison * Fix infinite loop in _studio.py path traversal * test: Add tests for the new root path exploration * Fix formatting style * Fixed line to long * Fix docstyle by running black manually * Fix testcase with \\ when running on non-windows machines * Fix formatting style * cleanup unused import --- src/sagemaker/_studio.py | 5 ++- tests/unit/sagemaker/test_studio.py | 63 ++++++++++++++++++++++++++++- 2 files changed, 66 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/_studio.py b/src/sagemaker/_studio.py index a23fae87e9..22f1c94c5f 100644 --- a/src/sagemaker/_studio.py +++ b/src/sagemaker/_studio.py @@ -65,7 +65,10 @@ def _find_config(working_dir=None): wd = Path(working_dir) if working_dir else Path.cwd() path = None - while path is None and not wd.match("/"): + + # Get the root of the current working directory for both Windows and Unix-like systems + root = Path(wd.anchor) + while path is None and wd != root: candidate = wd / STUDIO_PROJECT_CONFIG if Path.exists(candidate): path = candidate diff --git a/tests/unit/sagemaker/test_studio.py b/tests/unit/sagemaker/test_studio.py index 47528e1f36..81302894ab 100644 --- a/tests/unit/sagemaker/test_studio.py +++ b/tests/unit/sagemaker/test_studio.py @@ -12,7 +12,8 @@ # language governing permissions and limitations under the License. # language governing permissions and limitations under the License. from __future__ import absolute_import - +import os +from pathlib import Path from sagemaker._studio import ( _append_project_tags, _find_config, @@ -21,6 +22,66 @@ ) +def test_find_config_cross_platform(tmpdir): + """Test _find_config works correctly across different platforms.""" + # Create a completely separate directory for isolated tests + import tempfile + + with tempfile.TemporaryDirectory() as isolated_root: + # Setup test directory structure for positive tests + config = tmpdir.join(".sagemaker-code-config") + config.write('{"sagemakerProjectId": "proj-1234"}') + + # Test 1: Direct parent directory + working_dir = tmpdir.mkdir("sub") + found_path = _find_config(working_dir) + assert found_path == config + + # Test 2: Deeply nested directories + nested_dir = tmpdir.mkdir("deep").mkdir("nested").mkdir("path") + found_path = _find_config(nested_dir) + assert found_path == config + + # Test 3: Start from root directory + import os + + root_dir = os.path.abspath(os.sep) + found_path = _find_config(root_dir) + assert found_path is None + + # Test 4: No config file in path - using truly isolated directory + isolated_path = Path(isolated_root) / "nested" / "path" + isolated_path.mkdir(parents=True) + found_path = _find_config(isolated_path) + assert found_path is None + + +def test_find_config_path_separators(tmpdir): + """Test _find_config handles different path separator styles. + + Tests: + 1. Forward slashes + 2. Backslashes + 3. Mixed separators + """ + # Setup + config = tmpdir.join(".sagemaker-code-config") + config.write('{"sagemakerProjectId": "proj-1234"}') + base_path = str(tmpdir) + + # Always include the OS native path and forward slashes (which are equivalent on all OS) + paths = [os.path.join(base_path, "dir1", "dir2"), "/".join([base_path, "dir1", "dir2"])] + + # Only on Windows add the backslashes and mixed separator test cases. + if os.name == "nt": + paths.extend(["\\".join([base_path, "dir1", "dir2"]), base_path + "/dir1\\dir2"]) + + for path in paths: + os.makedirs(path, exist_ok=True) + found_path = _find_config(path) + assert found_path == config + + def test_find_config(tmpdir): path = tmpdir.join(".sagemaker-code-config") path.write('{"sagemakerProjectId": "proj-1234"}') From 30fe0ee0a04ebab3df09d6bf62290852b4e42c9f Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 11 Mar 2025 14:18:09 +0000 Subject: [PATCH 012/164] change: update image_uri_configs 03-11-2025 07:18:09 PST --- src/sagemaker/image_uri_config/pytorch.json | 94 ++++++++++++++++++++- 1 file changed, 92 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/pytorch.json b/src/sagemaker/image_uri_config/pytorch.json index b3a23733ae..01e0d65dc5 100644 --- a/src/sagemaker/image_uri_config/pytorch.json +++ b/src/sagemaker/image_uri_config/pytorch.json @@ -85,7 +85,8 @@ "2.2": "2.2.0", "2.3": "2.3.0", "2.4": "2.4.0", - "2.5": "2.5.1" + "2.5": "2.5.1", + "2.6": "2.6.0" }, "versions": { "0.4.0": { @@ -1253,6 +1254,50 @@ "us-west-2": "763104351884" }, "repository": "pytorch-inference" + }, + "2.6.0": { + "py_versions": [ + "py312" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "pytorch-inference" } } }, @@ -1628,7 +1673,8 @@ "2.2": "2.2.0", "2.3": "2.3.0", "2.4": "2.4.0", - "2.5": "2.5.1" + "2.5": "2.5.1", + "2.6": "2.6.0" }, "versions": { "0.4.0": { @@ -2801,6 +2847,50 @@ "us-west-2": "763104351884" }, "repository": "pytorch-training" + }, + "2.6.0": { + "py_versions": [ + "py312" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "pytorch-training" } } } From b6bf8cf771d5d29a000a651702e7b1e44550dd37 Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Tue, 11 Mar 2025 20:11:54 -0700 Subject: [PATCH 013/164] Fixing Pytorch training python version in tests (#5084) * Fixing Pytorch training python version in tests * Updating Inference test handling --- tests/conftest.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/tests/conftest.py b/tests/conftest.py index 2c8dc2689f..7557c87fbe 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -254,6 +254,8 @@ def mxnet_eia_latest_py_version(): @pytest.fixture(scope="module", params=["py2", "py3"]) def pytorch_training_py_version(pytorch_training_version, request): + if Version(pytorch_training_version) >= Version("2.6"): + return "py312" if Version(pytorch_training_version) >= Version("2.3"): return "py311" elif Version(pytorch_training_version) >= Version("2.0"): @@ -270,7 +272,9 @@ def pytorch_training_py_version(pytorch_training_version, request): @pytest.fixture(scope="module", params=["py2", "py3"]) def pytorch_inference_py_version(pytorch_inference_version, request): - if Version(pytorch_inference_version) >= Version("2.3"): + if Version(pytorch_inference_version) >= Version("2.6"): + return "py312" + elif Version(pytorch_inference_version) >= Version("2.3"): return "py311" elif Version(pytorch_inference_version) >= Version("2.0"): return "py310" From a282892158d541bd7e9c1ffdf003f67c2781de32 Mon Sep 17 00:00:00 2001 From: Ben Crabtree Date: Wed, 12 Mar 2025 09:40:19 -0700 Subject: [PATCH 014/164] remove s3 output location requirement from hub class init (#5081) * remove s3 output location requirement from hub class init * fix integ test hub * lint * fix test --------- Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> --- src/sagemaker/jumpstart/hub/hub.py | 69 +++++-------------- src/sagemaker/jumpstart/hub/utils.py | 57 --------------- .../unit/sagemaker/jumpstart/hub/test_hub.py | 31 +++------ .../sagemaker/jumpstart/hub/test_utils.py | 41 ----------- 4 files changed, 25 insertions(+), 173 deletions(-) diff --git a/src/sagemaker/jumpstart/hub/hub.py b/src/sagemaker/jumpstart/hub/hub.py index 402b2ce534..692966cee4 100644 --- a/src/sagemaker/jumpstart/hub/hub.py +++ b/src/sagemaker/jumpstart/hub/hub.py @@ -16,15 +16,11 @@ from datetime import datetime import logging from typing import Optional, Dict, List, Any, Union -from botocore import exceptions from sagemaker.jumpstart.constants import JUMPSTART_MODEL_HUB_NAME from sagemaker.jumpstart.enums import JumpStartScriptScope from sagemaker.session import Session -from sagemaker.jumpstart.constants import ( - JUMPSTART_LOGGER, -) from sagemaker.jumpstart.types import ( HubContentType, ) @@ -32,9 +28,6 @@ from sagemaker.jumpstart.hub.utils import ( get_hub_model_version, get_info_from_hub_resource_arn, - create_hub_bucket_if_it_does_not_exist, - generate_default_hub_bucket_name, - create_s3_object_reference_from_uri, construct_hub_arn_from_name, ) @@ -42,9 +35,6 @@ list_jumpstart_models, ) -from sagemaker.jumpstart.hub.types import ( - S3ObjectLocation, -) from sagemaker.jumpstart.hub.interfaces import ( DescribeHubResponse, DescribeHubContentResponse, @@ -66,8 +56,8 @@ class Hub: def __init__( self, hub_name: str, + sagemaker_session: Session, bucket_name: Optional[str] = None, - sagemaker_session: Optional[Session] = None, ) -> None: """Instantiates a SageMaker ``Hub``. @@ -78,41 +68,11 @@ def __init__( """ self.hub_name = hub_name self.region = sagemaker_session.boto_region_name + self.bucket_name = bucket_name self._sagemaker_session = ( sagemaker_session or utils.get_default_jumpstart_session_with_user_agent_suffix(is_hub_content=True) ) - self.hub_storage_location = self._generate_hub_storage_location(bucket_name) - - def _fetch_hub_bucket_name(self) -> str: - """Retrieves hub bucket name from Hub config if exists""" - try: - hub_response = self._sagemaker_session.describe_hub(hub_name=self.hub_name) - hub_output_location = hub_response["S3StorageConfig"].get("S3OutputPath") - if hub_output_location: - location = create_s3_object_reference_from_uri(hub_output_location) - return location.bucket - default_bucket_name = generate_default_hub_bucket_name(self._sagemaker_session) - JUMPSTART_LOGGER.warning( - "There is not a Hub bucket associated with %s. Using %s", - self.hub_name, - default_bucket_name, - ) - return default_bucket_name - except exceptions.ClientError: - hub_bucket_name = generate_default_hub_bucket_name(self._sagemaker_session) - JUMPSTART_LOGGER.warning( - "There is not a Hub bucket associated with %s. Using %s", - self.hub_name, - hub_bucket_name, - ) - return hub_bucket_name - - def _generate_hub_storage_location(self, bucket_name: Optional[str] = None) -> None: - """Generates an ``S3ObjectLocation`` given a Hub name.""" - hub_bucket_name = bucket_name or self._fetch_hub_bucket_name() - curr_timestamp = datetime.now().timestamp() - return S3ObjectLocation(bucket=hub_bucket_name, key=f"{self.hub_name}-{curr_timestamp}") def _get_latest_model_version(self, model_id: str) -> str: """Populates the lastest version of a model from specs no matter what is passed. @@ -132,19 +92,22 @@ def create( tags: Optional[str] = None, ) -> Dict[str, str]: """Creates a hub with the given description""" + curr_timestamp = datetime.now().timestamp() - create_hub_bucket_if_it_does_not_exist( - self.hub_storage_location.bucket, self._sagemaker_session - ) + request = { + "hub_name": self.hub_name, + "hub_description": description, + "hub_display_name": display_name, + "hub_search_keywords": search_keywords, + "tags": tags, + } - return self._sagemaker_session.create_hub( - hub_name=self.hub_name, - hub_description=description, - hub_display_name=display_name, - hub_search_keywords=search_keywords, - s3_storage_config={"S3OutputPath": self.hub_storage_location.get_uri()}, - tags=tags, - ) + if self.bucket_name: + request["s3_storage_config"] = { + "S3OutputPath": (f"s3://{self.bucket_name}/{self.hub_name}-{curr_timestamp}") + } + + return self._sagemaker_session.create_hub(**request) def describe(self, hub_name: Optional[str] = None) -> DescribeHubResponse: """Returns descriptive information about the Hub""" diff --git a/src/sagemaker/jumpstart/hub/utils.py b/src/sagemaker/jumpstart/hub/utils.py index 75af019ca6..0df5e9d5c3 100644 --- a/src/sagemaker/jumpstart/hub/utils.py +++ b/src/sagemaker/jumpstart/hub/utils.py @@ -15,8 +15,6 @@ from __future__ import absolute_import import re from typing import Optional, List, Any -from sagemaker.jumpstart.hub.types import S3ObjectLocation -from sagemaker.s3_utils import parse_s3_url from sagemaker.session import Session from sagemaker.utils import aws_partition from sagemaker.jumpstart.types import HubContentType, HubArnExtractedInfo @@ -139,61 +137,6 @@ def generate_hub_arn_for_init_kwargs( return hub_arn -def generate_default_hub_bucket_name( - sagemaker_session: Session = constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION, -) -> str: - """Return the name of the default bucket to use in relevant Amazon SageMaker Hub interactions. - - Returns: - str: The name of the default bucket. If the name was not explicitly specified through - the Session or sagemaker_config, the bucket will take the form: - ``sagemaker-hubs-{region}-{AWS account ID}``. - """ - - region: str = sagemaker_session.boto_region_name - account_id: str = sagemaker_session.account_id() - - # TODO: Validate and fast fail - - return f"sagemaker-hubs-{region}-{account_id}" - - -def create_s3_object_reference_from_uri(s3_uri: Optional[str]) -> Optional[S3ObjectLocation]: - """Utiity to help generate an S3 object reference""" - if not s3_uri: - return None - - bucket, key = parse_s3_url(s3_uri) - - return S3ObjectLocation( - bucket=bucket, - key=key, - ) - - -def create_hub_bucket_if_it_does_not_exist( - bucket_name: Optional[str] = None, - sagemaker_session: Session = constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION, -) -> str: - """Creates the default SageMaker Hub bucket if it does not exist. - - Returns: - str: The name of the default bucket. Takes the form: - ``sagemaker-hubs-{region}-{AWS account ID}``. - """ - - region: str = sagemaker_session.boto_region_name - if bucket_name is None: - bucket_name: str = generate_default_hub_bucket_name(sagemaker_session) - - sagemaker_session._create_s3_bucket_if_it_does_not_exist( - bucket_name=bucket_name, - region=region, - ) - - return bucket_name - - def is_gated_bucket(bucket_name: str) -> bool: """Returns true if the bucket name is the JumpStart gated bucket.""" return bucket_name in constants.JUMPSTART_GATED_BUCKET_NAME_SET diff --git a/tests/unit/sagemaker/jumpstart/hub/test_hub.py b/tests/unit/sagemaker/jumpstart/hub/test_hub.py index 06f5473322..29efb6b31f 100644 --- a/tests/unit/sagemaker/jumpstart/hub/test_hub.py +++ b/tests/unit/sagemaker/jumpstart/hub/test_hub.py @@ -16,7 +16,6 @@ import pytest from mock import Mock from sagemaker.jumpstart.hub.hub import Hub -from sagemaker.jumpstart.hub.types import S3ObjectLocation REGION = "us-east-1" @@ -60,48 +59,34 @@ def test_instantiates(sagemaker_session): @pytest.mark.parametrize( - ("hub_name,hub_description,hub_bucket_name,hub_display_name,hub_search_keywords,tags"), + ("hub_name,hub_description,,hub_display_name,hub_search_keywords,tags"), [ - pytest.param("MockHub1", "this is my sagemaker hub", None, None, None, None), + pytest.param("MockHub1", "this is my sagemaker hub", None, None, None), pytest.param( "MockHub2", "this is my sagemaker hub two", - None, "DisplayMockHub2", ["mock", "hub", "123"], [{"Key": "tag-key-1", "Value": "tag-value-1"}], ), ], ) -@patch("sagemaker.jumpstart.hub.hub.Hub._generate_hub_storage_location") def test_create_with_no_bucket_name( - mock_generate_hub_storage_location, sagemaker_session, hub_name, hub_description, - hub_bucket_name, hub_display_name, hub_search_keywords, tags, ): - storage_location = S3ObjectLocation( - "sagemaker-hubs-us-east-1-123456789123", f"{hub_name}-{FAKE_TIME.timestamp()}" - ) - mock_generate_hub_storage_location.return_value = storage_location create_hub = {"HubArn": f"arn:aws:sagemaker:us-east-1:123456789123:hub/{hub_name}"} sagemaker_session.create_hub = Mock(return_value=create_hub) - sagemaker_session.describe_hub.return_value = { - "S3StorageConfig": {"S3OutputPath": f"s3://{hub_bucket_name}/{storage_location.key}"} - } hub = Hub(hub_name=hub_name, sagemaker_session=sagemaker_session) request = { "hub_name": hub_name, "hub_description": hub_description, "hub_display_name": hub_display_name, "hub_search_keywords": hub_search_keywords, - "s3_storage_config": { - "S3OutputPath": f"s3://sagemaker-hubs-us-east-1-123456789123/{storage_location.key}" - }, "tags": tags, } response = hub.create( @@ -128,9 +113,9 @@ def test_create_with_no_bucket_name( ), ], ) -@patch("sagemaker.jumpstart.hub.hub.Hub._generate_hub_storage_location") +@patch("sagemaker.jumpstart.hub.hub.datetime") def test_create_with_bucket_name( - mock_generate_hub_storage_location, + mock_datetime, sagemaker_session, hub_name, hub_description, @@ -139,8 +124,8 @@ def test_create_with_bucket_name( hub_search_keywords, tags, ): - storage_location = S3ObjectLocation(hub_bucket_name, f"{hub_name}-{FAKE_TIME.timestamp()}") - mock_generate_hub_storage_location.return_value = storage_location + mock_datetime.now.return_value = FAKE_TIME + create_hub = {"HubArn": f"arn:aws:sagemaker:us-east-1:123456789123:hub/{hub_name}"} sagemaker_session.create_hub = Mock(return_value=create_hub) hub = Hub(hub_name=hub_name, sagemaker_session=sagemaker_session, bucket_name=hub_bucket_name) @@ -149,7 +134,9 @@ def test_create_with_bucket_name( "hub_description": hub_description, "hub_display_name": hub_display_name, "hub_search_keywords": hub_search_keywords, - "s3_storage_config": {"S3OutputPath": f"s3://mock-bucket-123/{storage_location.key}"}, + "s3_storage_config": { + "S3OutputPath": f"s3://mock-bucket-123/{hub_name}-{FAKE_TIME.timestamp()}" + }, "tags": tags, } response = hub.create( diff --git a/tests/unit/sagemaker/jumpstart/hub/test_utils.py b/tests/unit/sagemaker/jumpstart/hub/test_utils.py index a0b824fc9b..5745a7f79c 100644 --- a/tests/unit/sagemaker/jumpstart/hub/test_utils.py +++ b/tests/unit/sagemaker/jumpstart/hub/test_utils.py @@ -173,30 +173,6 @@ def test_generate_hub_arn_for_init_kwargs(): assert utils.generate_hub_arn_for_init_kwargs(hub_arn, None, mock_custom_session) == hub_arn -def test_create_hub_bucket_if_it_does_not_exist_hub_arn(): - mock_sagemaker_session = Mock() - mock_sagemaker_session.account_id.return_value = "123456789123" - mock_sagemaker_session.client("sts").get_caller_identity.return_value = { - "Account": "123456789123" - } - hub_arn = "arn:aws:sagemaker:us-west-2:12346789123:hub/my-awesome-hub" - # Mock custom session with custom values - mock_custom_session = Mock() - mock_custom_session.account_id.return_value = "000000000000" - mock_custom_session.boto_region_name = "us-east-2" - mock_sagemaker_session.boto_session.resource("s3").Bucket().creation_date = None - mock_sagemaker_session.boto_region_name = "us-east-1" - - bucket_name = "sagemaker-hubs-us-east-1-123456789123" - created_hub_bucket_name = utils.create_hub_bucket_if_it_does_not_exist( - sagemaker_session=mock_sagemaker_session - ) - - mock_sagemaker_session.boto_session.resource("s3").create_bucketassert_called_once() - assert created_hub_bucket_name == bucket_name - assert utils.generate_hub_arn_for_init_kwargs(hub_arn, None, mock_custom_session) == hub_arn - - def test_is_gated_bucket(): assert utils.is_gated_bucket("jumpstart-private-cache-prod-us-west-2") is True @@ -207,23 +183,6 @@ def test_is_gated_bucket(): assert utils.is_gated_bucket("") is False -def test_create_hub_bucket_if_it_does_not_exist(): - mock_sagemaker_session = Mock() - mock_sagemaker_session.account_id.return_value = "123456789123" - mock_sagemaker_session.client("sts").get_caller_identity.return_value = { - "Account": "123456789123" - } - mock_sagemaker_session.boto_session.resource("s3").Bucket().creation_date = None - mock_sagemaker_session.boto_region_name = "us-east-1" - bucket_name = "sagemaker-hubs-us-east-1-123456789123" - created_hub_bucket_name = utils.create_hub_bucket_if_it_does_not_exist( - sagemaker_session=mock_sagemaker_session - ) - - mock_sagemaker_session.boto_session.resource("s3").create_bucketassert_called_once() - assert created_hub_bucket_name == bucket_name - - @patch("sagemaker.session.Session") def test_get_hub_model_version_success(mock_session): hub_name = "test_hub" From 8dfb484b00180b8210d9c63030cf5f7f7d741d30 Mon Sep 17 00:00:00 2001 From: rrrkharse <91350438+rrrkharse@users.noreply.github.com> Date: Wed, 12 Mar 2025 12:17:28 -0700 Subject: [PATCH 015/164] fix: Prevent RunContext overlap between test_run tests (#5083) Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> --- tests/integ/sagemaker/experiments/helpers.py | 16 ++++++++++++++ tests/integ/sagemaker/experiments/test_run.py | 22 ++++++++++++++----- 2 files changed, 32 insertions(+), 6 deletions(-) diff --git a/tests/integ/sagemaker/experiments/helpers.py b/tests/integ/sagemaker/experiments/helpers.py index 9a22c3a30c..656cccd8dc 100644 --- a/tests/integ/sagemaker/experiments/helpers.py +++ b/tests/integ/sagemaker/experiments/helpers.py @@ -13,9 +13,12 @@ from __future__ import absolute_import from contextlib import contextmanager +import pytest +import logging from sagemaker import utils from sagemaker.experiments.experiment import Experiment +from sagemaker.experiments._run_context import _RunContext EXP_INTEG_TEST_NAME_PREFIX = "experiments-integ" @@ -40,3 +43,16 @@ def cleanup_exp_resources(exp_names, sagemaker_session): for exp_name in exp_names: exp = Experiment.load(experiment_name=exp_name, sagemaker_session=sagemaker_session) exp._delete_all(action="--force") + +@pytest.fixture +def clear_run_context(): + current_run = _RunContext.get_current_run() + if current_run == None: + return + + logging.info( + f"RunContext already populated by run {current_run.run_name}" + f" in experiment {current_run.experiment_name}." + " Clearing context manually" + ) + _RunContext.drop_current_run() \ No newline at end of file diff --git a/tests/integ/sagemaker/experiments/test_run.py b/tests/integ/sagemaker/experiments/test_run.py index 4f59d11c54..57d3ef41d4 100644 --- a/tests/integ/sagemaker/experiments/test_run.py +++ b/tests/integ/sagemaker/experiments/test_run.py @@ -32,7 +32,7 @@ from sagemaker.experiments.trial_component import _TrialComponent from sagemaker.sklearn import SKLearn from sagemaker.utils import retry_with_backoff, unique_name_from_base -from tests.integ.sagemaker.experiments.helpers import name, cleanup_exp_resources +from tests.integ.sagemaker.experiments.helpers import name, cleanup_exp_resources, clear_run_context from sagemaker.experiments.run import ( RUN_NAME_BASE, DELIMITER, @@ -55,7 +55,7 @@ def artifact_file_path(tempdir): metric_name = "Test-Local-Init-Log-Metric" -def test_local_run_with_load(sagemaker_session, artifact_file_path): +def test_local_run_with_load(sagemaker_session, artifact_file_path, clear_run_context): exp_name = f"My-Local-Exp-{name()}" with cleanup_exp_resources(exp_names=[exp_name], sagemaker_session=sagemaker_session): # Run name is not provided, will create a new TC @@ -86,7 +86,9 @@ def verify_load_run(): retry_with_backoff(verify_load_run, 4) -def test_two_local_run_init_with_same_run_name_and_different_exp_names(sagemaker_session): +def test_two_local_run_init_with_same_run_name_and_different_exp_names( + sagemaker_session, clear_run_context +): exp_name1 = f"my-two-local-exp1-{name()}" exp_name2 = f"my-two-local-exp2-{name()}" run_name = "test-run" @@ -124,7 +126,9 @@ def test_two_local_run_init_with_same_run_name_and_different_exp_names(sagemaker ("my-test4", "test-run", "run-display-name-test"), # with supplied display name ], ) -def test_run_name_vs_trial_component_name_edge_cases(sagemaker_session, input_names): +def test_run_name_vs_trial_component_name_edge_cases( + sagemaker_session, input_names, clear_run_context +): exp_name, run_name, run_display_name = input_names with cleanup_exp_resources(exp_names=[exp_name], sagemaker_session=sagemaker_session): with Run( @@ -177,6 +181,7 @@ def test_run_from_local_and_train_job_and_all_exp_cfg_match( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. The 1st Run created locally and its exp config was auto passed to the job @@ -277,6 +282,7 @@ def test_run_from_local_and_train_job_and_exp_cfg_not_match( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. The 1st Run created locally and its exp config was auto passed to the job @@ -363,6 +369,7 @@ def test_run_from_train_job_only( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. No Run created locally or specified in experiment config @@ -413,6 +420,7 @@ def test_run_from_processing_job_and_override_default_exp_config( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. The 1st Run (run) created locally @@ -492,6 +500,7 @@ def test_run_from_transform_job( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. The 1st Run (run) created locally @@ -573,6 +582,7 @@ def test_load_run_auto_pass_in_exp_config_to_job( execution_role, sagemaker_client_config, sagemaker_metrics_config, + clear_run_context, ): # Notes: # 1. In local side, load the Run created previously and invoke a job under the load context @@ -621,7 +631,7 @@ def test_load_run_auto_pass_in_exp_config_to_job( ) -def test_list(run_obj, sagemaker_session): +def test_list(run_obj, sagemaker_session, clear_run_context): tc1 = _TrialComponent.create( trial_component_name=f"non-run-tc1-{name()}", sagemaker_session=sagemaker_session, @@ -643,7 +653,7 @@ def test_list(run_obj, sagemaker_session): assert run_tcs[0].experiment_config == run_obj.experiment_config -def test_list_twice(run_obj, sagemaker_session): +def test_list_twice(run_obj, sagemaker_session, clear_run_context): tc1 = _TrialComponent.create( trial_component_name=f"non-run-tc1-{name()}", sagemaker_session=sagemaker_session, From 2d0c659d57ccd32326a87c7e20ed8f703c97f018 Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Thu, 13 Mar 2025 18:03:40 -0700 Subject: [PATCH 016/164] Torch upgrade (#5086) * Fix Flake8 Violations * UPDATE PYTORCH VERSION TO ADDRESS SECURITY RISK **Description** Currently used Pytorch version has a possible vulnerability . Internal - https://tiny.amazon.com/p5i4jla1 **Testing Done** Unit and Integration tests in the CodeBuild * REvert CPU Versions * Test Fix * Codestyle fixes * debug attempt * Fixes * Fix * Fix --- tests/data/serve_resources/mlflow/pytorch/conda.yaml | 4 ++-- tests/data/serve_resources/mlflow/pytorch/requirements.txt | 4 ++-- tests/integ/sagemaker/experiments/helpers.py | 5 +++-- .../serve/test_serve_mlflow_pytorch_flavor_happy.py | 6 +++--- tests/unit/sagemaker/jumpstart/constants.py | 2 +- 5 files changed, 11 insertions(+), 10 deletions(-) diff --git a/tests/data/serve_resources/mlflow/pytorch/conda.yaml b/tests/data/serve_resources/mlflow/pytorch/conda.yaml index be61456197..beecdbab08 100644 --- a/tests/data/serve_resources/mlflow/pytorch/conda.yaml +++ b/tests/data/serve_resources/mlflow/pytorch/conda.yaml @@ -17,8 +17,8 @@ dependencies: - pandas==2.2.1 - pyyaml==6.0.1 - requests==2.31.0 - - torch==2.0.1 - - torchvision==0.15.2 + - torch>=2.6.0 + - torchvision>=0.17.0 - tqdm==4.66.2 - scikit-learn==1.3.2 name: mlflow-env diff --git a/tests/data/serve_resources/mlflow/pytorch/requirements.txt b/tests/data/serve_resources/mlflow/pytorch/requirements.txt index 0446ed5053..450bcbfada 100644 --- a/tests/data/serve_resources/mlflow/pytorch/requirements.txt +++ b/tests/data/serve_resources/mlflow/pytorch/requirements.txt @@ -11,6 +11,6 @@ packaging==21.3 pandas==2.2.1 pyyaml==6.0.1 requests==2.32.2 -torch==2.2.0 -torchvision==0.17.0 +torch>=2.6.0 +torchvision>=0.17.0 tqdm==4.66.3 diff --git a/tests/integ/sagemaker/experiments/helpers.py b/tests/integ/sagemaker/experiments/helpers.py index 656cccd8dc..c8f35471b1 100644 --- a/tests/integ/sagemaker/experiments/helpers.py +++ b/tests/integ/sagemaker/experiments/helpers.py @@ -44,10 +44,11 @@ def cleanup_exp_resources(exp_names, sagemaker_session): exp = Experiment.load(experiment_name=exp_name, sagemaker_session=sagemaker_session) exp._delete_all(action="--force") + @pytest.fixture def clear_run_context(): current_run = _RunContext.get_current_run() - if current_run == None: + if current_run is None: return logging.info( @@ -55,4 +56,4 @@ def clear_run_context(): f" in experiment {current_run.experiment_name}." " Clearing context manually" ) - _RunContext.drop_current_run() \ No newline at end of file + _RunContext.drop_current_run() diff --git a/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py b/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py index e6beb76d6e..38ef1e28a3 100644 --- a/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py +++ b/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py @@ -166,9 +166,9 @@ def model_builder(request): # ), f"{caught_ex} was thrown when running pytorch squeezenet local container test" -@pytest.mark.skipif( - PYTHON_VERSION_IS_NOT_310, # or NOT_RUNNING_ON_INF_EXP_DEV_PIPELINE, - reason="The goal of these test are to test the serving components of our feature", +@pytest.mark.skip( + reason="Testing against Python version 310 which is not supported anymore" + " https://github.com/aws/deep-learning-containers/blob/master/available_images.md", ) def test_happy_pytorch_sagemaker_endpoint_with_torch_serve( sagemaker_session, diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py index 0c9065feb5..83e8a44a32 100644 --- a/tests/unit/sagemaker/jumpstart/constants.py +++ b/tests/unit/sagemaker/jumpstart/constants.py @@ -17393,7 +17393,7 @@ "texttable==1.6.7", "tokenize-rt==5.1.0", "tokenizers==0.13.3", - "torch==2.2.0", + "torch>=2.6.0", "transformers==4.33.3", "triton==2.2.0", "typing-extensions==4.8.0", From 305cacd819e2669c7688ef702bc79783fdf2c96e Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 14 Mar 2025 03:28:09 +0000 Subject: [PATCH 017/164] prepare release v2.242.0 --- CHANGELOG.md | 16 ++++++++++++++++ VERSION | 2 +- 2 files changed, 17 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 3e765f5260..df1d902c22 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,21 @@ # Changelog +## v2.242.0 (2025-03-14) + +### Features + + * add integ tests for training JumpStart models in private hub + +### Bug Fixes and Other Changes + + * Torch upgrade + * Prevent RunContext overlap between test_run tests + * remove s3 output location requirement from hub class init + * Fixing Pytorch training python version in tests + * update image_uri_configs 03-11-2025 07:18:09 PST + * resolve infinite loop in _find_config on Windows systems + * pipeline definition function doc update + ## v2.241.0 (2025-03-06) ### Features diff --git a/VERSION b/VERSION index c5d92b1891..187a2a4dcb 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.241.1.dev0 +2.242.0 From b776850d03693c5618ec2a30c679fb028e80338b Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 14 Mar 2025 03:28:14 +0000 Subject: [PATCH 018/164] update development version to v2.242.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 187a2a4dcb..819d69a27e 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.242.0 +2.242.1.dev0 From 1aae9170fc5f02c41ea56c1cbcfb4ff72b72f1f3 Mon Sep 17 00:00:00 2001 From: IshaChid76 <49986634+IshaChid76@users.noreply.github.com> Date: Fri, 14 Mar 2025 16:20:27 -0400 Subject: [PATCH 019/164] add new regions to JUMPSTART_LAUNCHED_REGIONS (#5089) Co-authored-by: isha chidrawar Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> --- src/sagemaker/jumpstart/constants.py | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/src/sagemaker/jumpstart/constants.py b/src/sagemaker/jumpstart/constants.py index 530e7ad16f..dd4ded4748 100644 --- a/src/sagemaker/jumpstart/constants.py +++ b/src/sagemaker/jumpstart/constants.py @@ -81,6 +81,12 @@ gated_content_bucket="jumpstart-private-cache-prod-eu-north-1", neo_content_bucket="sagemaker-sd-models-prod-eu-north-1", ), + JumpStartLaunchedRegionInfo( + region_name="eu-south-2", + content_bucket="jumpstart-cache-prod-eu-south-2", + gated_content_bucket="jumpstart-private-cache-prod-eu-south-2", + neo_content_bucket="sagemaker-sd-models-prod-eu-south-2", + ), JumpStartLaunchedRegionInfo( region_name="me-south-1", content_bucket="jumpstart-cache-prod-me-south-1", @@ -97,6 +103,12 @@ gated_content_bucket="jumpstart-private-cache-prod-ap-south-1", neo_content_bucket="sagemaker-sd-models-prod-ap-south-1", ), + JumpStartLaunchedRegionInfo( + region_name="ap-south-2", + content_bucket="jumpstart-cache-prod-ap-south-2", + gated_content_bucket="jumpstart-private-cache-prod-ap-south-2", + neo_content_bucket="sagemaker-sd-models-prod-ap-south-2", + ), JumpStartLaunchedRegionInfo( region_name="eu-west-3", content_bucket="jumpstart-cache-prod-eu-west-3", @@ -137,6 +149,12 @@ gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-3", neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-3", ), + JumpStartLaunchedRegionInfo( + region_name="ap-southeast-4", + content_bucket="jumpstart-cache-prod-ap-southeast-4", + gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-4", + neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-4", + ), JumpStartLaunchedRegionInfo( region_name="ap-southeast-5", content_bucket="jumpstart-cache-prod-ap-southeast-5", @@ -188,6 +206,12 @@ gated_content_bucket="jumpstart-private-cache-prod-ca-central-1", neo_content_bucket="sagemaker-sd-models-prod-ca-central-1", ), + JumpStartLaunchedRegionInfo( + region_name="ca-west-1", + content_bucket="jumpstart-cache-prod-ca-west-1", + gated_content_bucket="jumpstart-private-cache-prod-ca-west-1", + neo_content_bucket="sagemaker-sd-models-prod-ca-west-1", + ), JumpStartLaunchedRegionInfo( region_name="cn-north-1", content_bucket="jumpstart-cache-prod-cn-north-1", From 65482fa84dc01b5c532c1b8c7225e859cfbdab04 Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Mon, 17 Mar 2025 10:00:27 -0700 Subject: [PATCH 020/164] ADD Documentation to ReadtheDocs for Upgrading torch versions (#5090) * ADD Documentation to ReadtheDocs for Upgrading torch versions **Description** **Testing Done** Only documentation updates * Fix for Codestyle * Remove unused import * Flake8 Fix * CodeStyle Fixes --- doc/overview.rst | 5 +++++ tests/integ/sagemaker/experiments/test_run.py | 22 +++++-------------- .../test_serve_mlflow_pytorch_flavor_happy.py | 2 +- 3 files changed, 12 insertions(+), 17 deletions(-) diff --git a/doc/overview.rst b/doc/overview.rst index 77e6bd0c3b..26601900bd 100644 --- a/doc/overview.rst +++ b/doc/overview.rst @@ -30,6 +30,11 @@ To train a model by using the SageMaker Python SDK, you: After you train a model, you can save it, and then serve the model as an endpoint to get real-time inferences or get inferences for an entire dataset by using batch transform. + +Important Note: + +* When using torch to load Models, it is recommended to use version torch>=2.6.0 and torchvision>=0.17.0 + Prepare a Training script ========================= diff --git a/tests/integ/sagemaker/experiments/test_run.py b/tests/integ/sagemaker/experiments/test_run.py index 57d3ef41d4..4f59d11c54 100644 --- a/tests/integ/sagemaker/experiments/test_run.py +++ b/tests/integ/sagemaker/experiments/test_run.py @@ -32,7 +32,7 @@ from sagemaker.experiments.trial_component import _TrialComponent from sagemaker.sklearn import SKLearn from sagemaker.utils import retry_with_backoff, unique_name_from_base -from tests.integ.sagemaker.experiments.helpers import name, cleanup_exp_resources, clear_run_context +from tests.integ.sagemaker.experiments.helpers import name, cleanup_exp_resources from sagemaker.experiments.run import ( RUN_NAME_BASE, DELIMITER, @@ -55,7 +55,7 @@ def artifact_file_path(tempdir): metric_name = "Test-Local-Init-Log-Metric" -def test_local_run_with_load(sagemaker_session, artifact_file_path, clear_run_context): +def test_local_run_with_load(sagemaker_session, artifact_file_path): exp_name = f"My-Local-Exp-{name()}" with cleanup_exp_resources(exp_names=[exp_name], sagemaker_session=sagemaker_session): # Run name is not provided, will create a new TC @@ -86,9 +86,7 @@ def verify_load_run(): retry_with_backoff(verify_load_run, 4) -def test_two_local_run_init_with_same_run_name_and_different_exp_names( - sagemaker_session, clear_run_context -): +def test_two_local_run_init_with_same_run_name_and_different_exp_names(sagemaker_session): exp_name1 = f"my-two-local-exp1-{name()}" exp_name2 = f"my-two-local-exp2-{name()}" run_name = "test-run" @@ -126,9 +124,7 @@ def test_two_local_run_init_with_same_run_name_and_different_exp_names( ("my-test4", "test-run", "run-display-name-test"), # with supplied display name ], ) -def test_run_name_vs_trial_component_name_edge_cases( - sagemaker_session, input_names, clear_run_context -): +def test_run_name_vs_trial_component_name_edge_cases(sagemaker_session, input_names): exp_name, run_name, run_display_name = input_names with cleanup_exp_resources(exp_names=[exp_name], sagemaker_session=sagemaker_session): with Run( @@ -181,7 +177,6 @@ def test_run_from_local_and_train_job_and_all_exp_cfg_match( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. The 1st Run created locally and its exp config was auto passed to the job @@ -282,7 +277,6 @@ def test_run_from_local_and_train_job_and_exp_cfg_not_match( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. The 1st Run created locally and its exp config was auto passed to the job @@ -369,7 +363,6 @@ def test_run_from_train_job_only( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. No Run created locally or specified in experiment config @@ -420,7 +413,6 @@ def test_run_from_processing_job_and_override_default_exp_config( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. The 1st Run (run) created locally @@ -500,7 +492,6 @@ def test_run_from_transform_job( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. The 1st Run (run) created locally @@ -582,7 +573,6 @@ def test_load_run_auto_pass_in_exp_config_to_job( execution_role, sagemaker_client_config, sagemaker_metrics_config, - clear_run_context, ): # Notes: # 1. In local side, load the Run created previously and invoke a job under the load context @@ -631,7 +621,7 @@ def test_load_run_auto_pass_in_exp_config_to_job( ) -def test_list(run_obj, sagemaker_session, clear_run_context): +def test_list(run_obj, sagemaker_session): tc1 = _TrialComponent.create( trial_component_name=f"non-run-tc1-{name()}", sagemaker_session=sagemaker_session, @@ -653,7 +643,7 @@ def test_list(run_obj, sagemaker_session, clear_run_context): assert run_tcs[0].experiment_config == run_obj.experiment_config -def test_list_twice(run_obj, sagemaker_session, clear_run_context): +def test_list_twice(run_obj, sagemaker_session): tc1 = _TrialComponent.create( trial_component_name=f"non-run-tc1-{name()}", sagemaker_session=sagemaker_session, diff --git a/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py b/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py index 38ef1e28a3..345d5e5af9 100644 --- a/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py +++ b/tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py @@ -31,7 +31,7 @@ PYTORCH_SQUEEZENET_MLFLOW_RESOURCE_DIR, SERVE_SAGEMAKER_ENDPOINT_TIMEOUT, # SERVE_LOCAL_CONTAINER_TIMEOUT, - PYTHON_VERSION_IS_NOT_310, + # PYTHON_VERSION_IS_NOT_310, ) from tests.integ.timeout import timeout from tests.integ.utils import cleanup_model_resources From 9ead9c88874ef0ae0ac1a7adb5f4bad396c47542 Mon Sep 17 00:00:00 2001 From: rsareddy0329 Date: Mon, 17 Mar 2025 21:28:54 -0700 Subject: [PATCH 021/164] feature: Enabled update_endpoint through model_builder (#5085) * feature: Enabled update_endpoint through model_builder * fix: fix unit test, black-check, pylint errors * fix: fix black-check, pylint errors --------- Co-authored-by: Roja Reddy Sareddy --- src/sagemaker/huggingface/model.py | 7 + src/sagemaker/model.py | 56 +++++-- src/sagemaker/serve/builder/model_builder.py | 18 ++- src/sagemaker/session.py | 39 +++++ src/sagemaker/tensorflow/model.py | 2 + .../sagemaker/jumpstart/model/test_model.py | 2 +- tests/unit/sagemaker/model/test_deploy.py | 141 ++++++++++++++++++ .../serve/builder/test_model_builder.py | 83 ++++++++++- 8 files changed, 330 insertions(+), 18 deletions(-) diff --git a/src/sagemaker/huggingface/model.py b/src/sagemaker/huggingface/model.py index 05b981d21b..3ca25fb3ce 100644 --- a/src/sagemaker/huggingface/model.py +++ b/src/sagemaker/huggingface/model.py @@ -218,6 +218,7 @@ def deploy( container_startup_health_check_timeout=None, inference_recommendation_id=None, explainer_config=None, + update_endpoint: Optional[bool] = False, **kwargs, ): """Deploy this ``Model`` to an ``Endpoint`` and optionally return a ``Predictor``. @@ -296,6 +297,11 @@ def deploy( would like to deploy the model and endpoint with recommended parameters. explainer_config (sagemaker.explainer.ExplainerConfig): Specifies online explainability configuration for use with Amazon SageMaker Clarify. (default: None) + update_endpoint (Optional[bool]): + Flag to update the model in an existing Amazon SageMaker endpoint. + If True, this will deploy a new EndpointConfig to an already existing endpoint + and delete resources corresponding to the previous EndpointConfig. Default: False + Note: Currently this is supported for single model endpoints Raises: ValueError: If arguments combination check failed in these circumstances: - If no role is specified or @@ -335,6 +341,7 @@ def deploy( container_startup_health_check_timeout=container_startup_health_check_timeout, inference_recommendation_id=inference_recommendation_id, explainer_config=explainer_config, + update_endpoint=update_endpoint, **kwargs, ) diff --git a/src/sagemaker/model.py b/src/sagemaker/model.py index e5ea1ea314..b281d9f489 100644 --- a/src/sagemaker/model.py +++ b/src/sagemaker/model.py @@ -53,7 +53,6 @@ from sagemaker.model_card.schema_constraints import ModelApprovalStatusEnum from sagemaker.session import Session from sagemaker.model_metrics import ModelMetrics -from sagemaker.deprecations import removed_kwargs from sagemaker.drift_check_baselines import DriftCheckBaselines from sagemaker.explainer import ExplainerConfig from sagemaker.metadata_properties import MetadataProperties @@ -1386,6 +1385,7 @@ def deploy( routing_config: Optional[Dict[str, Any]] = None, model_reference_arn: Optional[str] = None, inference_ami_version: Optional[str] = None, + update_endpoint: Optional[bool] = False, **kwargs, ): """Deploy this ``Model`` to an ``Endpoint`` and optionally return a ``Predictor``. @@ -1497,6 +1497,11 @@ def deploy( inference_ami_version (Optional [str]): Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. For a full list of options, see: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariant.html + update_endpoint (Optional[bool]): + Flag to update the model in an existing Amazon SageMaker endpoint. + If True, this will deploy a new EndpointConfig to an already existing endpoint + and delete resources corresponding to the previous EndpointConfig. Default: False + Note: Currently this is supported for single model endpoints Raises: ValueError: If arguments combination check failed in these circumstances: - If no role is specified or @@ -1512,8 +1517,6 @@ def deploy( """ self.accept_eula = accept_eula - removed_kwargs("update_endpoint", kwargs) - self._init_sagemaker_session_if_does_not_exist(instance_type) # Depending on the instance type, a local session (or) a session is initialized. self.role = resolve_value_from_config( @@ -1628,6 +1631,10 @@ def deploy( # Support multiple models on same endpoint if endpoint_type == EndpointType.INFERENCE_COMPONENT_BASED: + if update_endpoint: + raise ValueError( + "Currently update_endpoint is supported for single model endpoints" + ) if endpoint_name: self.endpoint_name = endpoint_name else: @@ -1783,17 +1790,38 @@ def deploy( if is_explainer_enabled: explainer_config_dict = explainer_config._to_request_dict() - self.sagemaker_session.endpoint_from_production_variants( - name=self.endpoint_name, - production_variants=[production_variant], - tags=tags, - kms_key=kms_key, - wait=wait, - data_capture_config_dict=data_capture_config_dict, - explainer_config_dict=explainer_config_dict, - async_inference_config_dict=async_inference_config_dict, - live_logging=endpoint_logging, - ) + if update_endpoint: + endpoint_config_name = self.sagemaker_session.create_endpoint_config( + name=self.name, + model_name=self.name, + initial_instance_count=initial_instance_count, + instance_type=instance_type, + accelerator_type=accelerator_type, + tags=tags, + kms_key=kms_key, + data_capture_config_dict=data_capture_config_dict, + volume_size=volume_size, + model_data_download_timeout=model_data_download_timeout, + container_startup_health_check_timeout=container_startup_health_check_timeout, + explainer_config_dict=explainer_config_dict, + async_inference_config_dict=async_inference_config_dict, + serverless_inference_config=serverless_inference_config_dict, + routing_config=routing_config, + inference_ami_version=inference_ami_version, + ) + self.sagemaker_session.update_endpoint(self.endpoint_name, endpoint_config_name) + else: + self.sagemaker_session.endpoint_from_production_variants( + name=self.endpoint_name, + production_variants=[production_variant], + tags=tags, + kms_key=kms_key, + wait=wait, + data_capture_config_dict=data_capture_config_dict, + explainer_config_dict=explainer_config_dict, + async_inference_config_dict=async_inference_config_dict, + live_logging=endpoint_logging, + ) if self.predictor_cls: predictor = self.predictor_cls(self.endpoint_name, self.sagemaker_session) diff --git a/src/sagemaker/serve/builder/model_builder.py b/src/sagemaker/serve/builder/model_builder.py index a7a518105c..9122f22e44 100644 --- a/src/sagemaker/serve/builder/model_builder.py +++ b/src/sagemaker/serve/builder/model_builder.py @@ -1602,6 +1602,7 @@ def deploy( ResourceRequirements, ] ] = None, + update_endpoint: Optional[bool] = False, ) -> Union[Predictor, Transformer]: """Deploys the built Model. @@ -1615,24 +1616,33 @@ def deploy( AsyncInferenceConfig, BatchTransformInferenceConfig, ResourceRequirements]]) : Additional Config for different deployment types such as serverless, async, batch and multi-model/container + update_endpoint (Optional[bool]): + Flag to update the model in an existing Amazon SageMaker endpoint. + If True, this will deploy a new EndpointConfig to an already existing endpoint + and delete resources corresponding to the previous EndpointConfig. Default: False + Note: Currently this is supported for single model endpoints Returns: Transformer for Batch Deployments Predictors for all others """ if not hasattr(self, "built_model"): raise ValueError("Model Needs to be built before deploying") - endpoint_name = unique_name_from_base(endpoint_name) + if not update_endpoint: + endpoint_name = unique_name_from_base(endpoint_name) + if not inference_config: # Real-time Deployment return self.built_model.deploy( instance_type=self.instance_type, initial_instance_count=initial_instance_count, endpoint_name=endpoint_name, + update_endpoint=update_endpoint, ) if isinstance(inference_config, ServerlessInferenceConfig): return self.built_model.deploy( serverless_inference_config=inference_config, endpoint_name=endpoint_name, + update_endpoint=update_endpoint, ) if isinstance(inference_config, AsyncInferenceConfig): @@ -1641,6 +1651,7 @@ def deploy( initial_instance_count=initial_instance_count, async_inference_config=inference_config, endpoint_name=endpoint_name, + update_endpoint=update_endpoint, ) if isinstance(inference_config, BatchTransformInferenceConfig): @@ -1652,6 +1663,10 @@ def deploy( return transformer if isinstance(inference_config, ResourceRequirements): + if update_endpoint: + raise ValueError( + "Currently update_endpoint is supported for single model endpoints" + ) # Multi Model and MultiContainer endpoints with Inference Component return self.built_model.deploy( instance_type=self.instance_type, @@ -1660,6 +1675,7 @@ def deploy( resources=inference_config, initial_instance_count=initial_instance_count, role=self.role_arn, + update_endpoint=update_endpoint, ) raise ValueError("Deployment Options not supported") diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py index b2398e03d1..38fa7f8c26 100644 --- a/src/sagemaker/session.py +++ b/src/sagemaker/session.py @@ -4488,6 +4488,10 @@ def create_endpoint_config( model_data_download_timeout=None, container_startup_health_check_timeout=None, explainer_config_dict=None, + async_inference_config_dict=None, + serverless_inference_config_dict=None, + routing_config: Optional[Dict[str, Any]] = None, + inference_ami_version: Optional[str] = None, ): """Create an Amazon SageMaker endpoint configuration. @@ -4525,6 +4529,30 @@ def create_endpoint_config( -inference-algo-ping-requests explainer_config_dict (dict): Specifies configuration to enable explainers. Default: None. + async_inference_config_dict (dict): Specifies + configuration related to async endpoint. Use this configuration when trying + to create async endpoint and make async inference. If empty config object + passed through, will use default config to deploy async endpoint. Deploy a + real-time endpoint if it's None. (default: None). + serverless_inference_config_dict (dict): + Specifies configuration related to serverless endpoint. Use this configuration + when trying to create serverless endpoint and make serverless inference. If + empty object passed through, will use pre-defined values in + ``ServerlessInferenceConfig`` class to deploy serverless endpoint. Deploy an + instance based endpoint if it's None. (default: None). + routing_config (Optional[Dict[str, Any]): Settings the control how the endpoint routes + incoming traffic to the instances that the endpoint hosts. + Currently, support dictionary key ``RoutingStrategy``. + + .. code:: python + + { + "RoutingStrategy": sagemaker.enums.RoutingStrategy.RANDOM + } + inference_ami_version (Optional [str]): + Specifies an option from a collection of preconfigured + Amazon Machine Image (AMI) images. For a full list of options, see: + https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariant.html Example: >>> tags = [{'Key': 'tagname', 'Value': 'tagvalue'}] @@ -4544,9 +4572,12 @@ def create_endpoint_config( instance_type, initial_instance_count, accelerator_type=accelerator_type, + serverless_inference_config=serverless_inference_config_dict, volume_size=volume_size, model_data_download_timeout=model_data_download_timeout, container_startup_health_check_timeout=container_startup_health_check_timeout, + routing_config=routing_config, + inference_ami_version=inference_ami_version, ) production_variants = [provided_production_variant] # Currently we just inject CoreDumpConfig.KmsKeyId from the config for production variant. @@ -4586,6 +4617,14 @@ def create_endpoint_config( ) request["DataCaptureConfig"] = inferred_data_capture_config_dict + if async_inference_config_dict is not None: + inferred_async_inference_config_dict = update_nested_dictionary_with_values_from_config( + async_inference_config_dict, + ENDPOINT_CONFIG_ASYNC_INFERENCE_PATH, + sagemaker_session=self, + ) + request["AsyncInferenceConfig"] = inferred_async_inference_config_dict + if explainer_config_dict is not None: request["ExplainerConfig"] = explainer_config_dict diff --git a/src/sagemaker/tensorflow/model.py b/src/sagemaker/tensorflow/model.py index c7f624114f..b384cbbbb5 100644 --- a/src/sagemaker/tensorflow/model.py +++ b/src/sagemaker/tensorflow/model.py @@ -358,6 +358,7 @@ def deploy( container_startup_health_check_timeout=None, inference_recommendation_id=None, explainer_config=None, + update_endpoint: Optional[bool] = False, **kwargs, ): """Deploy a Tensorflow ``Model`` to a SageMaker ``Endpoint``.""" @@ -383,6 +384,7 @@ def deploy( container_startup_health_check_timeout=container_startup_health_check_timeout, inference_recommendation_id=inference_recommendation_id, explainer_config=explainer_config, + update_endpoint=update_endpoint, **kwargs, ) diff --git a/tests/unit/sagemaker/jumpstart/model/test_model.py b/tests/unit/sagemaker/jumpstart/model/test_model.py index be961828f4..d9b126f651 100644 --- a/tests/unit/sagemaker/jumpstart/model/test_model.py +++ b/tests/unit/sagemaker/jumpstart/model/test_model.py @@ -794,7 +794,7 @@ def test_jumpstart_model_kwargs_match_parent_class(self): and reach out to JumpStart team.""" init_args_to_skip: Set[str] = set(["model_reference_arn"]) - deploy_args_to_skip: Set[str] = set(["kwargs", "model_reference_arn"]) + deploy_args_to_skip: Set[str] = set(["kwargs", "model_reference_arn", "update_endpoint"]) deploy_args_removed_at_deploy_time: Set[str] = set(["model_access_configs"]) parent_class_init = Model.__init__ diff --git a/tests/unit/sagemaker/model/test_deploy.py b/tests/unit/sagemaker/model/test_deploy.py index 7b99281b96..4167ca62c3 100644 --- a/tests/unit/sagemaker/model/test_deploy.py +++ b/tests/unit/sagemaker/model/test_deploy.py @@ -23,6 +23,7 @@ from sagemaker.serverless import ServerlessInferenceConfig from sagemaker.explainer import ExplainerConfig from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements +from sagemaker.enums import EndpointType from tests.unit.sagemaker.inference_recommender.constants import ( DESCRIBE_COMPILATION_JOB_RESPONSE, DESCRIBE_MODEL_PACKAGE_RESPONSE, @@ -1051,3 +1052,143 @@ def test_deploy_with_name_and_resources(sagemaker_session): async_inference_config_dict=None, live_logging=False, ) + + +@patch("sagemaker.model.Model._create_sagemaker_model", Mock()) +@patch("sagemaker.utils.name_from_base", return_value=ENDPOINT_NAME) +@patch("sagemaker.production_variant", return_value=BASE_PRODUCTION_VARIANT) +def test_deploy_with_update_endpoint(production_variant, name_from_base, sagemaker_session): + model = Model( + MODEL_IMAGE, MODEL_DATA, role=ROLE, name=MODEL_NAME, sagemaker_session=sagemaker_session + ) + + # Mock the create_endpoint_config to return a specific config name + endpoint_config_name = "test-config-name" + sagemaker_session.create_endpoint_config.return_value = endpoint_config_name + + # Test update_endpoint=True scenario + endpoint_name = "existing-endpoint" + model.deploy( + instance_type=INSTANCE_TYPE, + initial_instance_count=INSTANCE_COUNT, + endpoint_name=endpoint_name, + update_endpoint=True, + ) + + # Verify create_endpoint_config is called with correct parameters + sagemaker_session.create_endpoint_config.assert_called_with( + name=MODEL_NAME, + model_name=MODEL_NAME, + initial_instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE, + accelerator_type=None, + tags=None, + kms_key=None, + data_capture_config_dict=None, + volume_size=None, + model_data_download_timeout=None, + container_startup_health_check_timeout=None, + explainer_config_dict=None, + async_inference_config_dict=None, + serverless_inference_config=None, + routing_config=None, + inference_ami_version=None, + ) + + # Verify update_endpoint is called with correct parameters + sagemaker_session.update_endpoint.assert_called_with(endpoint_name, endpoint_config_name) + + # Test update_endpoint with serverless config + serverless_inference_config = ServerlessInferenceConfig() + serverless_inference_config_dict = { + "MemorySizeInMB": 2048, + "MaxConcurrency": 5, + } + model.deploy( + endpoint_name=endpoint_name, + update_endpoint=True, + serverless_inference_config=serverless_inference_config, + ) + + sagemaker_session.create_endpoint_config.assert_called_with( + name=MODEL_NAME, + model_name=MODEL_NAME, + initial_instance_count=None, + instance_type=None, + accelerator_type=None, + tags=None, + kms_key=None, + data_capture_config_dict=None, + volume_size=None, + model_data_download_timeout=None, + container_startup_health_check_timeout=None, + explainer_config_dict=None, + async_inference_config_dict=None, + serverless_inference_config=serverless_inference_config_dict, + routing_config=None, + inference_ami_version=None, + ) + + # Verify update_endpoint is called with the new config + sagemaker_session.update_endpoint.assert_called_with(endpoint_name, endpoint_config_name) + + # Test update_endpoint with async inference config + async_inference_config = AsyncInferenceConfig( + output_path="s3://bucket/output", failure_path="s3://bucket/failure" + ) + async_inference_config_dict = { + "OutputConfig": { + "S3OutputPath": "s3://bucket/output", + "S3FailurePath": "s3://bucket/failure", + }, + } + model.deploy( + endpoint_name=endpoint_name, + instance_type=INSTANCE_TYPE, + initial_instance_count=INSTANCE_COUNT, + update_endpoint=True, + async_inference_config=async_inference_config, + ) + + sagemaker_session.create_endpoint_config.assert_called_with( + name=MODEL_NAME, + model_name=MODEL_NAME, + initial_instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE, + accelerator_type=None, + tags=None, + kms_key=None, + data_capture_config_dict=None, + volume_size=None, + model_data_download_timeout=None, + container_startup_health_check_timeout=None, + explainer_config_dict=None, + async_inference_config_dict=async_inference_config_dict, + serverless_inference_config=None, + routing_config=None, + inference_ami_version=None, + ) + + # Verify update_endpoint is called with the new config + sagemaker_session.update_endpoint.assert_called_with(endpoint_name, endpoint_config_name) + + +@patch("sagemaker.model.Model._create_sagemaker_model", Mock()) +@patch("sagemaker.production_variant", return_value=BASE_PRODUCTION_VARIANT) +def test_deploy_with_update_endpoint_inference_component(production_variant, sagemaker_session): + model = Model( + MODEL_IMAGE, MODEL_DATA, role=ROLE, name=MODEL_NAME, sagemaker_session=sagemaker_session + ) + + # Test that updating endpoint with inference component raises error + with pytest.raises( + ValueError, match="Currently update_endpoint is supported for single model endpoints" + ): + model.deploy( + endpoint_name="test-endpoint", + instance_type=INSTANCE_TYPE, + initial_instance_count=INSTANCE_COUNT, + update_endpoint=True, + resources=RESOURCES, + endpoint_type=EndpointType.INFERENCE_COMPONENT_BASED, + ) diff --git a/tests/unit/sagemaker/serve/builder/test_model_builder.py b/tests/unit/sagemaker/serve/builder/test_model_builder.py index 107d65c301..6661c6e2bf 100644 --- a/tests/unit/sagemaker/serve/builder/test_model_builder.py +++ b/tests/unit/sagemaker/serve/builder/test_model_builder.py @@ -4041,14 +4041,30 @@ def test_neuron_configurations_rule_set(self): @pytest.mark.parametrize( "test_case", [ + # Real-time deployment without update { "input_args": {"endpoint_name": "test"}, "call_params": { "instance_type": "ml.g5.2xlarge", "initial_instance_count": 1, "endpoint_name": "test", + "update_endpoint": False, }, }, + # Real-time deployment with update + { + "input_args": { + "endpoint_name": "existing-endpoint", + "update_endpoint": True, + }, + "call_params": { + "instance_type": "ml.g5.2xlarge", + "initial_instance_count": 1, + "endpoint_name": "existing-endpoint", + "update_endpoint": True, + }, + }, + # Serverless deployment without update { "input_args": { "endpoint_name": "test", @@ -4057,8 +4073,23 @@ def test_neuron_configurations_rule_set(self): "call_params": { "serverless_inference_config": ServerlessInferenceConfig(), "endpoint_name": "test", + "update_endpoint": False, }, }, + # Serverless deployment with update + { + "input_args": { + "endpoint_name": "existing-endpoint", + "inference_config": ServerlessInferenceConfig(), + "update_endpoint": True, + }, + "call_params": { + "serverless_inference_config": ServerlessInferenceConfig(), + "endpoint_name": "existing-endpoint", + "update_endpoint": True, + }, + }, + # Async deployment without update { "input_args": { "endpoint_name": "test", @@ -4069,10 +4100,30 @@ def test_neuron_configurations_rule_set(self): "instance_type": "ml.g5.2xlarge", "initial_instance_count": 1, "endpoint_name": "test", + "update_endpoint": False, }, }, + # Async deployment with update { - "input_args": {"endpoint_name": "test", "inference_config": RESOURCE_REQUIREMENTS}, + "input_args": { + "endpoint_name": "existing-endpoint", + "inference_config": AsyncInferenceConfig(output_path="op-path"), + "update_endpoint": True, + }, + "call_params": { + "async_inference_config": AsyncInferenceConfig(output_path="op-path"), + "instance_type": "ml.g5.2xlarge", + "initial_instance_count": 1, + "endpoint_name": "existing-endpoint", + "update_endpoint": True, + }, + }, + # Multi-Model deployment (update_endpoint not supported) + { + "input_args": { + "endpoint_name": "test", + "inference_config": RESOURCE_REQUIREMENTS, + }, "call_params": { "resources": RESOURCE_REQUIREMENTS, "role": "role-arn", @@ -4080,8 +4131,10 @@ def test_neuron_configurations_rule_set(self): "instance_type": "ml.g5.2xlarge", "mode": Mode.SAGEMAKER_ENDPOINT, "endpoint_type": EndpointType.INFERENCE_COMPONENT_BASED, + "update_endpoint": False, }, }, + # Batch transform { "input_args": { "inference_config": BatchTransformInferenceConfig( @@ -4096,7 +4149,16 @@ def test_neuron_configurations_rule_set(self): "id": "Batch", }, ], - ids=["Real Time", "Serverless", "Async", "Multi-Model", "Batch"], + ids=[ + "Real Time", + "Real Time Update", + "Serverless", + "Serverless Update", + "Async", + "Async Update", + "Multi-Model", + "Batch", + ], ) @patch("sagemaker.serve.builder.model_builder.unique_name_from_base") def test_deploy(mock_unique_name_from_base, test_case): @@ -4119,3 +4181,20 @@ def test_deploy(mock_unique_name_from_base, test_case): diff = deepdiff.DeepDiff(kwargs, test_case["call_params"]) assert diff == {} + + +def test_deploy_multi_model_update_error(): + model_builder = ModelBuilder( + model="meta-llama/Meta-Llama-3-8B-Instruct", + env_vars={"HUGGING_FACE_HUB_TOKEN": "token"}, + role_arn="role-arn", + instance_type="ml.g5.2xlarge", + ) + setattr(model_builder, "built_model", MagicMock()) + + with pytest.raises( + ValueError, match="Currently update_endpoint is supported for single model endpoints" + ): + model_builder.deploy( + endpoint_name="test", inference_config=RESOURCE_REQUIREMENTS, update_endpoint=True + ) From f10726f829a54ce6a94835346ac3cfe277b30a0d Mon Sep 17 00:00:00 2001 From: cj-zhang <32367995+cj-zhang@users.noreply.github.com> Date: Wed, 19 Mar 2025 20:05:55 -0700 Subject: [PATCH 022/164] fix: factor in set instance type when building JumpStart models in ModelBuilder. (#5093) * Remove main function entrypoint in ModelBuilder dependency manager. * Remove main function entrypoint in ModelBuilder dependency manager. * fix: factor in set instance type when building JumpStart models in ModelBuilder. * Remove default instance type from ModelBuilder. * Restore default instance type. Tweak integ test. --------- Co-authored-by: Joseph Zhang --- src/sagemaker/serve/builder/jumpstart_builder.py | 1 + tests/integ/sagemaker/serve/test_schema_builder.py | 4 +++- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/serve/builder/jumpstart_builder.py b/src/sagemaker/serve/builder/jumpstart_builder.py index 86a6875721..bf6fcaa376 100644 --- a/src/sagemaker/serve/builder/jumpstart_builder.py +++ b/src/sagemaker/serve/builder/jumpstart_builder.py @@ -157,6 +157,7 @@ def _create_pre_trained_js_model(self) -> Type[Model]: vpc_config=self.vpc_config, sagemaker_session=self.sagemaker_session, name=self.name, + instance_type=self.instance_type, ) self._original_deploy = pysdk_model.deploy diff --git a/tests/integ/sagemaker/serve/test_schema_builder.py b/tests/integ/sagemaker/serve/test_schema_builder.py index 1a2bbe2355..6d3e8281d5 100644 --- a/tests/integ/sagemaker/serve/test_schema_builder.py +++ b/tests/integ/sagemaker/serve/test_schema_builder.py @@ -34,7 +34,9 @@ def test_model_builder_happy_path_with_only_model_id_text_generation(sagemaker_session): model_builder = ModelBuilder( - model="HuggingFaceH4/zephyr-7b-beta", sagemaker_session=sagemaker_session + model="HuggingFaceH4/zephyr-7b-beta", + sagemaker_session=sagemaker_session, + instance_type=None, ) model = model_builder.build(sagemaker_session=sagemaker_session) From eb115a069593488b49909688f1bd49deb3a7452b Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Fri, 21 Mar 2025 14:17:55 +0000 Subject: [PATCH 023/164] change: update image_uri_configs 03-21-2025 07:17:55 PST --- src/sagemaker/image_uri_config/spark.json | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/sagemaker/image_uri_config/spark.json b/src/sagemaker/image_uri_config/spark.json index bb36b25bbb..bbb8c9b123 100644 --- a/src/sagemaker/image_uri_config/spark.json +++ b/src/sagemaker/image_uri_config/spark.json @@ -21,6 +21,7 @@ "ap-southeast-3": "800295151634", "ap-southeast-4": "819679513684", "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", "ca-central-1": "446299261295", "ca-west-1": "000907499111", "cn-north-1": "671472414489", @@ -36,6 +37,7 @@ "il-central-1": "408426139102", "me-central-1": "395420993607", "me-south-1": "750251592176", + "mx-central-1": "211125459255", "sa-east-1": "737130764395", "us-east-1": "173754725891", "us-east-2": "314815235551", @@ -63,6 +65,7 @@ "ap-southeast-3": "800295151634", "ap-southeast-4": "819679513684", "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", "ca-central-1": "446299261295", "ca-west-1": "000907499111", "cn-north-1": "671472414489", @@ -78,6 +81,7 @@ "il-central-1": "408426139102", "me-central-1": "395420993607", "me-south-1": "750251592176", + "mx-central-1": "211125459255", "sa-east-1": "737130764395", "us-east-1": "173754725891", "us-east-2": "314815235551", @@ -105,6 +109,7 @@ "ap-southeast-3": "800295151634", "ap-southeast-4": "819679513684", "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", "ca-central-1": "446299261295", "ca-west-1": "000907499111", "cn-north-1": "671472414489", @@ -120,6 +125,7 @@ "il-central-1": "408426139102", "me-central-1": "395420993607", "me-south-1": "750251592176", + "mx-central-1": "211125459255", "sa-east-1": "737130764395", "us-east-1": "173754725891", "us-east-2": "314815235551", @@ -147,6 +153,7 @@ "ap-southeast-3": "800295151634", "ap-southeast-4": "819679513684", "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", "ca-central-1": "446299261295", "ca-west-1": "000907499111", "cn-north-1": "671472414489", @@ -162,6 +169,7 @@ "il-central-1": "408426139102", "me-central-1": "395420993607", "me-south-1": "750251592176", + "mx-central-1": "211125459255", "sa-east-1": "737130764395", "us-east-1": "173754725891", "us-east-2": "314815235551", @@ -189,6 +197,7 @@ "ap-southeast-3": "800295151634", "ap-southeast-4": "819679513684", "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", "ca-central-1": "446299261295", "ca-west-1": "000907499111", "cn-north-1": "671472414489", @@ -204,6 +213,7 @@ "il-central-1": "408426139102", "me-central-1": "395420993607", "me-south-1": "750251592176", + "mx-central-1": "211125459255", "sa-east-1": "737130764395", "us-east-1": "173754725891", "us-east-2": "314815235551", From a550164539aff433df1913fdb5fd0bda925e097c Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Mon, 24 Mar 2025 10:18:26 -0700 Subject: [PATCH 024/164] Skip tests failed due to deprecated instance type (#5097) Co-authored-by: pintaoz --- tests/integ/sagemaker/serve/test_serve_model_builder_gpu.py | 4 ++++ tests/integ/sagemaker/serve/test_serve_transformers.py | 3 +++ 2 files changed, 7 insertions(+) diff --git a/tests/integ/sagemaker/serve/test_serve_model_builder_gpu.py b/tests/integ/sagemaker/serve/test_serve_model_builder_gpu.py index 8724fc5116..cf1eb65325 100644 --- a/tests/integ/sagemaker/serve/test_serve_model_builder_gpu.py +++ b/tests/integ/sagemaker/serve/test_serve_model_builder_gpu.py @@ -96,6 +96,8 @@ def model_builder(request): def test_non_text_generation_model_single_GPU( sagemaker_session, model_builder, model_input, **kwargs ): + if kwargs["instance_type"] == "ml.p2.xlarge": + pytest.skip("Instance type ml.p2.xlarge has been deprecated") iam_client = sagemaker_session.boto_session.client("iam") role_arn = iam_client.get_role(RoleName="SageMakerRole")["Role"]["Arn"] model = model_builder.build(role_arn=role_arn, sagemaker_session=sagemaker_session) @@ -147,6 +149,8 @@ def test_non_text_generation_model_single_GPU( def test_non_text_generation_model_multi_GPU( sagemaker_session, model_builder, model_input, **kwargs ): + if kwargs["instance_type"] == "ml.p2.xlarge": + pytest.skip("Instance type ml.p2.xlarge has been deprecated") iam_client = sagemaker_session.boto_session.client("iam") role_arn = iam_client.get_role(RoleName="SageMakerRole")["Role"]["Arn"] caught_ex = None diff --git a/tests/integ/sagemaker/serve/test_serve_transformers.py b/tests/integ/sagemaker/serve/test_serve_transformers.py index 5f172f3edb..9405934474 100644 --- a/tests/integ/sagemaker/serve/test_serve_transformers.py +++ b/tests/integ/sagemaker/serve/test_serve_transformers.py @@ -97,6 +97,9 @@ def model_builder(request): def test_pytorch_transformers_sagemaker_endpoint( sagemaker_session, model_builder, model_input, **kwargs ): + if kwargs["instance_type"] == "ml.p2.xlarge": + pytest.skip("Instance type ml.p2.xlarge has been deprecated") + logger.info("Running in SAGEMAKER_ENDPOINT mode...") caught_ex = None From 149149943e129c7fc2c4288b1dbac43bda19f46b Mon Sep 17 00:00:00 2001 From: Keshav Chandak Date: Tue, 25 Mar 2025 00:36:46 +0530 Subject: [PATCH 025/164] Feat: Added support for returing most recently created approved model package in a group (#5092) Co-authored-by: Keshav Chandak --- src/sagemaker/session.py | 43 +++++++++++++++++++++++++ tests/integ/test_session.py | 62 ++++++++++++++++++++++++++++++++++++- tests/unit/test_session.py | 32 +++++++++++++++++++ 3 files changed, 136 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py index 38fa7f8c26..797d559348 100644 --- a/src/sagemaker/session.py +++ b/src/sagemaker/session.py @@ -4463,6 +4463,49 @@ def wait_for_model_package(self, model_package_name, poll=5): ) return desc + def get_most_recently_created_approved_model_package(self, model_package_group_name): + """Returns the most recently created and Approved model package in a model package group + + Args: + model_package_group_name (str): Name or Arn of the model package group + + Returns: + dict: Returns a "sagemaker.model.ModelPackage" value. + """ + + approved_model_packages = self.sagemaker_client.list_model_packages( + ModelPackageGroupName=model_package_group_name, + ModelApprovalStatus="Approved", + SortBy="CreationTime", + SortOrder="Descending", + MaxResults=1, + ) + next_token = approved_model_packages.get("NextToken") + + while ( + len(approved_model_packages.get("ModelPackageSummaryList")) == 0 + and next_token is not None + and next_token != "" + ): + approved_model_packages = self.sagemaker_client.list_model_packages( + ModelPackageGroupName=model_package_group_name, + ModelApprovalStatus="Approved", + SortBy="CreationTime", + SortOrder="Descending", + MaxResults=1, + NextToken=next_token, + ) + next_token = approved_model_packages.get("NextToken") + + if len(approved_model_packages.get("ModelPackageSummaryList")) == 0: + return None + + return sagemaker.model.ModelPackage( + model_package_arn=approved_model_packages.get("ModelPackageSummaryList")[0].get( + "ModelPackageArn" + ) + ) + def describe_model(self, name): """Calls the DescribeModel API for the given model name. diff --git a/tests/integ/test_session.py b/tests/integ/test_session.py index 0015efe3fd..0b2900bef7 100644 --- a/tests/integ/test_session.py +++ b/tests/integ/test_session.py @@ -15,7 +15,8 @@ import boto3 from botocore.config import Config -from sagemaker import Session +from sagemaker import Session, ModelPackage +from sagemaker.utils import unique_name_from_base CUSTOM_BUCKET_NAME = "this-bucket-should-not-exist" @@ -44,3 +45,62 @@ def test_sagemaker_session_does_not_create_bucket_on_init( s3 = boto3.resource("s3", region_name=boto_session.region_name) assert s3.Bucket(CUSTOM_BUCKET_NAME).creation_date is None + + +def test_sagemaker_session_to_return_most_recent_approved_model_package(sagemaker_session): + model_package_group_name = unique_name_from_base("test-model-package-group") + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is None + sagemaker_session.sagemaker_client.create_model_package_group( + ModelPackageGroupName=model_package_group_name + ) + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is None + source_uri = "dummy source uri" + model_package = sagemaker_session.sagemaker_client.create_model_package( + ModelPackageGroupName=model_package_group_name, SourceUri=source_uri + ) + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is None + ModelPackage( + sagemaker_session=sagemaker_session, + model_package_arn=model_package["ModelPackageArn"], + ).update_approval_status(approval_status="Approved") + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is not None + assert approved_model_package.model_package_arn == model_package.get("ModelPackageArn") + model_package_2 = sagemaker_session.sagemaker_client.create_model_package( + ModelPackageGroupName=model_package_group_name, SourceUri=source_uri + ) + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is not None + assert approved_model_package.model_package_arn == model_package.get("ModelPackageArn") + ModelPackage( + sagemaker_session=sagemaker_session, + model_package_arn=model_package_2["ModelPackageArn"], + ).update_approval_status(approval_status="Approved") + approved_model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name=model_package_group_name + ) + assert approved_model_package is not None + assert approved_model_package.model_package_arn == model_package_2.get("ModelPackageArn") + + sagemaker_session.sagemaker_client.delete_model_package( + ModelPackageName=model_package_2["ModelPackageArn"] + ) + sagemaker_session.sagemaker_client.delete_model_package( + ModelPackageName=model_package["ModelPackageArn"] + ) + sagemaker_session.sagemaker_client.delete_model_package_group( + ModelPackageGroupName=model_package_group_name + ) diff --git a/tests/unit/test_session.py b/tests/unit/test_session.py index f873e9b14c..e3d763e612 100644 --- a/tests/unit/test_session.py +++ b/tests/unit/test_session.py @@ -7253,3 +7253,35 @@ def test_create_model_package_from_containers_to_create_mpg_if_not_present(sagem sagemaker_session.sagemaker_client.create_model_package_group.assert_called_with( ModelPackageGroupName="mock-mpg" ) + + +def test_get_most_recently_created_approved_model_package(sagemaker_session): + sagemaker_session.sagemaker_client.list_model_packages.side_effect = [ + ( + { + "ModelPackageSummaryList": [], + "NextToken": "NextToken", + } + ), + ( + { + "ModelPackageSummaryList": [ + { + "CreationTime": 1697440162, + "ModelApprovalStatus": "Approved", + "ModelPackageArn": "arn:aws:sagemaker:us-west-2:123456789012:model-package/model-version/3", + "ModelPackageGroupName": "model-version", + "ModelPackageVersion": 3, + }, + ], + } + ), + ] + model_package = sagemaker_session.get_most_recently_created_approved_model_package( + model_package_group_name="mpg" + ) + assert model_package is not None + assert ( + model_package.model_package_arn + == "arn:aws:sagemaker:us-west-2:123456789012:model-package/model-version/3" + ) From 6ddd5597f19ff6429cbdfd1c1eb880ad781b8946 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 25 Mar 2025 14:18:13 +0000 Subject: [PATCH 026/164] change: update image_uri_configs 03-25-2025 07:18:13 PST --- src/sagemaker/image_uri_config/sagemaker-base-python.json | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/sagemaker/image_uri_config/sagemaker-base-python.json b/src/sagemaker/image_uri_config/sagemaker-base-python.json index e1de6bfd21..65b284d25e 100644 --- a/src/sagemaker/image_uri_config/sagemaker-base-python.json +++ b/src/sagemaker/image_uri_config/sagemaker-base-python.json @@ -12,6 +12,7 @@ "ap-southeast-2": "452832661640", "ap-southeast-3": "276181064229", "ap-southeast-5": "148761635175", + "ap-southeast-7": "528757812139", "ca-central-1": "310906938811", "cn-north-1": "390048526115", "cn-northwest-1": "390780980154", @@ -26,6 +27,7 @@ "il-central-1": "380164790875", "me-central-1": "103105715889", "me-south-1": "117516905037", + "mx-central-1": "396913743851", "sa-east-1": "782484402741", "us-east-1": "081325390199", "us-east-2": "429704687514", From 11dbba98464a11474f9f9663822d4a117e730dfd Mon Sep 17 00:00:00 2001 From: Rohan Narayan Date: Tue, 25 Mar 2025 20:06:08 -0400 Subject: [PATCH 027/164] chore: fix integ tests to use latest version of model (#5104) --- tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py b/tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py index 5e54c7551f..c9a39ac3dc 100644 --- a/tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py +++ b/tests/integ/sagemaker/jumpstart/model/test_jumpstart_model.py @@ -170,7 +170,7 @@ def test_jumpstart_gated_model(setup): model = JumpStartModel( model_id=model_id, - model_version="3.*", # version >=3.0.0 stores artifacts in jumpstart-private-cache-* buckets + model_version="*", # version >=3.0.0 stores artifacts in jumpstart-private-cache-* buckets role=get_sm_session().get_caller_identity_arn(), sagemaker_session=get_sm_session(), ) @@ -197,7 +197,7 @@ def test_jumpstart_gated_model_inference_component_enabled(setup): model = JumpStartModel( model_id=model_id, - model_version="3.*", # version >=3.0.0 stores artifacts in jumpstart-private-cache-* buckets + model_version="*", # version >=3.0.0 stores artifacts in jumpstart-private-cache-* buckets role=get_sm_session().get_caller_identity_arn(), sagemaker_session=get_sm_session(), ) From d018442dfa7388fef0372663a5f982d84b3bc83f Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Wed, 26 Mar 2025 14:18:16 +0000 Subject: [PATCH 028/164] change: update image_uri_configs 03-26-2025 07:18:16 PST --- .../huggingface-llm-neuronx.json | 246 +++++++++++-- .../image_uri_config/huggingface-llm.json | 329 +++++++++++------- 2 files changed, 423 insertions(+), 152 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index 478d6ff597..ed5c289377 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -12,30 +12,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.16", "repository": "huggingface-pytorch-tgi-inference", @@ -48,30 +64,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.17", "repository": "huggingface-pytorch-tgi-inference", @@ -84,30 +116,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.18", "repository": "huggingface-pytorch-tgi-inference", @@ -120,30 +168,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.19", "repository": "huggingface-pytorch-tgi-inference", @@ -156,30 +220,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.20", "repository": "huggingface-pytorch-tgi-inference", @@ -192,30 +272,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "1.13.1-optimum0.0.21", "repository": "huggingface-pytorch-tgi-inference", @@ -228,28 +324,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "2.1.2-optimum0.0.22", "repository": "huggingface-pytorch-tgi-inference", @@ -262,30 +376,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "2.1.2-optimum0.0.23", "repository": "huggingface-pytorch-tgi-inference", @@ -298,30 +428,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "2.1.2-optimum0.0.24", "repository": "huggingface-pytorch-tgi-inference", @@ -334,30 +480,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", - "mx-central-1":"637423239942", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "2.1.2-optimum0.0.25", "repository": "huggingface-pytorch-tgi-inference", @@ -370,28 +532,46 @@ "py310" ], "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", "ap-south-1": "763104351884", "ap-south-2": "772153158452", "ap-southeast-1": "763104351884", "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", "eu-south-2": "503227376785", "eu-west-1": "763104351884", + "eu-west-2": "763104351884", "eu-west-3": "763104351884", "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", "us-gov-east-1": "446045086412", "us-gov-west-1": "442386744353", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" }, "tag_prefix": "2.1.2-optimum0.0.27", "repository": "huggingface-pytorch-tgi-inference", @@ -401,4 +581,4 @@ } } } -} +} \ No newline at end of file diff --git a/src/sagemaker/image_uri_config/huggingface-llm.json b/src/sagemaker/image_uri_config/huggingface-llm.json index cc6b2b20a0..27df32a073 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm.json +++ b/src/sagemaker/image_uri_config/huggingface-llm.json @@ -13,6 +13,7 @@ "1.3": "1.3.3", "1.4": "1.4.5", "2.0": "2.4.0", + "2.3": "2.3.1", "3.0": "3.0.1" }, "versions": { @@ -22,7 +23,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -33,19 +33,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -53,9 +58,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.0.0-tgi0.6.0", "repository": "huggingface-pytorch-tgi-inference", @@ -69,7 +75,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -80,19 +85,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -100,9 +110,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.0.0-tgi0.8.2", "repository": "huggingface-pytorch-tgi-inference", @@ -116,7 +127,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -127,19 +137,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -147,9 +162,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.0.1-tgi0.9.3", "repository": "huggingface-pytorch-tgi-inference", @@ -163,7 +179,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -174,19 +189,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -194,9 +214,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.0.1-tgi1.0.3", "repository": "huggingface-pytorch-tgi-inference", @@ -210,7 +231,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -221,19 +241,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -241,9 +266,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.0.1-tgi1.1.0", "repository": "huggingface-pytorch-tgi-inference", @@ -257,7 +283,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -268,19 +293,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -288,9 +318,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.1.1-tgi1.2.0", "repository": "huggingface-pytorch-tgi-inference", @@ -304,7 +335,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -315,19 +345,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -335,9 +370,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.1.1-tgi1.3.1", "repository": "huggingface-pytorch-tgi-inference", @@ -351,7 +387,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -362,19 +397,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", "eu-west-1": "763104351884", "eu-west-2": "763104351884", "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -382,9 +422,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + 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"763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", "eu-south-1": "692866216735", "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -476,9 +526,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.1.1-tgi1.4.2", "repository": "huggingface-pytorch-tgi-inference", @@ -492,7 +543,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -503,19 +553,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", "eu-south-1": 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"us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.1.1-tgi2.0.0", "repository": "huggingface-pytorch-tgi-inference", @@ -586,7 +647,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -597,19 +657,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - 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"ap-northeast-2": "763104351884", @@ -644,19 +709,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", "eu-south-1": "692866216735", "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -664,9 +734,10 @@ "us-gov-west-1": 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"763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", "eu-south-1": "692866216735", "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -805,9 +890,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.4.0-tgi2.4.0", "repository": "huggingface-pytorch-tgi-inference", @@ -821,7 +907,6 @@ ], "registries": { "af-south-1": "626614931356", - "il-central-1": "780543022126", "ap-east-1": "871362719292", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", @@ -832,19 +917,24 @@ "ap-southeast-2": "763104351884", "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", + "ca-west-1": "204538143572", "cn-north-1": "727897471807", "cn-northwest-1": "727897471807", "eu-central-1": "763104351884", "eu-central-2": "380420809688", "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", "eu-south-1": "692866216735", "eu-south-2": "503227376785", - "me-south-1": "217643126080", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", "sa-east-1": "763104351884", "us-east-1": "763104351884", "us-east-2": "763104351884", @@ -852,9 +942,10 @@ "us-gov-west-1": "442386744353", "us-iso-east-1": "886529160074", "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" + "us-west-2": "763104351884" }, "tag_prefix": "2.4.0-tgi3.0.1", "repository": "huggingface-pytorch-tgi-inference", @@ -864,4 +955,4 @@ } } } -} +} \ No newline at end of file From c84f54faa8a8396b5126dd25549fb8f273abcefe Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 26 Mar 2025 13:15:39 -0700 Subject: [PATCH 029/164] Update Jinja version (#5101) --- doc/requirements.txt | 2 +- requirements/extras/test_requirements.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/requirements.txt b/doc/requirements.txt index 9bef9392a8..71a95f7633 100644 --- a/doc/requirements.txt +++ b/doc/requirements.txt @@ -2,7 +2,7 @@ sphinx==5.1.1 sphinx-rtd-theme==0.5.0 docutils==0.15.2 packaging==20.9 -jinja2==3.1.4 +jinja2==3.1.6 schema==0.7.5 accelerate>=0.24.1,<=0.27.0 graphene<4.0 diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index fe31300c22..2789463a97 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -20,7 +20,7 @@ attrs>=23.1.0,<24 fabric==2.6.0 requests==2.32.2 sagemaker-experiments==0.1.35 -Jinja2==3.1.4 +Jinja2==3.1.6 pyvis==0.2.1 pandas==1.4.4 scikit-learn==1.3.0 From d0ccacf5520c1dc9ee110695dc62f22f7afa5bde Mon Sep 17 00:00:00 2001 From: Bruno Pistone Date: Thu, 27 Mar 2025 01:19:31 +0100 Subject: [PATCH 030/164] Aligned disable_output_compression for @remote with Estimator (#5094) --- src/sagemaker/remote_function/client.py | 14 +++++- src/sagemaker/remote_function/job.py | 9 +++- .../test_feature_scheduler.py | 1 + .../sagemaker/remote_function/test_client.py | 1 + .../sagemaker/remote_function/test_job.py | 50 +++++++++++++++++-- 5 files changed, 69 insertions(+), 6 deletions(-) diff --git a/src/sagemaker/remote_function/client.py b/src/sagemaker/remote_function/client.py index 76a8443fba..55b4654aa9 100644 --- a/src/sagemaker/remote_function/client.py +++ b/src/sagemaker/remote_function/client.py @@ -90,6 +90,7 @@ def remote( spark_config: SparkConfig = None, use_spot_instances=False, max_wait_time_in_seconds=None, + disable_output_compression: bool = False, use_torchrun: bool = False, use_mpirun: bool = False, nproc_per_node: Optional[int] = None, @@ -283,13 +284,16 @@ def remote( After this amount of time Amazon SageMaker will stop waiting for managed spot training job to complete. Defaults to ``None``. + disable_output_compression (bool): Optional. When set to true, Model is uploaded to + Amazon S3 without compression after training finishes. + use_torchrun (bool): Specifies whether to use torchrun for distributed training. Defaults to ``False``. use_mpirun (bool): Specifies whether to use mpirun for distributed training. Defaults to ``False``. - nproc_per_node (Optional int): Specifies the number of processes per node for + nproc_per_node (int): Optional. Specifies the number of processes per node for distributed training. Defaults to ``None``. This is defined automatically configured on the instance type. """ @@ -324,6 +328,7 @@ def _remote(func): spark_config=spark_config, use_spot_instances=use_spot_instances, max_wait_time_in_seconds=max_wait_time_in_seconds, + disable_output_compression=disable_output_compression, use_torchrun=use_torchrun, use_mpirun=use_mpirun, nproc_per_node=nproc_per_node, @@ -543,6 +548,7 @@ def __init__( spark_config: SparkConfig = None, use_spot_instances=False, max_wait_time_in_seconds=None, + disable_output_compression: bool = False, use_torchrun: bool = False, use_mpirun: bool = False, nproc_per_node: Optional[int] = None, @@ -736,13 +742,16 @@ def __init__( After this amount of time Amazon SageMaker will stop waiting for managed spot training job to complete. Defaults to ``None``. + disable_output_compression (bool): Optional. When set to true, Model is uploaded to + Amazon S3 without compression after training finishes. + use_torchrun (bool): Specifies whether to use torchrun for distributed training. Defaults to ``False``. use_mpirun (bool): Specifies whether to use mpirun for distributed training. Defaults to ``False``. - nproc_per_node (Optional int): Specifies the number of processes per node for + nproc_per_node (int): Optional. Specifies the number of processes per node for distributed training. Defaults to ``None``. This is defined automatically configured on the instance type. """ @@ -790,6 +799,7 @@ def __init__( spark_config=spark_config, use_spot_instances=use_spot_instances, max_wait_time_in_seconds=max_wait_time_in_seconds, + disable_output_compression=disable_output_compression, use_torchrun=use_torchrun, use_mpirun=use_mpirun, nproc_per_node=nproc_per_node, diff --git a/src/sagemaker/remote_function/job.py b/src/sagemaker/remote_function/job.py index 52cb0ff04f..9000ccda08 100644 --- a/src/sagemaker/remote_function/job.py +++ b/src/sagemaker/remote_function/job.py @@ -373,6 +373,7 @@ def __init__( spark_config: SparkConfig = None, use_spot_instances=False, max_wait_time_in_seconds=None, + disable_output_compression: bool = False, use_torchrun: bool = False, use_mpirun: bool = False, nproc_per_node: Optional[int] = None, @@ -558,13 +559,16 @@ def __init__( After this amount of time Amazon SageMaker will stop waiting for managed spot training job to complete. Defaults to ``None``. + disable_output_compression (bool): Optional. When set to true, Model is uploaded to + Amazon S3 without compression after training finishes. + use_torchrun (bool): Specifies whether to use torchrun for distributed training. Defaults to ``False``. use_mpirun (bool): Specifies whether to use mpirun for distributed training. Defaults to ``False``. - nproc_per_node (Optional int): Specifies the number of processes per node for + nproc_per_node (int): Optional. Specifies the number of processes per node for distributed training. Defaults to ``None``. This is defined automatically configured on the instance type. """ @@ -725,6 +729,7 @@ def __init__( tags = format_tags(tags) self.tags = self.sagemaker_session._append_sagemaker_config_tags(tags, REMOTE_FUNCTION_TAGS) + self.disable_output_compression = disable_output_compression self.use_torchrun = use_torchrun self.use_mpirun = use_mpirun self.nproc_per_node = nproc_per_node @@ -954,6 +959,8 @@ def compile( output_config = {"S3OutputPath": s3_base_uri} if job_settings.s3_kms_key is not None: output_config["KmsKeyId"] = job_settings.s3_kms_key + if job_settings.disable_output_compression: + output_config["CompressionType"] = "NONE" request_dict["OutputDataConfig"] = output_config container_args = ["--s3_base_uri", s3_base_uri] diff --git a/tests/unit/sagemaker/feature_store/feature_processor/test_feature_scheduler.py b/tests/unit/sagemaker/feature_store/feature_processor/test_feature_scheduler.py index 00bd3ca090..7b35174940 100644 --- a/tests/unit/sagemaker/feature_store/feature_processor/test_feature_scheduler.py +++ b/tests/unit/sagemaker/feature_store/feature_processor/test_feature_scheduler.py @@ -907,6 +907,7 @@ def test_remote_decorator_fields_consistency(get_execution_role, session): "use_spot_instances", "max_wait_time_in_seconds", "custom_file_filter", + "disable_output_compression", "use_torchrun", "use_mpirun", "nproc_per_node", diff --git a/tests/unit/sagemaker/remote_function/test_client.py b/tests/unit/sagemaker/remote_function/test_client.py index 6c2a373dbc..de8758bfad 100644 --- a/tests/unit/sagemaker/remote_function/test_client.py +++ b/tests/unit/sagemaker/remote_function/test_client.py @@ -1504,6 +1504,7 @@ def test_consistency_between_remote_and_step_decorator(): "s3_kms_key", "s3_root_uri", "sagemaker_session", + "disable_output_compression", "use_torchrun", "use_mpirun", "nproc_per_node", diff --git a/tests/unit/sagemaker/remote_function/test_job.py b/tests/unit/sagemaker/remote_function/test_job.py index 671f091d02..5be84fe5ba 100644 --- a/tests/unit/sagemaker/remote_function/test_job.py +++ b/tests/unit/sagemaker/remote_function/test_job.py @@ -291,8 +291,8 @@ def mock_get_current_run(): return current_run -def describe_training_job_response(job_status): - return { +def describe_training_job_response(job_status, disable_output_compression=False): + job_response = { "TrainingJobArn": TRAINING_JOB_ARN, "TrainingJobStatus": job_status, "ResourceConfig": { @@ -300,15 +300,38 @@ def describe_training_job_response(job_status): "InstanceType": "ml.c4.xlarge", "VolumeSizeInGB": 30, }, - "OutputDataConfig": {"S3OutputPath": "s3://sagemaker-123/image_uri/output"}, } + if disable_output_compression: + output_config = { + "S3OutputPath": "s3://sagemaker-123/image_uri/output", + "CompressionType": "NONE", + } + else: + output_config = { + "S3OutputPath": "s3://sagemaker-123/image_uri/output", + "CompressionType": "NONE", + } + + job_response["OutputDataConfig"] = output_config + + return job_response + COMPLETED_TRAINING_JOB = describe_training_job_response("Completed") INPROGRESS_TRAINING_JOB = describe_training_job_response("InProgress") CANCELLED_TRAINING_JOB = describe_training_job_response("Stopped") FAILED_TRAINING_JOB = describe_training_job_response("Failed") +COMPLETED_TRAINING_JOB_DISABLE_OUTPUT_COMPRESSION = describe_training_job_response( + "Completed", True +) +INPROGRESS_TRAINING_JOB_DISABLE_OUTPUT_COMPRESSION = describe_training_job_response( + "InProgress", True +) +CANCELLED_TRAINING_JOB_DISABLE_OUTPUT_COMPRESSION = describe_training_job_response("Stopped", True) +FAILED_TRAINING_JOB_DISABLE_OUTPUT_COMPRESSION = describe_training_job_response("Failed", True) + def mock_session(): session = Mock() @@ -1303,6 +1326,27 @@ def test_describe(session, *args): session().sagemaker_client.describe_training_job.assert_called_once() +@patch("sagemaker.remote_function.job._prepare_and_upload_runtime_scripts") +@patch("sagemaker.remote_function.job._prepare_and_upload_workspace") +@patch("sagemaker.remote_function.job.StoredFunction") +@patch("sagemaker.remote_function.job.Session", return_value=mock_session()) +def test_describe_disable_output_compression(session, *args): + + job_settings = _JobSettings( + image_uri=IMAGE, + s3_root_uri=S3_URI, + role=ROLE_ARN, + instance_type="ml.m5.large", + disable_output_compression=True, + ) + job = _Job.start(job_settings, job_function, func_args=(1, 2), func_kwargs={"c": 3, "d": 4}) + + job.describe() + assert job.describe() == COMPLETED_TRAINING_JOB_DISABLE_OUTPUT_COMPRESSION + + session().sagemaker_client.describe_training_job.assert_called_once() + + @patch("sagemaker.remote_function.job._prepare_and_upload_runtime_scripts") @patch("sagemaker.remote_function.job._prepare_and_upload_workspace") @patch("sagemaker.remote_function.job.StoredFunction") From af05231d719431cada1fa4c897d34e9d94f3b197 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 26 Mar 2025 21:55:45 -0700 Subject: [PATCH 031/164] Update transformers version (#5102) --- requirements/extras/test_requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 2789463a97..de960e4619 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -33,7 +33,7 @@ pillow>=10.0.1,<=11 opentelemetry-proto==1.27.0 protobuf==4.25.5 tensorboard>=2.9.0,<=2.15.2 -transformers==4.46.1 +transformers==4.48.0 sentencepiece==0.1.99 # https://github.com/triton-inference-server/server/issues/6246 tritonclient[http]<2.37.0 From 9d8e1f562ea63ba6acd3cb621715c9a1c7cf5f6e Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Thu, 27 Mar 2025 09:35:23 -0700 Subject: [PATCH 032/164] fix: use temp file in unit tests (#5106) --- .../sagemaker/remote_function/test_job.py | 339 +++++++++--------- 1 file changed, 166 insertions(+), 173 deletions(-) diff --git a/tests/unit/sagemaker/remote_function/test_job.py b/tests/unit/sagemaker/remote_function/test_job.py index 5be84fe5ba..f153b5b2ca 100644 --- a/tests/unit/sagemaker/remote_function/test_job.py +++ b/tests/unit/sagemaker/remote_function/test_job.py @@ -15,6 +15,7 @@ import os import sys +import tempfile import pytest from mock import patch, Mock, ANY, mock_open from mock.mock import MagicMock @@ -256,8 +257,6 @@ "OutputDataConfig": {"S3OutputPath": "s3://sagemaker-123/image_uri/output"}, } -OUTPUT_FILE = os.path.join(os.path.dirname(__file__), "sm_training.env") - TEST_JOB_NAME = "my-job-name" TEST_PIPELINE_NAME = "my-pipeline" TEST_EXP_NAME = "my-exp-name" @@ -2115,37 +2114,36 @@ def test_set_env_single_node_cpu( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1"], - current_group_name="homogeneousCluster", - current_instance_type="ml.t3.xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.t3.xlarge", - hosts=["algo-1"], - ) - ], - network_interface_name="eth0", - ), - distribution=None, - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1"], + current_group_name="homogeneousCluster", + current_instance_type="ml.t3.xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.t3.xlarge", + hosts=["algo-1"], + ) + ], + network_interface_name="eth0", + ), + distribution=None, + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_CPU) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_CPU) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env @patch( @@ -2168,37 +2166,36 @@ def test_set_env_single_node_multi_gpu( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1"], - current_group_name="homogeneousCluster", - current_instance_type="ml.g5.12xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.g5.12xlarge", - hosts=["algo-1"], - ) - ], - network_interface_name="eth0", - ), - distribution="torchrun", - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1"], + current_group_name="homogeneousCluster", + current_instance_type="ml.g5.12xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.g5.12xlarge", + hosts=["algo-1"], + ) + ], + network_interface_name="eth0", + ), + distribution="torchrun", + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env @patch( @@ -2221,37 +2218,36 @@ def test_set_env_multi_node_multi_gpu( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1", "algo-2", "algo-3", "algo-4"], - current_group_name="homogeneousCluster", - current_instance_type="ml.g5.2xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.g5.2xlarge", - hosts=["algo-4", "algo-2", "algo-1", "algo-3"], - ) - ], - network_interface_name="eth0", - ), - distribution="torchrun", - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1", "algo-2", "algo-3", "algo-4"], + current_group_name="homogeneousCluster", + current_instance_type="ml.g5.2xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.g5.2xlarge", + hosts=["algo-4", "algo-2", "algo-1", "algo-3"], + ) + ], + network_interface_name="eth0", + ), + distribution="torchrun", + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines(EXPECTED_ENV_MULTI_NODE_MULTI_GPUS) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines(EXPECTED_ENV_MULTI_NODE_MULTI_GPUS) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env @patch( @@ -2274,37 +2270,36 @@ def test_set_env_single_node_multi_gpu_mpirun( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1"], - current_group_name="homogeneousCluster", - current_instance_type="ml.g5.12xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.g5.12xlarge", - hosts=["algo-1"], - ) - ], - network_interface_name="eth0", - ), - distribution="mpirun", - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1"], + current_group_name="homogeneousCluster", + current_instance_type="ml.g5.12xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.g5.12xlarge", + hosts=["algo-1"], + ) + ], + network_interface_name="eth0", + ), + distribution="mpirun", + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS_MPIRUN) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines(EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS_MPIRUN) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env @patch( @@ -2327,37 +2322,36 @@ def test_set_env_multi_node_multi_gpu_mpirun( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1", "algo-2", "algo-3", "algo-4"], - current_group_name="homogeneousCluster", - current_instance_type="ml.g5.2xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.g5.2xlarge", - hosts=["algo-4", "algo-2", "algo-1", "algo-3"], - ) - ], - network_interface_name="eth0", - ), - distribution="mpirun", - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1", "algo-2", "algo-3", "algo-4"], + current_group_name="homogeneousCluster", + current_instance_type="ml.g5.2xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.g5.2xlarge", + hosts=["algo-4", "algo-2", "algo-1", "algo-3"], + ) + ], + network_interface_name="eth0", + ), + distribution="mpirun", + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines(EXPECTED_ENV_MULTI_NODE_MULTI_GPUS_MPIRUN) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines(EXPECTED_ENV_MULTI_NODE_MULTI_GPUS_MPIRUN) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env @patch("sagemaker.experiments._run_context._RunContext.get_current_run", new=mock_get_current_run) @@ -2644,40 +2638,39 @@ def test_set_env_single_node_multi_gpu_mpirun_with_nproc_per_node( mock_safe_serialize, mock_num_cpus, mock_num_gpus, mock_num_neurons ): with patch.dict(os.environ, {"TRAINING_JOB_NAME": "test-job"}): - set_env( - resource_config=dict( - current_host="algo-1", - hosts=["algo-1"], - current_group_name="homogeneousCluster", - current_instance_type="ml.g5.12xlarge", - instance_groups=[ - dict( - instance_group_name="homogeneousCluster", - instance_type="ml.g5.12xlarge", - hosts=["algo-1"], - ) - ], - network_interface_name="eth0", - ), - distribution="mpirun", - user_nproc_per_node=2, - output_file=OUTPUT_FILE, - ) + with tempfile.NamedTemporaryFile() as f: + set_env( + resource_config=dict( + current_host="algo-1", + hosts=["algo-1"], + current_group_name="homogeneousCluster", + current_instance_type="ml.g5.12xlarge", + instance_groups=[ + dict( + instance_group_name="homogeneousCluster", + instance_type="ml.g5.12xlarge", + hosts=["algo-1"], + ) + ], + network_interface_name="eth0", + ), + distribution="mpirun", + user_nproc_per_node=2, + output_file=f.name, + ) - mock_num_cpus.assert_called_once() - mock_num_gpus.assert_called_once() - mock_num_neurons.assert_called_once() + mock_num_cpus.assert_called_once() + mock_num_gpus.assert_called_once() + mock_num_neurons.assert_called_once() - with open(OUTPUT_FILE, "r") as f: - env_file = f.read().strip() - expected_env = _remove_extra_lines( - EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS_MPIRUN_WITH_NPROC_PER_NODE - ) - env_file = _remove_extra_lines(env_file) + with open(f.name, "r") as f: + env_file = f.read().strip() + expected_env = _remove_extra_lines( + EXPECTED_ENV_SINGLE_NODE_MULTI_GPUS_MPIRUN_WITH_NPROC_PER_NODE + ) + env_file = _remove_extra_lines(env_file) - assert env_file == expected_env - os.remove(OUTPUT_FILE) - assert not os.path.exists(OUTPUT_FILE) + assert env_file == expected_env def _remove_extra_lines(string): From 6b7f0c59bafcb3adc54d6ad01db61647449c21dd Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Thu, 27 Mar 2025 09:35:35 -0700 Subject: [PATCH 033/164] fix: fix flaky spark processor integ (#5109) * fix: fix flaky spark processor integ * format --- tests/integ/test_spark_processing.py | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/tests/integ/test_spark_processing.py b/tests/integ/test_spark_processing.py index 25a4942d70..eeba205b3b 100644 --- a/tests/integ/test_spark_processing.py +++ b/tests/integ/test_spark_processing.py @@ -35,7 +35,7 @@ SPARK_PATH = os.path.join(DATA_DIR, "spark") -@pytest.fixture(scope="module") +@pytest.fixture(scope="module", autouse=True) def build_jar(): jar_file_path = os.path.join(SPARK_PATH, "code", "java", "hello-java-spark") # compile java file @@ -207,12 +207,10 @@ def configuration() -> list: def test_sagemaker_pyspark_v3( - spark_v3_py_processor, spark_v3_jar_processor, sagemaker_session, configuration, build_jar + spark_v3_py_processor, spark_v3_jar_processor, sagemaker_session, configuration ): test_sagemaker_pyspark_multinode(spark_v3_py_processor, sagemaker_session, configuration) - test_sagemaker_java_jar_multinode( - spark_v3_jar_processor, sagemaker_session, configuration, build_jar - ) + test_sagemaker_java_jar_multinode(spark_v3_jar_processor, sagemaker_session, configuration) def test_sagemaker_pyspark_multinode(spark_py_processor, sagemaker_session, configuration): @@ -280,9 +278,7 @@ def test_sagemaker_pyspark_multinode(spark_py_processor, sagemaker_session, conf assert len(output_contents) != 0 -def test_sagemaker_java_jar_multinode( - spark_jar_processor, sagemaker_session, configuration, build_jar -): +def test_sagemaker_java_jar_multinode(spark_jar_processor, sagemaker_session, configuration): """Test SparkJarProcessor using Java application jar""" bucket = spark_jar_processor.sagemaker_session.default_bucket() with open(os.path.join(SPARK_PATH, "files", "data.jsonl")) as data: From e6b498c366cbfc31d829ed02cbd597ac9421904f Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Thu, 27 Mar 2025 09:35:56 -0700 Subject: [PATCH 034/164] fix: fix flaky clarify model monitor test (#5107) --- tests/unit/sagemaker/monitor/test_clarify_model_monitor.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py index 53119e532a..026e1a2d54 100644 --- a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py +++ b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py @@ -568,11 +568,12 @@ def test_clarify_model_monitor(): # The subclass should has monitoring_type() defined # noinspection PyAbstractClass - class DummyClarifyModelMonitoir(ClarifyModelMonitor): + class DummyClarifyModelMonitor(ClarifyModelMonitor): + _TEST_CLASS = True pass with pytest.raises(TypeError): - DummyClarifyModelMonitoir.monitoring_type() + DummyClarifyModelMonitor.monitoring_type() def test_clarify_model_monitor_invalid_update(clarify_model_monitors): @@ -593,6 +594,8 @@ def test_clarify_model_monitor_invalid_attach(sagemaker_session): ) # attach, invalid monitoring type for clarify_model_monitor_cls in ClarifyModelMonitor.__subclasses__(): + if hasattr(clarify_model_monitor_cls, "_TEST_CLASS"): + continue with pytest.raises(TypeError): clarify_model_monitor_cls.attach(SCHEDULE_NAME, sagemaker_session) From 8ead59a1ec876d08ac66dccd085dbd42907852e2 Mon Sep 17 00:00:00 2001 From: evakravi <69981223+evakravi@users.noreply.github.com> Date: Thu, 27 Mar 2025 15:49:45 -0400 Subject: [PATCH 035/164] chore: move jumpstart region definitions to json file (#5095) * chore: move jumpstart region definitions to json file * chore: address formatting issues * fix: neo regions not ga in 5 regions * chore: make variable private --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> --- src/sagemaker/jumpstart/constants.py | 272 ++++--------------- src/sagemaker/jumpstart/region_config.json | 163 +++++++++++ tests/unit/sagemaker/jumpstart/test_utils.py | 111 +++++++- 3 files changed, 321 insertions(+), 225 deletions(-) create mode 100644 src/sagemaker/jumpstart/region_config.json diff --git a/src/sagemaker/jumpstart/constants.py b/src/sagemaker/jumpstart/constants.py index dd4ded4748..b81f97ce3a 100644 --- a/src/sagemaker/jumpstart/constants.py +++ b/src/sagemaker/jumpstart/constants.py @@ -15,6 +15,7 @@ import logging import os from typing import Dict, Set, Type +import json import boto3 from sagemaker.base_deserializers import BaseDeserializer, JSONDeserializer from sagemaker.jumpstart.enums import ( @@ -35,214 +36,58 @@ from sagemaker.session import Session +JUMPSTART_LOGGER = logging.getLogger("sagemaker.jumpstart") + +# disable logging if env var is set +JUMPSTART_LOGGER.addHandler( + type( + "", + (logging.StreamHandler,), + { + "emit": lambda self, *args, **kwargs: ( + logging.StreamHandler.emit(self, *args, **kwargs) + if not os.environ.get(ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING) + else None + ) + }, + )() +) + + +_CURRENT_FILE_DIRECTORY_PATH = os.path.dirname(os.path.realpath(__file__)) +REGION_CONFIG_JSON_FILENAME = "region_config.json" +REGION_CONFIG_JSON_FILEPATH = os.path.join( + _CURRENT_FILE_DIRECTORY_PATH, REGION_CONFIG_JSON_FILENAME +) + + +def _load_region_config(filepath: str) -> Set[JumpStartLaunchedRegionInfo]: + """Load the JumpStart region config from a JSON file.""" + debug_msg = f"Loading JumpStart region config from '{filepath}'." + JUMPSTART_LOGGER.debug(debug_msg) + try: + with open(filepath) as f: + config = json.load(f) + + return { + JumpStartLaunchedRegionInfo( + region_name=region, + content_bucket=data["content_bucket"], + gated_content_bucket=data.get("gated_content_bucket"), + neo_content_bucket=data.get("neo_content_bucket"), + ) + for region, data in config.items() + } + except Exception: # pylint: disable=W0703 + JUMPSTART_LOGGER.error("Unable to load JumpStart region config.", exc_info=True) + return set() + + ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING = "DISABLE_JUMPSTART_LOGGING" ENV_VARIABLE_DISABLE_JUMPSTART_TELEMETRY = "DISABLE_JUMPSTART_TELEMETRY" -JUMPSTART_LAUNCHED_REGIONS: Set[JumpStartLaunchedRegionInfo] = set( - [ - JumpStartLaunchedRegionInfo( - region_name="us-west-2", - content_bucket="jumpstart-cache-prod-us-west-2", - gated_content_bucket="jumpstart-private-cache-prod-us-west-2", - neo_content_bucket="sagemaker-sd-models-prod-us-west-2", - ), - JumpStartLaunchedRegionInfo( - region_name="us-east-1", - content_bucket="jumpstart-cache-prod-us-east-1", - gated_content_bucket="jumpstart-private-cache-prod-us-east-1", - neo_content_bucket="sagemaker-sd-models-prod-us-east-1", - ), - JumpStartLaunchedRegionInfo( - region_name="us-east-2", - content_bucket="jumpstart-cache-prod-us-east-2", - gated_content_bucket="jumpstart-private-cache-prod-us-east-2", - neo_content_bucket="sagemaker-sd-models-prod-us-east-2", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-west-1", - content_bucket="jumpstart-cache-prod-eu-west-1", - gated_content_bucket="jumpstart-private-cache-prod-eu-west-1", - neo_content_bucket="sagemaker-sd-models-prod-eu-west-1", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-central-1", - content_bucket="jumpstart-cache-prod-eu-central-1", - gated_content_bucket="jumpstart-private-cache-prod-eu-central-1", - neo_content_bucket="sagemaker-sd-models-prod-eu-central-1", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-central-2", - content_bucket="jumpstart-cache-prod-eu-central-2", - gated_content_bucket="jumpstart-private-cache-prod-eu-central-2", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-north-1", - content_bucket="jumpstart-cache-prod-eu-north-1", - gated_content_bucket="jumpstart-private-cache-prod-eu-north-1", - neo_content_bucket="sagemaker-sd-models-prod-eu-north-1", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-south-2", - content_bucket="jumpstart-cache-prod-eu-south-2", - gated_content_bucket="jumpstart-private-cache-prod-eu-south-2", - neo_content_bucket="sagemaker-sd-models-prod-eu-south-2", - ), - JumpStartLaunchedRegionInfo( - region_name="me-south-1", - content_bucket="jumpstart-cache-prod-me-south-1", - gated_content_bucket="jumpstart-private-cache-prod-me-south-1", - ), - JumpStartLaunchedRegionInfo( - region_name="me-central-1", - content_bucket="jumpstart-cache-prod-me-central-1", - gated_content_bucket="jumpstart-private-cache-prod-me-central-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-south-1", - content_bucket="jumpstart-cache-prod-ap-south-1", - gated_content_bucket="jumpstart-private-cache-prod-ap-south-1", - neo_content_bucket="sagemaker-sd-models-prod-ap-south-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-south-2", - content_bucket="jumpstart-cache-prod-ap-south-2", - gated_content_bucket="jumpstart-private-cache-prod-ap-south-2", - neo_content_bucket="sagemaker-sd-models-prod-ap-south-2", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-west-3", - content_bucket="jumpstart-cache-prod-eu-west-3", - gated_content_bucket="jumpstart-private-cache-prod-eu-west-3", - neo_content_bucket="sagemaker-sd-models-prod-eu-west-3", - ), - JumpStartLaunchedRegionInfo( - region_name="af-south-1", - content_bucket="jumpstart-cache-prod-af-south-1", - gated_content_bucket="jumpstart-private-cache-prod-af-south-1", - ), - JumpStartLaunchedRegionInfo( - region_name="sa-east-1", - content_bucket="jumpstart-cache-prod-sa-east-1", - gated_content_bucket="jumpstart-private-cache-prod-sa-east-1", - neo_content_bucket="sagemaker-sd-models-prod-sa-east-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-east-1", - content_bucket="jumpstart-cache-prod-ap-east-1", - gated_content_bucket="jumpstart-private-cache-prod-ap-east-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-northeast-2", - content_bucket="jumpstart-cache-prod-ap-northeast-2", - gated_content_bucket="jumpstart-private-cache-prod-ap-northeast-2", - neo_content_bucket="sagemaker-sd-models-prod-ap-northeast-2", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-northeast-3", - content_bucket="jumpstart-cache-prod-ap-northeast-3", - gated_content_bucket="jumpstart-private-cache-prod-ap-northeast-3", - neo_content_bucket="sagemaker-sd-models-prod-ap-northeast-3", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-3", - content_bucket="jumpstart-cache-prod-ap-southeast-3", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-3", - neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-3", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-4", - content_bucket="jumpstart-cache-prod-ap-southeast-4", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-4", - neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-4", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-5", - content_bucket="jumpstart-cache-prod-ap-southeast-5", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-5", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-7", - content_bucket="jumpstart-cache-prod-ap-southeast-7", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-7", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-west-2", - content_bucket="jumpstart-cache-prod-eu-west-2", - gated_content_bucket="jumpstart-private-cache-prod-eu-west-2", - neo_content_bucket="sagemaker-sd-models-prod-eu-west-2", - ), - JumpStartLaunchedRegionInfo( - region_name="eu-south-1", - content_bucket="jumpstart-cache-prod-eu-south-1", - gated_content_bucket="jumpstart-private-cache-prod-eu-south-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-northeast-1", - content_bucket="jumpstart-cache-prod-ap-northeast-1", - gated_content_bucket="jumpstart-private-cache-prod-ap-northeast-1", - neo_content_bucket="sagemaker-sd-models-prod-ap-northeast-1", - ), - JumpStartLaunchedRegionInfo( - region_name="us-west-1", - content_bucket="jumpstart-cache-prod-us-west-1", - gated_content_bucket="jumpstart-private-cache-prod-us-west-1", - neo_content_bucket="sagemaker-sd-models-prod-us-west-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-1", - content_bucket="jumpstart-cache-prod-ap-southeast-1", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-1", - neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ap-southeast-2", - content_bucket="jumpstart-cache-prod-ap-southeast-2", - gated_content_bucket="jumpstart-private-cache-prod-ap-southeast-2", - neo_content_bucket="sagemaker-sd-models-prod-ap-southeast-2", - ), - JumpStartLaunchedRegionInfo( - region_name="ca-central-1", - content_bucket="jumpstart-cache-prod-ca-central-1", - gated_content_bucket="jumpstart-private-cache-prod-ca-central-1", - neo_content_bucket="sagemaker-sd-models-prod-ca-central-1", - ), - JumpStartLaunchedRegionInfo( - region_name="ca-west-1", - content_bucket="jumpstart-cache-prod-ca-west-1", - gated_content_bucket="jumpstart-private-cache-prod-ca-west-1", - neo_content_bucket="sagemaker-sd-models-prod-ca-west-1", - ), - JumpStartLaunchedRegionInfo( - region_name="cn-north-1", - content_bucket="jumpstart-cache-prod-cn-north-1", - gated_content_bucket="jumpstart-private-cache-prod-cn-north-1", - ), - JumpStartLaunchedRegionInfo( - region_name="cn-northwest-1", - content_bucket="jumpstart-cache-prod-cn-northwest-1", - gated_content_bucket="jumpstart-private-cache-prod-cn-northwest-1", - ), - JumpStartLaunchedRegionInfo( - region_name="il-central-1", - content_bucket="jumpstart-cache-prod-il-central-1", - gated_content_bucket="jumpstart-private-cache-prod-il-central-1", - ), - JumpStartLaunchedRegionInfo( - region_name="mx-central-1", - content_bucket="jumpstart-cache-prod-mx-central-1", - gated_content_bucket="jumpstart-private-cache-prod-mx-central-1", - ), - JumpStartLaunchedRegionInfo( - region_name="us-gov-east-1", - content_bucket="jumpstart-cache-prod-us-gov-east-1", - gated_content_bucket="jumpstart-private-cache-prod-us-gov-east-1", - ), - JumpStartLaunchedRegionInfo( - region_name="us-gov-west-1", - content_bucket="jumpstart-cache-prod-us-gov-west-1", - gated_content_bucket="jumpstart-private-cache-prod-us-gov-west-1", - ), - ] +JUMPSTART_LAUNCHED_REGIONS: Set[JumpStartLaunchedRegionInfo] = _load_region_config( + REGION_CONFIG_JSON_FILEPATH ) JUMPSTART_REGION_NAME_TO_LAUNCHED_REGION_DICT = { @@ -331,23 +176,6 @@ MODEL_ID_LIST_WEB_URL = "https://sagemaker.readthedocs.io/en/stable/doc_utils/pretrainedmodels.html" -JUMPSTART_LOGGER = logging.getLogger("sagemaker.jumpstart") - -# disable logging if env var is set -JUMPSTART_LOGGER.addHandler( - type( - "", - (logging.StreamHandler,), - { - "emit": lambda self, *args, **kwargs: ( - logging.StreamHandler.emit(self, *args, **kwargs) - if not os.environ.get(ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING) - else None - ) - }, - )() -) - try: DEFAULT_JUMPSTART_SAGEMAKER_SESSION = Session( boto3.Session(region_name=JUMPSTART_DEFAULT_REGION_NAME) diff --git a/src/sagemaker/jumpstart/region_config.json b/src/sagemaker/jumpstart/region_config.json new file mode 100644 index 0000000000..30bea6ee70 --- /dev/null +++ b/src/sagemaker/jumpstart/region_config.json @@ -0,0 +1,163 @@ +{ + "af-south-1": { + "content_bucket": "jumpstart-cache-prod-af-south-1", + "gated_content_bucket": "jumpstart-private-cache-prod-af-south-1" + }, + "ap-east-1": { + "content_bucket": "jumpstart-cache-prod-ap-east-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-1" + }, + "ap-northeast-1": { + "content_bucket": "jumpstart-cache-prod-ap-northeast-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-1", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-northeast-1" + }, + "ap-northeast-2": { + "content_bucket": "jumpstart-cache-prod-ap-northeast-2", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-2", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-northeast-2" + }, + "ap-northeast-3": { + "content_bucket": "jumpstart-cache-prod-ap-northeast-3", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-3", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-northeast-3" + }, + "ap-south-1": { + "content_bucket": "jumpstart-cache-prod-ap-south-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-south-1", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-south-1" + }, + "ap-south-2": { + "content_bucket": "jumpstart-cache-prod-ap-south-2", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-south-2" + }, + "ap-southeast-1": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-1", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-southeast-1" + }, + "ap-southeast-2": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-2", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-2", + "neo_content_bucket": "sagemaker-sd-models-prod-ap-southeast-2" + }, + "ap-southeast-3": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-3", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-3" + }, + "ap-southeast-4": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-4", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-4" + }, + "ap-southeast-5": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-5", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-5" + }, + "ap-southeast-7": { + "content_bucket": "jumpstart-cache-prod-ap-southeast-7", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-southeast-7" + }, + "ca-central-1": { + "content_bucket": "jumpstart-cache-prod-ca-central-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ca-central-1", + "neo_content_bucket": "sagemaker-sd-models-prod-ca-central-1" + }, + "ca-west-1": { + "content_bucket": "jumpstart-cache-prod-ca-west-1", + "gated_content_bucket": "jumpstart-private-cache-prod-ca-west-1" + }, + "cn-north-1": { + "content_bucket": "jumpstart-cache-prod-cn-north-1", + "gated_content_bucket": "jumpstart-private-cache-prod-cn-north-1" + }, + "cn-northwest-1": { + "content_bucket": "jumpstart-cache-prod-cn-northwest-1", + "gated_content_bucket": "jumpstart-private-cache-prod-cn-northwest-1" + }, + "eu-central-1": { + "content_bucket": "jumpstart-cache-prod-eu-central-1", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-central-1", + "neo_content_bucket": "sagemaker-sd-models-prod-eu-central-1" + }, + "eu-central-2": { + "content_bucket": "jumpstart-cache-prod-eu-central-2", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-central-2" + }, + "eu-north-1": { + "content_bucket": "jumpstart-cache-prod-eu-north-1", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-north-1", + "neo_content_bucket": "sagemaker-sd-models-prod-eu-north-1" + }, + "eu-south-1": { + "content_bucket": "jumpstart-cache-prod-eu-south-1", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-south-1" + }, + "eu-south-2": { + "content_bucket": "jumpstart-cache-prod-eu-south-2", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-south-2" + }, + "eu-west-1": { + "content_bucket": "jumpstart-cache-prod-eu-west-1", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-west-1", + "neo_content_bucket": "sagemaker-sd-models-prod-eu-west-1" + }, + "eu-west-2": { + "content_bucket": "jumpstart-cache-prod-eu-west-2", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-west-2", + "neo_content_bucket": "sagemaker-sd-models-prod-eu-west-2" + }, + "eu-west-3": { + "content_bucket": "jumpstart-cache-prod-eu-west-3", + "gated_content_bucket": "jumpstart-private-cache-prod-eu-west-3", + "neo_content_bucket": "sagemaker-sd-models-prod-eu-west-3" + }, + "il-central-1": { + "content_bucket": "jumpstart-cache-prod-il-central-1", + "gated_content_bucket": "jumpstart-private-cache-prod-il-central-1" + }, + "me-central-1": { + "content_bucket": "jumpstart-cache-prod-me-central-1", + "gated_content_bucket": "jumpstart-private-cache-prod-me-central-1" + }, + "me-south-1": { + "content_bucket": "jumpstart-cache-prod-me-south-1", + "gated_content_bucket": "jumpstart-private-cache-prod-me-south-1" + }, + "mx-central-1": { + "content_bucket": "jumpstart-cache-prod-mx-central-1", + "gated_content_bucket": "jumpstart-private-cache-prod-mx-central-1" + }, + "sa-east-1": { + "content_bucket": "jumpstart-cache-prod-sa-east-1", + "gated_content_bucket": "jumpstart-private-cache-prod-sa-east-1", + "neo_content_bucket": "sagemaker-sd-models-prod-sa-east-1" + }, + "us-east-1": { + "content_bucket": "jumpstart-cache-prod-us-east-1", + "gated_content_bucket": "jumpstart-private-cache-prod-us-east-1", + "neo_content_bucket": "sagemaker-sd-models-prod-us-east-1" + }, + "us-east-2": { + "content_bucket": "jumpstart-cache-prod-us-east-2", + "gated_content_bucket": "jumpstart-private-cache-prod-us-east-2", + "neo_content_bucket": "sagemaker-sd-models-prod-us-east-2" + }, + "us-gov-east-1": { + "content_bucket": "jumpstart-cache-prod-us-gov-east-1", + "gated_content_bucket": "jumpstart-private-cache-prod-us-gov-east-1" + }, + "us-gov-west-1": { + "content_bucket": "jumpstart-cache-prod-us-gov-west-1", + "gated_content_bucket": "jumpstart-private-cache-prod-us-gov-west-1" + }, + "us-west-1": { + "content_bucket": "jumpstart-cache-prod-us-west-1", + "gated_content_bucket": "jumpstart-private-cache-prod-us-west-1", + "neo_content_bucket": "sagemaker-sd-models-prod-us-west-1" + }, + "us-west-2": { + "content_bucket": "jumpstart-cache-prod-us-west-2", + "gated_content_bucket": "jumpstart-private-cache-prod-us-west-2", + "neo_content_bucket": "sagemaker-sd-models-prod-us-west-2" + } +} \ No newline at end of file diff --git a/tests/unit/sagemaker/jumpstart/test_utils.py b/tests/unit/sagemaker/jumpstart/test_utils.py index ea4d64f289..e3e3110da8 100644 --- a/tests/unit/sagemaker/jumpstart/test_utils.py +++ b/tests/unit/sagemaker/jumpstart/test_utils.py @@ -13,10 +13,9 @@ from __future__ import absolute_import import os from unittest import TestCase -from unittest.mock import call - +from unittest.mock import call, mock_open, Mock, patch +import json from botocore.exceptions import ClientError -from mock.mock import Mock, patch import pytest import boto3 import random @@ -24,6 +23,7 @@ from sagemaker import session from sagemaker.jumpstart import utils from sagemaker.jumpstart.constants import ( + _load_region_config, DEFAULT_JUMPSTART_SAGEMAKER_SESSION, ENV_VARIABLE_DISABLE_JUMPSTART_LOGGING, ENV_VARIABLE_JUMPSTART_CONTENT_BUCKET_OVERRIDE, @@ -38,6 +38,7 @@ JUMPSTART_RESOURCE_BASE_NAME, NEO_DEFAULT_REGION_NAME, JumpStartScriptScope, + JUMPSTART_LAUNCHED_REGIONS, ) from functools import partial from sagemaker.jumpstart.enums import JumpStartTag, MIMEType, JumpStartModelType @@ -49,6 +50,7 @@ JumpStartBenchmarkStat, JumpStartModelHeader, JumpStartVersionedModelId, + JumpStartLaunchedRegionInfo, ) from tests.unit.sagemaker.jumpstart.utils import ( get_base_spec_with_prototype_configs, @@ -1569,6 +1571,109 @@ def test_multiple_config_names_found_aliases_inconsistent(self): mock_list_tags.assert_called_once_with("some-arn") +class TestJumpStartLaunchedRegions(TestCase): + def test_regions_not_empty(self): + self.assertTrue(len(JUMPSTART_LAUNCHED_REGIONS) > 0) + + +class TestLoadRegionConfig(TestCase): + def setUp(self): + # Sample valid config that matches the expected structure + self.valid_config = { + "us-east-1": { + "content_bucket": "jumpstart-cache-prod-us-east-1", + "gated_content_bucket": "jumpstart-private-cache-prod-us-east-1", + "neo_content_bucket": "jumpstart-neo-cache-prod-us-east-1", + }, + "us-west-2": { + "content_bucket": "jumpstart-cache-prod-us-west-2", + }, + } + self.config_json = json.dumps(self.valid_config) + + @patch("builtins.open", new_callable=mock_open) + def test_successful_config_load(self, mock_file): + # Setup mock to return valid config + mock_file.return_value.__enter__().read.return_value = self.config_json + + result = _load_region_config("dummy/path") + + # Verify the returned dictionary contains JumpStartLaunchedRegionInfo objects + self.assertTrue(all(isinstance(region, JumpStartLaunchedRegionInfo) for region in result)) + + for region in result: + if region.region_name == "us-east-1": + self.assertEqual(region.region_name, "us-east-1") + self.assertEqual(region.content_bucket, "jumpstart-cache-prod-us-east-1") + self.assertEqual( + region.gated_content_bucket, "jumpstart-private-cache-prod-us-east-1" + ) + self.assertEqual(region.neo_content_bucket, "jumpstart-neo-cache-prod-us-east-1") + + elif region.region_name == "us-west-2": + self.assertEqual(region.region_name, "us-west-2") + self.assertEqual(region.content_bucket, "jumpstart-cache-prod-us-west-2") + self.assertIsNone(region.gated_content_bucket) + self.assertIsNone(region.neo_content_bucket) + else: + raise AssertionError(f"Unexpected region name found: {region.region_name}") + + @patch("builtins.open", new_callable=mock_open) + def test_missing_required_field(self, mock_file): + # Config missing required content_bucket field + invalid_config = { + "us-east-1": { + "gated_content_bucket": "XXXXXXXXXXX", + "neo_content_bucket": "some-other-bucket", + } + } + mock_file.return_value.__enter__().read.return_value = json.dumps(invalid_config) + + # Should return empty dict due to exception handling + result = _load_region_config("dummy/path") + self.assertEqual(result, set()) + + @patch("builtins.open") + def test_file_not_found(self, mock_file): + # Simulate file not found + mock_file.side_effect = FileNotFoundError() + + # Should return empty dict due to exception handling + result = _load_region_config("dummy/path") + self.assertEqual(result, set()) + + @patch("builtins.open", new_callable=mock_open) + def test_invalid_json(self, mock_file): + # Setup mock to return invalid JSON + mock_file.return_value.__enter__().read.return_value = "invalid json content" + + # Should return empty dict due to exception handling + result = _load_region_config("dummy/path") + self.assertEqual(result, set()) + + @patch("builtins.open", new_callable=mock_open) + def test_empty_config(self, mock_file): + # Setup mock to return empty JSON object + mock_file.return_value.__enter__().read.return_value = "{}" + + result = _load_region_config("dummy/path") + self.assertEqual(result, set()) + + @patch("sagemaker.jumpstart.constants.JUMPSTART_LOGGER") + @patch("builtins.open") + def test_logging_on_error(self, mock_file, mock_logger): + + # Simulate an error + mock_file.side_effect = Exception("Test error") + + result = _load_region_config("dummy/path") + + self.assertEqual(result, set()) + + # Verify error was logged + mock_logger.error.assert_called_once() + + class TestJumpStartLogger(TestCase): @patch.dict("os.environ", {}) @patch("logging.StreamHandler.emit") From fac9571e958cf501f2e5bf8d2e216ad60062e9a1 Mon Sep 17 00:00:00 2001 From: Victor Zhu Date: Thu, 27 Mar 2025 12:56:34 -0700 Subject: [PATCH 036/164] change: Update for PT 2.5.1, SMP 2.8.0 (#5071) --- src/sagemaker/fw_utils.py | 1 + .../image_uri_config/pytorch-smp.json | 28 ++++++++++++++++++- src/sagemaker/image_uris.py | 16 +++++++---- .../unit/sagemaker/image_uris/test_smp_v2.py | 15 ++++++---- 4 files changed, 47 insertions(+), 13 deletions(-) diff --git a/src/sagemaker/fw_utils.py b/src/sagemaker/fw_utils.py index 0e4e582261..234f0c61fa 100644 --- a/src/sagemaker/fw_utils.py +++ b/src/sagemaker/fw_utils.py @@ -155,6 +155,7 @@ "2.3.0", "2.3.1", "2.4.1", + "2.5.1", ] TRAINIUM_SUPPORTED_DISTRIBUTION_STRATEGIES = ["torch_distributed"] diff --git a/src/sagemaker/image_uri_config/pytorch-smp.json b/src/sagemaker/image_uri_config/pytorch-smp.json index 449726927a..53c2a75e13 100644 --- a/src/sagemaker/image_uri_config/pytorch-smp.json +++ b/src/sagemaker/image_uri_config/pytorch-smp.json @@ -9,7 +9,8 @@ "2.2": "2.3.1", "2.2.0": "2.3.1", "2.3.1": "2.5.0", - "2.4.1": "2.7.0" + "2.4.1": "2.7.0", + "2.5.1": "2.8.0" }, "versions": { "2.0.1": { @@ -186,6 +187,31 @@ "us-west-2": "658645717510" }, "repository": "smdistributed-modelparallel" + }, + "2.8.0": { + "py_versions": [ + "py311" + ], + "registries": { + "ap-northeast-1": "658645717510", + "ap-northeast-2": "658645717510", + "ap-northeast-3": "658645717510", + "ap-south-1": "658645717510", + "ap-southeast-1": "658645717510", + "ap-southeast-2": "658645717510", + "ca-central-1": "658645717510", + "eu-central-1": "658645717510", + "eu-north-1": "658645717510", + "eu-west-1": "658645717510", + "eu-west-2": "658645717510", + "eu-west-3": "658645717510", + "sa-east-1": "658645717510", + "us-east-1": "658645717510", + "us-east-2": "658645717510", + "us-west-1": "658645717510", + "us-west-2": "658645717510" + }, + "repository": "smdistributed-modelparallel" } } } diff --git a/src/sagemaker/image_uris.py b/src/sagemaker/image_uris.py index 7d277cd854..de6d622f78 100644 --- a/src/sagemaker/image_uris.py +++ b/src/sagemaker/image_uris.py @@ -701,12 +701,16 @@ def get_training_image_uri( if "modelparallel" in distribution["smdistributed"]: if distribution["smdistributed"]["modelparallel"].get("enabled", True): framework = "pytorch-smp" - if ( - "p5" in instance_type - or "2.1" in framework_version - or "2.2" in framework_version - or "2.3" in framework_version - or "2.4" in framework_version + supported_smp_pt_versions_cu124 = ("2.5",) + supported_smp_pt_versions_cu121 = ("2.1", "2.2", "2.3", "2.4") + if any( + pt_version in framework_version + for pt_version in supported_smp_pt_versions_cu124 + ): + container_version = "cu124" + elif "p5" in instance_type or any( + pt_version in framework_version + for pt_version in supported_smp_pt_versions_cu121 ): container_version = "cu121" else: diff --git a/tests/unit/sagemaker/image_uris/test_smp_v2.py b/tests/unit/sagemaker/image_uris/test_smp_v2.py index b1297822f7..3177384e7e 100644 --- a/tests/unit/sagemaker/image_uris/test_smp_v2.py +++ b/tests/unit/sagemaker/image_uris/test_smp_v2.py @@ -36,15 +36,18 @@ def test_smp_v2(load_config): for region in ACCOUNTS.keys(): for instance_type in CONTAINER_VERSIONS.keys(): cuda_vers = CONTAINER_VERSIONS[instance_type] - if ( - "2.1" in version - or "2.2" in version - or "2.3" in version - or "2.4" in version + supported_smp_pt_versions_cu124 = ("2.5",) + supported_smp_pt_versions_cu121 = ("2.1", "2.2", "2.3", "2.4") + if any( + pt_version in version for pt_version in supported_smp_pt_versions_cu124 + ): + cuda_vers = "cu124" + elif any( + pt_version in version for pt_version in supported_smp_pt_versions_cu121 ): cuda_vers = "cu121" - if "2.3.1" == version or "2.4.1" == version: + if version in ("2.3.1", "2.4.1", "2.5.1"): py_version = "py311" uri = image_uris.get_training_image_uri( From b65d9a5139d66af8a11078e29e2897fd07261431 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 27 Mar 2025 22:48:58 +0000 Subject: [PATCH 037/164] prepare release v2.243.0 --- CHANGELOG.md | 25 +++++++++++++++++++++++++ VERSION | 2 +- 2 files changed, 26 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index df1d902c22..a22635a580 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,30 @@ # Changelog +## v2.243.0 (2025-03-27) + +### Features + + * Enabled update_endpoint through model_builder + +### Bug Fixes and Other Changes + + * Update for PT 2.5.1, SMP 2.8.0 + * chore: move jumpstart region definitions to json file + * fix flaky clarify model monitor test + * fix flaky spark processor integ + * use temp file in unit tests + * Update transformers version + * Aligned disable_output_compression for @remote with Estimator + * Update Jinja version + * update image_uri_configs 03-26-2025 07:18:16 PST + * chore: fix integ tests to use latest version of model + * update image_uri_configs 03-25-2025 07:18:13 PST + * Skip tests failed due to deprecated instance type + * update image_uri_configs 03-21-2025 07:17:55 PST + * factor in set instance type when building JumpStart models in ModelBuilder. + * ADD Documentation to ReadtheDocs for Upgrading torch versions + * add new regions to JUMPSTART_LAUNCHED_REGIONS + ## v2.242.0 (2025-03-14) ### Features diff --git a/VERSION b/VERSION index 819d69a27e..40cf5c98bb 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.242.1.dev0 +2.243.0 From 645f6694970868b20da00f6c464621c6461de423 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 27 Mar 2025 22:49:03 +0000 Subject: [PATCH 038/164] update development version to v2.243.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 40cf5c98bb..7fbcc66779 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.0 +2.243.1.dev0 From 230fb5591a84028c64635b99af0b2a5fcf6e54c6 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Thu, 27 Mar 2025 18:37:49 -0700 Subject: [PATCH 039/164] fix: flaky test (#5111) --- tests/integ/test_spark_processing.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/tests/integ/test_spark_processing.py b/tests/integ/test_spark_processing.py index eeba205b3b..ac956be94e 100644 --- a/tests/integ/test_spark_processing.py +++ b/tests/integ/test_spark_processing.py @@ -69,9 +69,6 @@ def build_jar(): ".", ] ) - yield - subprocess.run(["rm", os.path.join(jar_file_path, "hello-spark-java.jar")]) - subprocess.run(["rm", os.path.join(jar_file_path, JAVA_FILE_PATH, "HelloJavaSparkApp.class")]) @pytest.fixture(scope="module") From 305bdf88994b8f8f61388ee1dadf7b55e76ad315 Mon Sep 17 00:00:00 2001 From: Rohan Narayan Date: Mon, 31 Mar 2025 22:28:20 -0400 Subject: [PATCH 040/164] chore: fix semantic versioning for wildcard identifier (#5105) --- src/sagemaker/jumpstart/cache.py | 6 +++++ tests/unit/sagemaker/jumpstart/constants.py | 12 ++++++++++ tests/unit/sagemaker/jumpstart/test_cache.py | 24 ++++++++++++++++++++ 3 files changed, 42 insertions(+) diff --git a/src/sagemaker/jumpstart/cache.py b/src/sagemaker/jumpstart/cache.py index f862d4702a..29a903e00b 100644 --- a/src/sagemaker/jumpstart/cache.py +++ b/src/sagemaker/jumpstart/cache.py @@ -552,6 +552,12 @@ def _select_version( ) return version_str if version_str in available_versions else None + if version_str[-1] == "*": + # major or minor version is pinned, e.g 1.* or 1.0.* + return utils.get_latest_version( + [version for version in available_versions if version.startswith(version_str[:-1])] + ) + try: spec = SpecifierSet(f"=={version_str}") except InvalidSpecifier: diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py index 83e8a44a32..2eb7469e21 100644 --- a/tests/unit/sagemaker/jumpstart/constants.py +++ b/tests/unit/sagemaker/jumpstart/constants.py @@ -15990,6 +15990,18 @@ "spec_key": "community_models_specs/tensorflow-ic-" "imagenet-inception-v3-classification-4/specs_v3.0.0.json", }, + { + "model_id": "meta-textgeneration-llama-2-7b", + "version": "4.9.0", + "min_version": "2.49.0", + "spec_key": "community_models/meta-textgeneration-llama-2-7b/specs_v4.9.0.json", + }, + { + "model_id": "meta-textgeneration-llama-2-7b", + "version": "4.13.0", + "min_version": "2.49.0", + "spec_key": "community_models/meta-textgeneration-llama-2-7b/specs_v4.13.0.json", + }, ] BASE_PROPRIETARY_HEADER = { diff --git a/tests/unit/sagemaker/jumpstart/test_cache.py b/tests/unit/sagemaker/jumpstart/test_cache.py index b7edc124d3..17996f4f15 100644 --- a/tests/unit/sagemaker/jumpstart/test_cache.py +++ b/tests/unit/sagemaker/jumpstart/test_cache.py @@ -184,6 +184,30 @@ def test_jumpstart_cache_get_header(): semantic_version_str="1.0.*", ) + assert JumpStartModelHeader( + { + "model_id": "meta-textgeneration-llama-2-7b", + "version": "4.13.0", + "min_version": "2.49.0", + "spec_key": "community_models/meta-textgeneration-llama-2-7b/specs_v4.13.0.json", + } + ) == cache.get_header( + model_id="meta-textgeneration-llama-2-7b", + semantic_version_str="*", + ) + + assert JumpStartModelHeader( + { + "model_id": "meta-textgeneration-llama-2-7b", + "version": "4.13.0", + "min_version": "2.49.0", + "spec_key": "community_models/meta-textgeneration-llama-2-7b/specs_v4.13.0.json", + } + ) == cache.get_header( + model_id="meta-textgeneration-llama-2-7b", + semantic_version_str="4.*", + ) + assert JumpStartModelHeader( { "model_id": "ai21-summarization", From 7fc9868b6f591086ee3ffedb6b4fc44d927cf011 Mon Sep 17 00:00:00 2001 From: ruiliann666 <141953824+ruiliann666@users.noreply.github.com> Date: Thu, 3 Apr 2025 14:21:07 -0700 Subject: [PATCH 041/164] Add mlflow tracking arn telemetry (#5113) Integ test failure is align with CI health --- src/sagemaker/serve/utils/telemetry_logger.py | 5 ++++- tests/unit/sagemaker/serve/utils/test_telemetry_logger.py | 8 ++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/src/sagemaker/serve/utils/telemetry_logger.py b/src/sagemaker/serve/utils/telemetry_logger.py index a1a0408718..c02fe9bf78 100644 --- a/src/sagemaker/serve/utils/telemetry_logger.py +++ b/src/sagemaker/serve/utils/telemetry_logger.py @@ -19,7 +19,7 @@ from sagemaker import Session, exceptions from sagemaker.serve.mode.function_pointers import Mode -from sagemaker.serve.model_format.mlflow.constants import MLFLOW_MODEL_PATH +from sagemaker.serve.model_format.mlflow.constants import MLFLOW_MODEL_PATH, MLFLOW_TRACKING_ARN from sagemaker.serve.utils.exceptions import ModelBuilderException from sagemaker.serve.utils.lineage_constants import ( MLFLOW_LOCAL_PATH, @@ -144,6 +144,9 @@ def wrapper(self, *args, **kwargs): mlflow_model_path = self.model_metadata[MLFLOW_MODEL_PATH] mlflow_model_path_type = _get_mlflow_model_path_type(mlflow_model_path) extra += f"&x-mlflowModelPathType={MLFLOW_MODEL_PATH_CODE[mlflow_model_path_type]}" + mlflow_model_tracking_server_arn = self.model_metadata.get(MLFLOW_TRACKING_ARN) + if mlflow_model_tracking_server_arn is not None: + extra += f"&x-mlflowTrackingServerArn={mlflow_model_tracking_server_arn}" if getattr(self, "model_hub", False): extra += f"&x-modelHub={MODEL_HUB_TO_CODE[str(self.model_hub)]}" diff --git a/tests/unit/sagemaker/serve/utils/test_telemetry_logger.py b/tests/unit/sagemaker/serve/utils/test_telemetry_logger.py index 4729efbda4..fc832ad02d 100644 --- a/tests/unit/sagemaker/serve/utils/test_telemetry_logger.py +++ b/tests/unit/sagemaker/serve/utils/test_telemetry_logger.py @@ -14,7 +14,7 @@ import unittest from unittest.mock import Mock, patch, MagicMock from sagemaker.serve import Mode, ModelServer -from sagemaker.serve.model_format.mlflow.constants import MLFLOW_MODEL_PATH +from sagemaker.serve.model_format.mlflow.constants import MLFLOW_MODEL_PATH, MLFLOW_TRACKING_ARN from sagemaker.serve.utils.telemetry_logger import ( _send_telemetry, _capture_telemetry, @@ -40,7 +40,10 @@ MOCK_HUGGINGFACE_ID = "meta-llama/Llama-2-7b-hf" MOCK_EXCEPTION = LocalModelOutOfMemoryException("mock raise ex") MOCK_ENDPOINT_ARN = "arn:aws:sagemaker:us-west-2:123456789012:endpoint/test" -MOCK_MODEL_METADATA_FOR_MLFLOW = {MLFLOW_MODEL_PATH: "s3://some_path"} +MOCK_MODEL_METADATA_FOR_MLFLOW = { + MLFLOW_MODEL_PATH: "s3://some_path", + MLFLOW_TRACKING_ARN: "arn:aws:sagemaker:us-west-2:000000000000:mlflow-tracking-server/test", +} class ModelBuilderMock: @@ -274,6 +277,7 @@ def test_capture_telemetry_decorator_mlflow_success(self, mock_send_telemetry): f"&x-defaultImageUsage={ImageUriOption.DEFAULT_IMAGE.value}" f"&x-endpointArn={MOCK_ENDPOINT_ARN}" f"&x-mlflowModelPathType=2" + f"&x-mlflowTrackingServerArn={MOCK_MODEL_METADATA_FOR_MLFLOW[MLFLOW_TRACKING_ARN]}" f"&x-latency={latency}" ) From 09be430164417836260862eef9cc0430d96f0525 Mon Sep 17 00:00:00 2001 From: Ben Crabtree Date: Thu, 3 Apr 2025 21:44:43 -0400 Subject: [PATCH 042/164] Master (#5112) * fix integ test hub * lint * fix jumpstart curated hub bugs * lint * fix tests * linting * lint * rm test file * fix test * fix * lint * remove test * update for test --- src/sagemaker/jumpstart/accessors.py | 5 ++++ src/sagemaker/jumpstart/estimator.py | 9 ++++--- src/sagemaker/jumpstart/utils.py | 36 +++++++++++++++++++++------- 3 files changed, 39 insertions(+), 11 deletions(-) diff --git a/src/sagemaker/jumpstart/accessors.py b/src/sagemaker/jumpstart/accessors.py index 2ed2deb803..9ebc2880bc 100644 --- a/src/sagemaker/jumpstart/accessors.py +++ b/src/sagemaker/jumpstart/accessors.py @@ -25,6 +25,7 @@ from sagemaker.jumpstart.hub.utils import ( construct_hub_model_arn_from_inputs, construct_hub_model_reference_arn_from_inputs, + generate_hub_arn_for_init_kwargs, ) from sagemaker.jumpstart.constants import JUMPSTART_DEFAULT_REGION_NAME from sagemaker.session import Session @@ -291,6 +292,10 @@ def get_model_specs( # Users only input model id, not contentType, so first try to describe with ModelReference, then with Model if hub_arn: try: + hub_arn = generate_hub_arn_for_init_kwargs( + hub_name=hub_arn, region=region, session=sagemaker_session + ) + hub_model_arn = construct_hub_model_reference_arn_from_inputs( hub_arn=hub_arn, model_name=model_id, version=version ) diff --git a/src/sagemaker/jumpstart/estimator.py b/src/sagemaker/jumpstart/estimator.py index af2fb5bc54..4daf9b1810 100644 --- a/src/sagemaker/jumpstart/estimator.py +++ b/src/sagemaker/jumpstart/estimator.py @@ -41,7 +41,7 @@ validate_model_id_and_get_type, resolve_model_sagemaker_config_field, verify_model_region_and_return_specs, - remove_env_var_from_estimator_kwargs_if_accept_eula_present, + remove_env_var_from_estimator_kwargs_if_model_access_config_present, get_model_access_config, get_hub_access_config, ) @@ -616,6 +616,7 @@ def _validate_model_id_and_get_type_hook(): self.tolerate_vulnerable_model = estimator_init_kwargs.tolerate_vulnerable_model self.instance_count = estimator_init_kwargs.instance_count self.region = estimator_init_kwargs.region + self.environment = estimator_init_kwargs.environment self.orig_predictor_cls = None self.role = estimator_init_kwargs.role self.sagemaker_session = estimator_init_kwargs.sagemaker_session @@ -693,7 +694,7 @@ def fit( accept the end-user license agreement (EULA) that some models require. (Default: None). """ - self.model_access_config = get_model_access_config(accept_eula) + self.model_access_config = get_model_access_config(accept_eula, self.environment) self.hub_access_config = get_hub_access_config( hub_content_arn=self.init_kwargs.get("model_reference_arn", None) ) @@ -713,7 +714,9 @@ def fit( config_name=self.config_name, hub_access_config=self.hub_access_config, ) - remove_env_var_from_estimator_kwargs_if_accept_eula_present(self.init_kwargs, accept_eula) + remove_env_var_from_estimator_kwargs_if_model_access_config_present( + self.init_kwargs, self.model_access_config + ) return super(JumpStartEstimator, self).fit(**estimator_fit_kwargs.to_kwargs_dict()) diff --git a/src/sagemaker/jumpstart/utils.py b/src/sagemaker/jumpstart/utils.py index bd81226727..15f9e9b52e 100644 --- a/src/sagemaker/jumpstart/utils.py +++ b/src/sagemaker/jumpstart/utils.py @@ -1632,17 +1632,29 @@ def get_draft_model_content_bucket(provider: Dict, region: str) -> str: return neo_bucket -def remove_env_var_from_estimator_kwargs_if_accept_eula_present( - init_kwargs: dict, accept_eula: Optional[bool] +def remove_env_var_from_estimator_kwargs_if_model_access_config_present( + init_kwargs: dict, model_access_config: Optional[dict] ): - """Remove env vars if access configs are used + """Remove env vars if ModelAccessConfig is used Args: init_kwargs (dict): Dictionary of kwargs when Estimator is instantiated. accept_eula (Optional[bool]): Whether or not the EULA was accepted, optionally passed in to Estimator.fit(). """ - if accept_eula is not None and init_kwargs["environment"]: - del init_kwargs["environment"][constants.SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY] + if ( + model_access_config is not None + and init_kwargs.get("environment") is not None + and init_kwargs.get("model_uri") is not None + ): + if ( + constants.SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY + in init_kwargs["environment"] + ): + del init_kwargs["environment"][ + constants.SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY + ] + if "accept_eula" in init_kwargs["environment"]: + del init_kwargs["environment"]["accept_eula"] def get_hub_access_config(hub_content_arn: Optional[str]): @@ -1659,16 +1671,24 @@ def get_hub_access_config(hub_content_arn: Optional[str]): return hub_access_config -def get_model_access_config(accept_eula: Optional[bool]): +def get_model_access_config(accept_eula: Optional[bool], environment: Optional[dict]): """Get access configs Args: accept_eula (Optional[bool]): Whether or not the EULA was accepted, optionally passed in to Estimator.fit(). """ + env_var_eula = environment.get("accept_eula") if environment else None + if env_var_eula is not None and accept_eula is not None: + raise ValueError( + "Cannot pass in both accept_eula and environment variables. " + "Please remove the environment variable and pass in the accept_eula parameter." + ) + + model_access_config = None + if env_var_eula is not None: + model_access_config = {"AcceptEula": env_var_eula == "true"} if accept_eula is not None: model_access_config = {"AcceptEula": accept_eula} - else: - model_access_config = None return model_access_config From 228310246557dd36e2b439b7e11a10344faf2f8b Mon Sep 17 00:00:00 2001 From: Namrata Madan Date: Fri, 4 Apr 2025 16:19:46 -0700 Subject: [PATCH 043/164] documentation: update ModelStep data dependency info (#5120) Co-authored-by: Namrata Madan --- ...azon_sagemaker_model_building_pipeline.rst | 24 ++++++++++++++++--- 1 file changed, 21 insertions(+), 3 deletions(-) diff --git a/doc/amazon_sagemaker_model_building_pipeline.rst b/doc/amazon_sagemaker_model_building_pipeline.rst index e3548f80f2..c9f58068f0 100644 --- a/doc/amazon_sagemaker_model_building_pipeline.rst +++ b/doc/amazon_sagemaker_model_building_pipeline.rst @@ -408,21 +408,39 @@ Example: step_args=step_args_register_model, ) -CreateModelStep +ModelStep ```````````````` Referable Property List: - `DescribeModel`_ + OR +- `DescribeModelPackage`_ + .. _DescribeModel: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeModel.html#API_DescribeModel_ResponseSyntax +.. _DescribeModelPackage: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeModelPackage.html#API_DescribeModelPackage_ResponseSyntax Example: +For model creation usecase: + .. code-block:: python - step_model = CreateModelStep(...) - model_data = step_model.PrimaryContainer.ModelDataUrl + create_model_step = ModelStep( + name="MyModelCreationStep", + step_args = model.create(...) + ) + model_data = create_model_step.properties.PrimaryContainer.ModelDataUrl + +For model registration usercase: + +.. code-block:: python + register_model_step = ModelStep( + name="MyModelRegistrationStep", + step_args=model.register(...) + ) + approval_status=register_model_step.properties.ModelApprovalStatus LambdaStep ````````````` From 0a86e605efe3742afa46eb82077f384fb7384dfb Mon Sep 17 00:00:00 2001 From: ruiliann666 <141953824+ruiliann666@users.noreply.github.com> Date: Fri, 4 Apr 2025 19:20:54 -0700 Subject: [PATCH 044/164] Update instance gpu info (#5119) --- .../image_uri_config/instance_gpu_info.json | 60 +++++++++---------- .../serve/utils/test_hardware_detector.py | 2 +- .../serve/utils/test_hardware_detector.py | 4 +- 3 files changed, 33 insertions(+), 33 deletions(-) diff --git a/src/sagemaker/image_uri_config/instance_gpu_info.json b/src/sagemaker/image_uri_config/instance_gpu_info.json index 9fc005bc47..e64a9bcf88 100644 --- a/src/sagemaker/image_uri_config/instance_gpu_info.json +++ b/src/sagemaker/image_uri_config/instance_gpu_info.json @@ -23,7 +23,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-east-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -49,7 +49,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-northeast-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -75,7 +75,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-northeast-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -101,7 +101,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-northeast-3": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -127,7 +127,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-south-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -153,7 +153,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-southeast-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -179,7 +179,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-southeast-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -205,7 +205,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ap-southeast-3": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -231,7 +231,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "ca-central-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -257,7 +257,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "cn-north-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -283,7 +283,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "cn-northwest-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -309,7 +309,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-central-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -335,7 +335,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-central-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -361,7 +361,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-north-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -387,7 +387,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-south-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -413,7 +413,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-south-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -439,7 +439,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-west-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -465,7 +465,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-west-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -491,7 +491,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "eu-west-3": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -517,7 +517,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "il-central-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -543,7 +543,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "me-central-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -569,7 +569,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "me-south-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -595,7 +595,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "sa-east-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -621,7 +621,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-east-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -647,7 +647,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-east-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -673,7 +673,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-gov-east-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -699,7 +699,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-gov-west-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -725,7 +725,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-west-1": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -751,7 +751,7 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} }, "us-west-2": { "ml.p5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 655360}, @@ -777,6 +777,6 @@ "ml.g5.16xlarge": {"Count": 1, "TotalGpuMemoryInMiB": 24576}, "ml.g5.12xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, "ml.g5.24xlarge": {"Count": 4, "TotalGpuMemoryInMiB": 98304}, - "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 196608} + "ml.g5.48xlarge": {"Count": 8, "TotalGpuMemoryInMiB": 183104} } } \ No newline at end of file diff --git a/tests/integ/sagemaker/serve/utils/test_hardware_detector.py b/tests/integ/sagemaker/serve/utils/test_hardware_detector.py index 9102927c55..bab26a25d1 100644 --- a/tests/integ/sagemaker/serve/utils/test_hardware_detector.py +++ b/tests/integ/sagemaker/serve/utils/test_hardware_detector.py @@ -19,7 +19,7 @@ REGION = "us-west-2" VALID_INSTANCE_TYPE = "ml.g5.48xlarge" INVALID_INSTANCE_TYPE = "fl.c5.57xxlarge" -EXPECTED_INSTANCE_GPU_INFO = (8, 196608) +EXPECTED_INSTANCE_GPU_INFO = (8, 183104) def test_get_gpu_info_success(sagemaker_session): diff --git a/tests/unit/sagemaker/serve/utils/test_hardware_detector.py b/tests/unit/sagemaker/serve/utils/test_hardware_detector.py index d383f95809..58839bfc50 100644 --- a/tests/unit/sagemaker/serve/utils/test_hardware_detector.py +++ b/tests/unit/sagemaker/serve/utils/test_hardware_detector.py @@ -21,7 +21,7 @@ REGION = "us-west-2" VALID_INSTANCE_TYPE = "ml.g5.48xlarge" INVALID_INSTANCE_TYPE = "fl.c5.57xxlarge" -EXPECTED_INSTANCE_GPU_INFO = (8, 196608) +EXPECTED_INSTANCE_GPU_INFO = (8, 183104) MIB_CONVERSION_FACTOR = 0.00000095367431640625 MEMORY_BUFFER_MULTIPLIER = 1.2 # 20% buffer @@ -39,7 +39,7 @@ def test_get_gpu_info_success(sagemaker_session, boto_session): "MemoryInfo": {"SizeInMiB": 24576}, } ], - "TotalGpuMemoryInMiB": 196608, + "TotalGpuMemoryInMiB": 183104, }, } ] From 1782329121c8b7b046a9f92700b2a0ecd56d178e Mon Sep 17 00:00:00 2001 From: jkasiraj Date: Mon, 7 Apr 2025 20:07:17 -0700 Subject: [PATCH 045/164] fix: remove historical job_name caching which causes long job name (#5118) --- src/sagemaker/workflow/steps.py | 45 +-------------------- tests/unit/sagemaker/workflow/test_steps.py | 2 +- tests/unit/sagemaker/workflow/test_utils.py | 10 ++--- 3 files changed, 7 insertions(+), 50 deletions(-) diff --git a/src/sagemaker/workflow/steps.py b/src/sagemaker/workflow/steps.py index f49e457bc6..dbc37371db 100644 --- a/src/sagemaker/workflow/steps.py +++ b/src/sagemaker/workflow/steps.py @@ -18,7 +18,6 @@ from enum import Enum from typing import Dict, List, Set, Union, Optional, Any, TYPE_CHECKING -from urllib.parse import urlparse import attr @@ -465,6 +464,7 @@ def __init__( self.step_args = step_args self.estimator = estimator self.inputs = inputs + self.job_name = None self._properties = Properties( step_name=name, step=self, shape_name="DescribeTrainingJobResponse" @@ -493,19 +493,6 @@ def __init__( DeprecationWarning, ) - self.job_name = None - if estimator and (estimator.source_dir or estimator.entry_point): - # By default, `Estimator` will upload the local code to an S3 path - # containing a timestamp. This causes cache misses whenever a - # pipeline is updated, even if the underlying script hasn't changed. - # To avoid this, hash the contents of the training script and include it - # in the `job_name` passed to the `Estimator`, which will be used - # instead of the timestamped path. - if not is_pipeline_variable(estimator.source_dir) and not is_pipeline_variable( - estimator.entry_point - ): - self.job_name = self._generate_code_upload_path() - @property def arguments(self) -> RequestType: """The arguments dictionary that is used to call `create_training_job`. @@ -554,26 +541,6 @@ def to_request(self) -> RequestType: return request_dict - def _generate_code_upload_path(self) -> str or None: - """Generate an upload path for local training scripts based on their content.""" - from sagemaker.workflow.utilities import hash_files_or_dirs - - if self.estimator.source_dir: - source_dir_url = urlparse(self.estimator.source_dir) - if source_dir_url.scheme == "" or source_dir_url.scheme == "file": - code_hash = hash_files_or_dirs( - [self.estimator.source_dir] + self.estimator.dependencies - ) - return f"{self.name}-{code_hash}"[:1024] - elif self.estimator.entry_point: - entry_point_url = urlparse(self.estimator.entry_point) - if entry_point_url.scheme == "" or entry_point_url.scheme == "file": - code_hash = hash_files_or_dirs( - [self.estimator.entry_point] + self.estimator.dependencies - ) - return f"{self.name}-{code_hash}"[:1024] - return None - class CreateModelStep(ConfigurableRetryStep): """`CreateModelStep` for SageMaker Pipelines Workflows.""" @@ -895,16 +862,6 @@ def __init__( "code argument has to be a valid S3 URI or local file path " + "rather than a pipeline variable" ) - code_url = urlparse(code) - if code_url.scheme == "" or code_url.scheme == "file": - # By default, `Processor` will upload the local code to an S3 path - # containing a timestamp. This causes cache misses whenever a - # pipeline is updated, even if the underlying script hasn't changed. - # To avoid this, hash the contents of the script and include it - # in the `job_name` passed to the `Processor`, which will be used - # instead of the timestamped path. - self.job_name = self._generate_code_upload_path() - warnings.warn( ( 'We are deprecating the instantiation of ProcessingStep using "processor".' diff --git a/tests/unit/sagemaker/workflow/test_steps.py b/tests/unit/sagemaker/workflow/test_steps.py index 248fee6532..84906ce620 100644 --- a/tests/unit/sagemaker/workflow/test_steps.py +++ b/tests/unit/sagemaker/workflow/test_steps.py @@ -671,7 +671,7 @@ def test_processing_step_normalizes_args_with_local_code(mock_normalize_args, sc mock_normalize_args.return_value = [step.inputs, step.outputs] step.to_request() mock_normalize_args.assert_called_with( - job_name="MyProcessingStep-a22fc59b38f13da26f6a40b18687ba598cf669f74104b793cefd9c63eddf4ac7", + job_name=None, arguments=step.job_arguments, inputs=step.inputs, outputs=step.outputs, diff --git a/tests/unit/sagemaker/workflow/test_utils.py b/tests/unit/sagemaker/workflow/test_utils.py index e16293a1c5..b18ed71f9b 100644 --- a/tests/unit/sagemaker/workflow/test_utils.py +++ b/tests/unit/sagemaker/workflow/test_utils.py @@ -80,11 +80,11 @@ def test_repack_model_step(estimator): assert hyperparameters["inference_script"] == '"dummy_script.py"' assert hyperparameters["model_archive"] == '"s3://my-bucket/model.tar.gz"' assert hyperparameters["sagemaker_program"] == f'"{REPACK_SCRIPT_LAUNCHER}"' - assert ( - hyperparameters["sagemaker_submit_directory"] - == '"s3://my-bucket/MyRepackModelStep-717d7bdd388168c27e9ad2938ff0314e35be50b3157cf2498688c7525ea27e1e\ -/source/sourcedir.tar.gz"' - ) + + # ex: "gits3://my-bucket/sagemaker-scikit-learn-2025-04-07-20-39-38-854/source/sourcedir.tar.gz" + sagemaker_submit_directory = hyperparameters["sagemaker_submit_directory"] + assert sagemaker_submit_directory.startswith('"s3://my-bucket/sagemaker-scikit-learn-') + assert sagemaker_submit_directory.endswith('/source/sourcedir.tar.gz"') del request_dict["Arguments"]["HyperParameters"] del request_dict["Arguments"]["AlgorithmSpecification"]["TrainingImage"] From fb22b91f0af020da97dce5fc46d8ac7159bf5335 Mon Sep 17 00:00:00 2001 From: "parknate@" Date: Tue, 8 Apr 2025 09:23:06 -0700 Subject: [PATCH 046/164] Fix issue #4856 by copying environment variables (#5115) * Fix issue #4856 by copying environment variables --- src/sagemaker/workflow/notebook_job_step.py | 50 +++++---------- .../workflow/test_notebook_job_step.py | 63 ++++++++++++++++++- 2 files changed, 79 insertions(+), 34 deletions(-) diff --git a/src/sagemaker/workflow/notebook_job_step.py b/src/sagemaker/workflow/notebook_job_step.py index 8a1dd6bc53..ca0ecac15b 100644 --- a/src/sagemaker/workflow/notebook_job_step.py +++ b/src/sagemaker/workflow/notebook_job_step.py @@ -13,49 +13,33 @@ """The notebook job step definitions for workflow.""" from __future__ import absolute_import +import os import re import shutil -import os +from typing import Dict, List, Optional, Union -from typing import ( - List, - Optional, - Union, - Dict, +from sagemaker import vpc_utils +from sagemaker.config.config_schema import ( + NOTEBOOK_JOB_ROLE_ARN, + NOTEBOOK_JOB_S3_KMS_KEY_ID, + NOTEBOOK_JOB_S3_ROOT_URI, + NOTEBOOK_JOB_VOLUME_KMS_KEY_ID, + NOTEBOOK_JOB_VPC_CONFIG_SECURITY_GROUP_IDS, + NOTEBOOK_JOB_VPC_CONFIG_SUBNETS, ) - +from sagemaker.s3 import S3Uploader +from sagemaker.s3_utils import s3_path_join +from sagemaker.session import get_execution_role +from sagemaker.utils import Tags, _tmpdir, format_tags, name_from_base, resolve_value_from_config +from sagemaker.workflow.entities import PipelineVariable, RequestType from sagemaker.workflow.execution_variables import ExecutionVariables from sagemaker.workflow.functions import Join from sagemaker.workflow.properties import Properties from sagemaker.workflow.retry import RetryPolicy -from sagemaker.workflow.steps import ( - Step, - ConfigurableRetryStep, - StepTypeEnum, -) from sagemaker.workflow.step_collections import StepCollection from sagemaker.workflow.step_outputs import StepOutput - -from sagemaker.workflow.entities import ( - RequestType, - PipelineVariable, -) +from sagemaker.workflow.steps import ConfigurableRetryStep, Step, StepTypeEnum from sagemaker.workflow.utilities import _collect_parameters, load_step_compilation_context -from sagemaker.session import get_execution_role - -from sagemaker.s3_utils import s3_path_join -from sagemaker.s3 import S3Uploader -from sagemaker.utils import _tmpdir, name_from_base, resolve_value_from_config, format_tags, Tags -from sagemaker import vpc_utils - -from sagemaker.config.config_schema import ( - NOTEBOOK_JOB_ROLE_ARN, - NOTEBOOK_JOB_S3_ROOT_URI, - NOTEBOOK_JOB_S3_KMS_KEY_ID, - NOTEBOOK_JOB_VOLUME_KMS_KEY_ID, - NOTEBOOK_JOB_VPC_CONFIG_SUBNETS, - NOTEBOOK_JOB_VPC_CONFIG_SECURITY_GROUP_IDS, -) # disable E1101 as collect_parameters decorator sets the attributes @@ -374,7 +358,7 @@ def _prepare_env_variables(self): execution mechanism. """ - job_envs = self.environment_variables if self.environment_variables else {} + job_envs = dict(self.environment_variables or {}) system_envs = { "AWS_DEFAULT_REGION": self._region_from_session, "SM_JOB_DEF_VERSION": "1.0", diff --git a/tests/unit/sagemaker/workflow/test_notebook_job_step.py b/tests/unit/sagemaker/workflow/test_notebook_job_step.py index 9cc34ee243..6a5bb20daa 100644 --- a/tests/unit/sagemaker/workflow/test_notebook_job_step.py +++ b/tests/unit/sagemaker/workflow/test_notebook_job_step.py @@ -12,11 +12,13 @@ # language governing permissions and limitations under the License. from __future__ import absolute_import +import os import unittest + from mock import Mock, patch -from sagemaker.workflow.notebook_job_step import NotebookJobStep from sagemaker.workflow.functions import Join +from sagemaker.workflow.notebook_job_step import NotebookJobStep REGION = "us-west-2" PIPELINE_NAME = "test-pipeline-name" @@ -573,3 +575,62 @@ def _create_step_with_required_fields(self): image_uri=IMAGE_URI, kernel_name=KERNEL_NAME, ) + + def test_environment_variables_not_shared(self): + """Test that environment variables are not shared between NotebookJob steps""" + # Setup shared environment variables + shared_env_vars = {"test": "test"} + + # Create two steps with the same environment variables dictionary + step1 = NotebookJobStep( + name="step1", + input_notebook=INPUT_NOTEBOOK, + image_uri=IMAGE_URI, + kernel_name=KERNEL_NAME, + environment_variables=shared_env_vars, + ) + + step2 = NotebookJobStep( + name="step2", + input_notebook=INPUT_NOTEBOOK, + image_uri=IMAGE_URI, + kernel_name=KERNEL_NAME, + environment_variables=shared_env_vars, + ) + + # Get the arguments for both steps + step1_args = step1.arguments + step2_args = step2.arguments + + # Verify that the environment variables are different objects + self.assertIsNot( + step1_args["Environment"], + step2_args["Environment"], + "Environment dictionaries should be different objects", + ) + + # Verify that modifying one step's environment doesn't affect the other + step1_env = step1_args["Environment"] + step2_env = step2_args["Environment"] + + # Both should have the original test value + self.assertEqual(step1_env["test"], "test") + self.assertEqual(step2_env["test"], "test") + + # Modify step1's environment + step1_env["test"] = "modified" + + # Verify step2's environment remains unchanged + self.assertEqual(step2_env["test"], "test") + + # Verify notebook names are correct for each step + self.assertEqual( + step1_env["SM_INPUT_NOTEBOOK_NAME"], + os.path.basename(INPUT_NOTEBOOK), + "Step 1 should have its own notebook name", + ) + self.assertEqual( + step2_env["SM_INPUT_NOTEBOOK_NAME"], + os.path.basename(INPUT_NOTEBOOK), + "Step 2 should have its own notebook name", + ) From 28e07cfe93290e65273288617e8be94e30959c55 Mon Sep 17 00:00:00 2001 From: rsareddy0329 Date: Thu, 10 Apr 2025 11:59:56 -0700 Subject: [PATCH 047/164] Added handler for pipeline variable while creating process job (#5122) * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * documentation: Removed a line about python version requirements of training script which can misguide users.Training script can be of latest version based on the support provided by framework_version of the container * feature: Enabled update_endpoint through model_builder * fix: fix unit test, black-check, pylint errors * fix: fix black-check, pylint errors * fix:Added handler for pipeline variable while creating process job * fix: Added handler for pipeline variable while creating process job --------- Co-authored-by: Roja Reddy Sareddy --- src/sagemaker/processing.py | 11 +- .../workflow/test_processing_step.py | 17 +- tests/unit/test_processing.py | 249 +++++++++++++++++- 3 files changed, 272 insertions(+), 5 deletions(-) diff --git a/src/sagemaker/processing.py b/src/sagemaker/processing.py index d8674f269d..7beef2e5bd 100644 --- a/src/sagemaker/processing.py +++ b/src/sagemaker/processing.py @@ -17,7 +17,7 @@ and interpretation on Amazon SageMaker. """ from __future__ import absolute_import - +import json import logging import os import pathlib @@ -314,6 +314,15 @@ def _normalize_args( "code argument has to be a valid S3 URI or local file path " + "rather than a pipeline variable" ) + if arguments is not None: + processed_arguments = [] + for arg in arguments: + if isinstance(arg, PipelineVariable): + processed_value = json.dumps(arg.expr) + processed_arguments.append(processed_value) + else: + processed_arguments.append(str(arg)) + arguments = processed_arguments self._current_job_name = self._generate_current_job_name(job_name=job_name) diff --git a/tests/unit/sagemaker/workflow/test_processing_step.py b/tests/unit/sagemaker/workflow/test_processing_step.py index 0dcd7c2495..f94e0791cb 100644 --- a/tests/unit/sagemaker/workflow/test_processing_step.py +++ b/tests/unit/sagemaker/workflow/test_processing_step.py @@ -824,7 +824,12 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session): processor, run_inputs = spark_processor processor.sagemaker_session = pipeline_session processor.role = ROLE - + arguments_output = [ + "--input", + "input-data-uri", + "--output", + '{"Get": "Parameters.MyArgOutput"}', + ] run_inputs["inputs"] = processing_input step_args = processor.run(**run_inputs) @@ -835,7 +840,7 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session): step_args = get_step_args_helper(step_args, "Processing") - assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"] + assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output entry_points = step_args["AppSpecification"]["ContainerEntrypoint"] entry_points_expr = [] @@ -1019,6 +1024,12 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_ processor, run_inputs = spark_processor processor.sagemaker_session = pipeline_session processor.role = ROLE + arguments_output = [ + "--input", + "input-data-uri", + "--output", + '{"Get": "Parameters.MyArgOutput"}', + ] run_inputs["inputs"] = processing_input @@ -1030,7 +1041,7 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_ step_args = get_step_args_helper(step_args, "Processing") - assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"] + assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output entry_points = step_args["AppSpecification"]["ContainerEntrypoint"] entry_points_expr = [] diff --git a/tests/unit/test_processing.py b/tests/unit/test_processing.py index 06d2cde02e..7b020c61bf 100644 --- a/tests/unit/test_processing.py +++ b/tests/unit/test_processing.py @@ -46,8 +46,9 @@ from sagemaker.fw_utils import UploadedCode from sagemaker.workflow.pipeline_context import PipelineSession, _PipelineConfig from sagemaker.workflow.functions import Join -from sagemaker.workflow.execution_variables import ExecutionVariables +from sagemaker.workflow.execution_variables import ExecutionVariable, ExecutionVariables from tests.unit import SAGEMAKER_CONFIG_PROCESSING_JOB +from sagemaker.workflow.parameters import ParameterString BUCKET_NAME = "mybucket" REGION = "us-west-2" @@ -1717,3 +1718,249 @@ def _get_describe_response_inputs_and_ouputs(): "ProcessingInputs": _get_expected_args_all_parameters(None)["inputs"], "ProcessingOutputConfig": _get_expected_args_all_parameters(None)["output_config"], } + + +# Parameters +def _get_data_inputs_with_parameters(): + return [ + ProcessingInput( + source=ParameterString(name="input_data", default_value="s3://dummy-bucket/input"), + destination="/opt/ml/processing/input", + input_name="input-1", + ) + ] + + +def _get_data_outputs_with_parameters(): + return [ + ProcessingOutput( + source="/opt/ml/processing/output", + destination=ParameterString( + name="output_data", default_value="s3://dummy-bucket/output" + ), + output_name="output-1", + ) + ] + + +def _get_expected_args_with_parameters(job_name): + return { + "inputs": [ + { + "InputName": "input-1", + "S3Input": { + "S3Uri": "s3://dummy-bucket/input", + "LocalPath": "/opt/ml/processing/input", + "S3DataType": "S3Prefix", + "S3InputMode": "File", + "S3DataDistributionType": "FullyReplicated", + "S3CompressionType": "None", + }, + } + ], + "output_config": { + "Outputs": [ + { + "OutputName": "output-1", + "S3Output": { + "S3Uri": "s3://dummy-bucket/output", + "LocalPath": "/opt/ml/processing/output", + "S3UploadMode": "EndOfJob", + }, + } + ] + }, + "job_name": job_name, + "resources": { + "ClusterConfig": { + "InstanceType": "ml.m4.xlarge", + "InstanceCount": 1, + "VolumeSizeInGB": 100, + "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", + } + }, + "stopping_condition": {"MaxRuntimeInSeconds": 3600}, + "app_specification": { + "ImageUri": "custom-image-uri", + "ContainerArguments": [ + "--input-data", + "s3://dummy-bucket/input-param", + "--output-path", + "s3://dummy-bucket/output-param", + ], + "ContainerEntrypoint": ["python3"], + }, + "environment": {"my_env_variable": "my_env_variable_value"}, + "network_config": { + "EnableNetworkIsolation": True, + "EnableInterContainerTrafficEncryption": True, + "VpcConfig": { + "Subnets": ["my_subnet_id"], + "SecurityGroupIds": ["my_security_group_id"], + }, + }, + "role_arn": "dummy/role", + "tags": [{"Key": "my-tag", "Value": "my-tag-value"}], + "experiment_config": {"ExperimentName": "AnExperiment"}, + } + + +@patch("os.path.exists", return_value=True) +@patch("os.path.isfile", return_value=True) +@patch("sagemaker.utils.repack_model") +@patch("sagemaker.utils.create_tar_file") +@patch("sagemaker.session.Session.upload_data") +def test_script_processor_with_parameter_string( + upload_data_mock, + create_tar_file_mock, + repack_model_mock, + exists_mock, + isfile_mock, + sagemaker_session, +): + """Test ScriptProcessor with ParameterString arguments""" + upload_data_mock.return_value = "s3://mocked_s3_uri_from_upload_data" + + # Setup processor + processor = ScriptProcessor( + role="arn:aws:iam::012345678901:role/SageMakerRole", # Updated role ARN + image_uri="custom-image-uri", + command=["python3"], + instance_type="ml.m4.xlarge", + instance_count=1, + volume_size_in_gb=100, + volume_kms_key="arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", + output_kms_key="arn:aws:kms:us-west-2:012345678901:key/output-kms-key", + max_runtime_in_seconds=3600, + base_job_name="test_processor", + env={"my_env_variable": "my_env_variable_value"}, + tags=[{"Key": "my-tag", "Value": "my-tag-value"}], + network_config=NetworkConfig( + subnets=["my_subnet_id"], + security_group_ids=["my_security_group_id"], + enable_network_isolation=True, + encrypt_inter_container_traffic=True, + ), + sagemaker_session=sagemaker_session, + ) + + input_param = ParameterString(name="input_param", default_value="s3://dummy-bucket/input-param") + output_param = ParameterString( + name="output_param", default_value="s3://dummy-bucket/output-param" + ) + exec_var = ExecutionVariable(name="ExecutionTest") + join_var = Join(on="/", values=["s3://bucket", "prefix", "file.txt"]) + dummy_str_var = "test-variable" + + # Define expected arguments + expected_args = { + "inputs": [ + { + "InputName": "input-1", + "AppManaged": False, + "S3Input": { + "S3Uri": ParameterString( + name="input_data", default_value="s3://dummy-bucket/input" + ), + "LocalPath": "/opt/ml/processing/input", + "S3DataType": "S3Prefix", + "S3InputMode": "File", + "S3DataDistributionType": "FullyReplicated", + "S3CompressionType": "None", + }, + }, + { + "InputName": "code", + "AppManaged": False, + "S3Input": { + "S3Uri": "s3://mocked_s3_uri_from_upload_data", + "LocalPath": "/opt/ml/processing/input/code", + "S3DataType": "S3Prefix", + "S3InputMode": "File", + "S3DataDistributionType": "FullyReplicated", + "S3CompressionType": "None", + }, + }, + ], + "output_config": { + "Outputs": [ + { + "OutputName": "output-1", + "AppManaged": False, + "S3Output": { + "S3Uri": ParameterString( + name="output_data", default_value="s3://dummy-bucket/output" + ), + "LocalPath": "/opt/ml/processing/output", + "S3UploadMode": "EndOfJob", + }, + } + ], + "KmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/output-kms-key", + }, + "job_name": "test_job", + "resources": { + "ClusterConfig": { + "InstanceType": "ml.m4.xlarge", + "InstanceCount": 1, + "VolumeSizeInGB": 100, + "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", + } + }, + "stopping_condition": {"MaxRuntimeInSeconds": 3600}, + "app_specification": { + "ImageUri": "custom-image-uri", + "ContainerArguments": [ + "--input-data", + '{"Get": "Parameters.input_param"}', + "--output-path", + '{"Get": "Parameters.output_param"}', + "--exec-arg", + '{"Get": "Execution.ExecutionTest"}', + "--join-arg", + '{"Std:Join": {"On": "/", "Values": ["s3://bucket", "prefix", "file.txt"]}}', + "--string-param", + "test-variable", + ], + "ContainerEntrypoint": ["python3", "/opt/ml/processing/input/code/processing_code.py"], + }, + "environment": {"my_env_variable": "my_env_variable_value"}, + "network_config": { + "EnableNetworkIsolation": True, + "EnableInterContainerTrafficEncryption": True, + "VpcConfig": { + "SecurityGroupIds": ["my_security_group_id"], + "Subnets": ["my_subnet_id"], + }, + }, + "role_arn": "arn:aws:iam::012345678901:role/SageMakerRole", + "tags": [{"Key": "my-tag", "Value": "my-tag-value"}], + "experiment_config": {"ExperimentName": "AnExperiment"}, + } + + # Run processor + processor.run( + code="/local/path/to/processing_code.py", + inputs=_get_data_inputs_with_parameters(), + outputs=_get_data_outputs_with_parameters(), + arguments=[ + "--input-data", + input_param, + "--output-path", + output_param, + "--exec-arg", + exec_var, + "--join-arg", + join_var, + "--string-param", + dummy_str_var, + ], + wait=True, + logs=False, + job_name="test_job", + experiment_config={"ExperimentName": "AnExperiment"}, + ) + + # Assert + sagemaker_session.process.assert_called_with(**expected_args) + assert "test_job" in processor._current_job_name From 1f09c08057f9588d81ef861f244e0d6607b54f56 Mon Sep 17 00:00:00 2001 From: Brock Wade Date: Thu, 10 Apr 2025 12:15:04 -0700 Subject: [PATCH 048/164] documentation: update pipelines step caching examples to include more steps (#5121) Co-authored-by: Brock Wade --- ...azon_sagemaker_model_building_pipeline.rst | 214 +++++++++++++++++- 1 file changed, 213 insertions(+), 1 deletion(-) diff --git a/doc/amazon_sagemaker_model_building_pipeline.rst b/doc/amazon_sagemaker_model_building_pipeline.rst index c9f58068f0..1645302d52 100644 --- a/doc/amazon_sagemaker_model_building_pipeline.rst +++ b/doc/amazon_sagemaker_model_building_pipeline.rst @@ -930,7 +930,7 @@ Caching is supported for the following step types: - :class:`sagemaker.workflow.clarify_check_step.ClarifyCheckStep` - :class:`sagemaker.workflow.emr_step.EMRStep` -In order to create pipeline steps and eventually construct a SageMaker pipeline, you provide parameters within a Python script or notebook. The SageMaker Python SDK creates a pipeline definition by translating these parameters into SageMaker job attributes. Some of these attributes, when changed, cause the step to re-run (See `Caching Pipeline Steps `__ for a detailed list). Therefore, if you update a SDK parameter that is used to create such an attribute, the step will rerun. See the following discussion for examples of this in processing and training steps, which are commonly used steps in Pipelines. +In order to create pipeline steps and eventually construct a SageMaker pipeline, you provide parameters within a Python script or notebook. The SageMaker Python SDK creates a pipeline definition by translating these parameters into SageMaker job attributes. Some of these attributes, when changed, cause the step to re-run (See `Caching Pipeline Steps `__ for a detailed list). Therefore, if you update a SDK parameter that is used to create such an attribute, the step will rerun. See the following discussion for examples of this in commonly used step types in Pipelines. The following example creates a processing step: @@ -1055,6 +1055,218 @@ The following parameters from the example cause additional training step iterati - :code:`entry_point`: The entry point file is included in the training job’s `InputDataConfig Channel `__ array. A unique hash is created from the file (and any other dependencies), and then the file is uploaded to S3 with the hash included in the path. When a different entry point file is used, a new hash is created and the S3 path for that `InputDataConfig Channel `__ object changes, initiating a new step run. For examples of what the S3 paths look like, see the **S3 Artifact Folder Structure** section. - :code:`inputs`: The inputs are also included in the training job’s `InputDataConfig `__. Local inputs are uploaded to S3. If the S3 path changes, a new training job is initiated. For examples of S3 paths, see the **S3 Artifact Folder Structure** section. +The following example creates a tuning step: + +.. code-block:: python + + from sagemaker.workflow.steps import TuningStep + from sagemaker.tuner import HyperparameterTuner + from sagemaker.estimator import Estimator + from sagemaker.inputs import TrainingInput + + model_path = f"s3://{default_bucket}/{base_job_prefix}/AbaloneTrain" + + xgb_train = Estimator( + image_uri=image_uri, + instance_type=training_instance_type, + instance_count=1, + output_path=model_path, + base_job_name=f"{base_job_prefix}/abalone-train", + sagemaker_session=pipeline_session, + role=role, + ) + + xgb_train.set_hyperparameters( + eval_metric="rmse", + objective="reg:squarederror", # Define the object metric for the training job + num_round=50, + max_depth=5, + eta=0.2, + gamma=4, + min_child_weight=6, + subsample=0.7, + silent=0, + ) + + objective_metric_name = "validation:rmse" + + hyperparameter_ranges = { + "alpha": ContinuousParameter(0.01, 10, scaling_type="Logarithmic"), + "lambda": ContinuousParameter(0.01, 10, scaling_type="Logarithmic"), + } + + tuner = HyperparameterTuner( + xgb_train, + objective_metric_name, + hyperparameter_ranges, + max_jobs=3, + max_parallel_jobs=3, + strategy="Random", + objective_type="Minimize", + ) + + hpo_args = tuner.fit( + inputs={ + "train": TrainingInput( + s3_data=step_process.properties.ProcessingOutputConfig.Outputs["train"].S3Output.S3Uri, + content_type="text/csv", + ), + "validation": TrainingInput( + s3_data=step_process.properties.ProcessingOutputConfig.Outputs[ + "validation" + ].S3Output.S3Uri, + content_type="text/csv", + ), + } + ) + + step_tuning = TuningStep( + name="HPTuning", + step_args=hpo_args, + cache_config=cache_config, + ) + +The following parameters from the example cause additional tuning (or training) step iterations when you change them: + +- :code:`image_uri`: The :code:`image_uri` parameter defines the image used for training, and is used directly in the `AlgorithmSpecification `__ attribute of the training job(s) that are created from the tuning job. +- :code:`hyperparameters`: All of the hyperparameters passed in the :code:`xgb_train.set_hyperparameters()` method are used directly in the `StaticHyperParameters `__ attribute for the tuning job. +- The following parameters are all included in the `HyperParameterTuningJobConfig `__ and if any one of them changes, a new tuning job is initiated: + - :code:`hyperparameter_ranges` + - :code:`objective_metric_name` + - :code:`max_jobs` + - :code:`max_parallel_jobs` + - :code:`strategy` + - :code:`objective_type` +- :code:`inputs`: The inputs are included in any training job’s `InputDataConfig `__ that get created from the tuning job. Local inputs are uploaded to S3. If the S3 path changes, a new tuning job is initiated. For examples of S3 paths, see the S3 Artifact Folder Structure section. + +The following examples creates a transform step: + +.. code-block:: python + + from sagemaker.transformer import Transformer + from sagemaker.inputs import TransformInput + from sagemaker.workflow.steps import TransformStep + + base_uri = f"s3://{default_bucket}/abalone" + batch_data_uri = sagemaker.s3.S3Uploader.upload( + local_path=local_path, + desired_s3_uri=base_uri, + ) + + batch_data = ParameterString( + name="BatchData", + default_value=batch_data_uri, + ) + + transformer = Transformer( + model_name=step_create_model.properties.ModelName, + instance_type="ml.m5.xlarge", + instance_count=1, + output_path=f"s3://{default_bucket}/AbaloneTransform", + env={ + 'class': 'Transformer' + } + ) + + step_transform = TransformStep( + name="AbaloneTransform", + step_args=transformer.transform( + data=batch_data, + data_type="S3Prefix" + ) + ) + +The following parameters from the example cause additional batch transform step iterations when you change them: + +- :code:`model_name`: The name of the SageMaker model being used for the transform job. +- :code:`env`: Environment variables to be set for use during the transform job. +- :code:`batch_data`: The input data will be included in the transform job’s `TransformInputfield `__. If the S3 path changes, a new transform job is initiated. + +The following example creates an automl step: + +.. code-block:: python + + from sagemaker.workflow.pipeline_context import PipelineSession + from sagemaker.workflow.automl_step import AutoMLStep + + pipeline_session = PipelineSession() + + auto_ml = AutoML(..., + role=role, + target_attribute_name="my_target_attribute_name", + mode="ENSEMBLING", + sagemaker_session=pipeline_session) + + input_training = AutoMLInput( + inputs="s3://amzn-s3-demo-bucket/my-training-data", + target_attribute_name="my_target_attribute_name", + channel_type="training", + ) + input_validation = AutoMLInput( + inputs="s3://amzn-s3-demo-bucket/my-validation-data", + target_attribute_name="my_target_attribute_name", + channel_type="validation", + ) + + step_args = auto_ml.fit( + inputs=[input_training, input_validation] + ) + + step_automl = AutoMLStep( + name="AutoMLStep", + step_args=step_args, + ) + + best_model = step_automl.get_best_auto_ml_model(role=) + +The following parameters from the example cause additional automl step iterations when you change them: + +- :code:`target_attribute_name`: The name of the target variable in supervised learning. +- :code:`mode`: The method that AutoML job uses to train the model - either AUTO, ENSEMBLING or HYPERPARAMETER_TUNING. +- :code:`inputs`: The inputs passed to the auto_ml.fit() method are included in the automl job’s `InputDataConfig `__. If the included S3 path(s) change, a new automl job is initiated. + +The following example creates an EMR step: + +.. code-block:: python + + from sagemaker.workflow.emr_step import EMRStep, EMRStepConfig + + emr_config = EMRStepConfig( + jar="jar-location", # required, path to jar file used + args=["--verbose", "--force"], # optional list of arguments to pass to the jar + main_class="com.my.Main1", # optional main class, this can be omitted if jar above has a manifest + properties=[ # optional list of Java properties that are set when the step runs + { + "key": "mapred.tasktracker.map.tasks.maximum", + "value": "2" + }, + { + "key": "mapreduce.map.sort.spill.percent", + "value": "0.90" + }, + { + "key": "mapreduce.tasktracker.reduce.tasks.maximum", + "value": "5" + } + ] + ) + + step_emr = EMRStep( + name="EMRSampleStep", # required + cluster_id="j-1ABCDEFG2HIJK", # include cluster_id to use a running cluster + step_config=emr_config, # required + display_name="My EMR Step", + description="Pipeline step to execute EMR job" + ) + +The following parameters from the example cause additional EMR step iterations when you change them: + +- :code:`cluster_id`: The id of a running cluster to leverage for the EMR job. +- :code:`emr_config`: Configuration regarding the code that will run on the EMR cluster during the job. + +:class:`Note`: A :code:`cluster_config` parameter may also be passed into :code:`EMRStep` in order to spin up a new cluster. This parameter will also trigger additional step iterations if changed. + + S3 Artifact Folder Structure ---------------------------- From 2bb8c78f84c89bf4d21a6e9277125ec31c443a25 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 11 Apr 2025 01:19:59 +0000 Subject: [PATCH 049/164] prepare release v2.243.1 --- CHANGELOG.md | 18 ++++++++++++++++++ VERSION | 2 +- 2 files changed, 19 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index a22635a580..7db9aa6c8e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,23 @@ # Changelog +## v2.243.1 (2025-04-11) + +### Bug Fixes and Other Changes + + * Added handler for pipeline variable while creating process job + * Fix issue #4856 by copying environment variables + * remove historical job_name caching which causes long job name + * Update instance gpu info + * Master + * Add mlflow tracking arn telemetry + * chore: fix semantic versioning for wildcard identifier + * flaky test + +### Documentation Changes + + * update pipelines step caching examples to include more steps + * update ModelStep data dependency info + ## v2.243.0 (2025-03-27) ### Features diff --git a/VERSION b/VERSION index 7fbcc66779..eb42dabdb4 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.1.dev0 +2.243.1 From 2f86ad9f2edfd26aab6d4cd70a5c2f1811ee7ca3 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 11 Apr 2025 01:20:03 +0000 Subject: [PATCH 050/164] update development version to v2.243.2.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index eb42dabdb4..f68f7b9691 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.1 +2.243.2.dev0 From 99b1b81f61becde712d4735ab9b3c2b2033c27a4 Mon Sep 17 00:00:00 2001 From: Pravali Uppugunduri <46845440+pravali96@users.noreply.github.com> Date: Tue, 15 Apr 2025 08:14:38 -0700 Subject: [PATCH 051/164] Fix deepdiff dependencies (#5128) * Fix deepdiff dependencies * trigger tests --- requirements/extras/test_requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index de960e4619..a0087a8e13 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -50,3 +50,4 @@ fastapi==0.115.4 nest-asyncio sagemaker-mlflow>=0.1.0 deepdiff>=8.0.0 +orderly-set<5.4.0 From 6d52a81fb8e0d1f4e8c333aaeaad8854096136bd Mon Sep 17 00:00:00 2001 From: rsareddy0329 Date: Tue, 15 Apr 2025 09:39:34 -0700 Subject: [PATCH 052/164] Fix: fix the issue due to PR changes, 5122 (#5124) * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * documentation: Removed a line about python version requirements of training script which can misguide users.Training script can be of latest version based on the support provided by framework_version of the container * feature: Enabled update_endpoint through model_builder * fix: fix unit test, black-check, pylint errors * fix: fix black-check, pylint errors * fix:Added handler for pipeline variable while creating process job * fix: Added handler for pipeline variable while creating process job * Revert the PR changes: #5122, due to issue https://t.corp.amazon.com/P223568185/overview * Fix: fix the issue, https://t.corp.amazon.com/P223568185/communication --------- Co-authored-by: Roja Reddy Sareddy --- src/sagemaker/processing.py | 3 ++- tests/unit/sagemaker/workflow/test_processing_step.py | 3 +++ 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/processing.py b/src/sagemaker/processing.py index 7beef2e5bd..eda4ffc01e 100644 --- a/src/sagemaker/processing.py +++ b/src/sagemaker/processing.py @@ -314,6 +314,7 @@ def _normalize_args( "code argument has to be a valid S3 URI or local file path " + "rather than a pipeline variable" ) + if arguments is not None: processed_arguments = [] for arg in arguments: @@ -321,7 +322,7 @@ def _normalize_args( processed_value = json.dumps(arg.expr) processed_arguments.append(processed_value) else: - processed_arguments.append(str(arg)) + processed_arguments.append(arg) arguments = processed_arguments self._current_job_name = self._generate_current_job_name(job_name=job_name) diff --git a/tests/unit/sagemaker/workflow/test_processing_step.py b/tests/unit/sagemaker/workflow/test_processing_step.py index f94e0791cb..9ee8242a45 100644 --- a/tests/unit/sagemaker/workflow/test_processing_step.py +++ b/tests/unit/sagemaker/workflow/test_processing_step.py @@ -824,12 +824,14 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session): processor, run_inputs = spark_processor processor.sagemaker_session = pipeline_session processor.role = ROLE + arguments_output = [ "--input", "input-data-uri", "--output", '{"Get": "Parameters.MyArgOutput"}', ] + run_inputs["inputs"] = processing_input step_args = processor.run(**run_inputs) @@ -1024,6 +1026,7 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_ processor, run_inputs = spark_processor processor.sagemaker_session = pipeline_session processor.role = ROLE + arguments_output = [ "--input", "input-data-uri", From 92efc091509733e86fb8b8161e11bfc379dc905b Mon Sep 17 00:00:00 2001 From: evakravi <69981223+evakravi@users.noreply.github.com> Date: Tue, 15 Apr 2025 18:30:23 -0400 Subject: [PATCH 053/164] fix: tgi image uri unit tests (#5127) * fix: tgi image uri unit tests * fix: black-format and flake8 failures * fix: parse * fix: print statement --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> --- .../image_uris/test_huggingface_llm.py | 22 +++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py index 0d96417e9f..084c2d1438 100644 --- a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py +++ b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py @@ -13,6 +13,7 @@ from __future__ import absolute_import import pytest +from packaging.version import parse from sagemaker.huggingface import get_huggingface_llm_image_uri from tests.unit.sagemaker.image_uris import expected_uris, conftest @@ -72,10 +73,31 @@ def test_huggingface_uris(load_config): VERSIONS = load_config["inference"]["versions"] device = load_config["inference"]["processors"][0] backend = "huggingface-neuronx" if device == "inf2" else "huggingface" + + # Fail if device is not in mapping + if device not in HF_VERSIONS_MAPPING: + raise ValueError(f"Device {device} not found in HF_VERSIONS_MAPPING") + + # Get highest version for the device + highest_version = max(HF_VERSIONS_MAPPING[device].keys(), key=lambda x: parse(x)) + for version in VERSIONS: ACCOUNTS = load_config["inference"]["versions"][version]["registries"] for region in ACCOUNTS.keys(): uri = get_huggingface_llm_image_uri(backend, region=region, version=version) + + # Skip only if test version is higher than highest known version. + # There's now automation to add new TGI releases to image_uri_config directory + # that doesn't involve a human raising a PR. + if parse(version) > parse(highest_version): + print( + f"Skipping version check for {version} as there is " + "automation that now updates the image_uri_config " + "without a human raising a PR. Tests will pass for " + f"versions higher than {highest_version} that are not in HF_VERSIONS_MAPPING." + ) + continue + expected = expected_uris.huggingface_llm_framework_uri( "huggingface-pytorch-tgi-inference", ACCOUNTS[region], From 29bdeb42985499317f6823a9f51b201c2397675e Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 16 Apr 2025 10:20:25 +0000 Subject: [PATCH 054/164] prepare release v2.243.2 --- CHANGELOG.md | 7 +++++++ VERSION | 2 +- 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 7db9aa6c8e..e59d964bd1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,12 @@ # Changelog +## v2.243.2 (2025-04-16) + +### Bug Fixes and Other Changes + + * tgi image uri unit tests + * Fix deepdiff dependencies + ## v2.243.1 (2025-04-11) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index f68f7b9691..9ce3f056ec 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.2.dev0 +2.243.2 From 27e5208201efbebdc0cd7ff1a03448f58591f14f Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 16 Apr 2025 10:20:29 +0000 Subject: [PATCH 055/164] update development version to v2.243.3.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 9ce3f056ec..4e55ec1ee4 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.2 +2.243.3.dev0 From ba6323f4b7d511e0861055cab9fff9522d89349a Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Fri, 11 Apr 2025 14:18:19 +0000 Subject: [PATCH 056/164] change: update image_uri_configs 04-11-2025 07:18:19 PST --- .../image_uri_config/huggingface-llm.json | 108 +++++++++++++++++- 1 file changed, 107 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm.json b/src/sagemaker/image_uri_config/huggingface-llm.json index 27df32a073..eead1b33aa 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm.json +++ b/src/sagemaker/image_uri_config/huggingface-llm.json @@ -14,7 +14,9 @@ "1.4": "1.4.5", "2.0": "2.4.0", "2.3": "2.3.1", - "3.0": "3.0.1" + "3.0": "3.0.1", + "3.2": "3.2.0", + "3.1": "3.1.1" }, "versions": { "0.6.0": { @@ -952,6 +954,110 @@ "container_version": { "gpu": "cu124-ubuntu22.04-v2.1" } + }, + "3.1.1": { + "py_versions": [ + "py311" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "tag_prefix": "2.6.0-tgi3.1.1", + "repository": "huggingface-pytorch-tgi-inference", + "container_version": { + "gpu": "cu124-ubuntu22.04" + } + }, + "3.2.0": { + "py_versions": [ + "py311" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "tag_prefix": "2.6.0-tgi3.2.0", + "repository": "huggingface-pytorch-tgi-inference", + "container_version": { + "gpu": "cu124-ubuntu22.04" + } } } } From f225b856dbc162464ae61e9707f2e5aa0eb68ecd Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 15 Apr 2025 14:18:10 +0000 Subject: [PATCH 057/164] change: update image_uri_configs 04-15-2025 07:18:10 PST --- .../huggingface-llm-neuronx.json | 11 +++ .../image_uri_config/huggingface-llm.json | 20 +++++ src/sagemaker/image_uri_config/pytorch.json | 55 ++++++++++++ .../image_uri_config/tensorflow.json | 83 +++++++++++++++++++ 4 files changed, 169 insertions(+) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index ed5c289377..d79e7637ed 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -14,6 +14,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -66,6 +67,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -118,6 +120,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -170,6 +173,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -222,6 +226,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -274,6 +279,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -326,6 +332,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -378,6 +385,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -430,6 +438,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -482,6 +491,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -534,6 +544,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", diff --git a/src/sagemaker/image_uri_config/huggingface-llm.json b/src/sagemaker/image_uri_config/huggingface-llm.json index eead1b33aa..127b341d6a 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm.json +++ b/src/sagemaker/image_uri_config/huggingface-llm.json @@ -26,6 +26,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -78,6 +79,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -130,6 +132,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -182,6 +185,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -234,6 +238,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -286,6 +291,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -338,6 +344,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -390,6 +397,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -442,6 +450,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -494,6 +503,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -546,6 +556,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -598,6 +609,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -650,6 +662,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -702,6 +715,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -754,6 +768,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -806,6 +821,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -858,6 +874,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -910,6 +927,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -962,6 +980,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1014,6 +1033,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", diff --git a/src/sagemaker/image_uri_config/pytorch.json b/src/sagemaker/image_uri_config/pytorch.json index 01e0d65dc5..dbff976442 100644 --- a/src/sagemaker/image_uri_config/pytorch.json +++ b/src/sagemaker/image_uri_config/pytorch.json @@ -199,6 +199,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -246,6 +247,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -293,6 +295,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -340,6 +343,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -387,6 +391,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -434,6 +439,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -481,6 +487,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -528,6 +535,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -574,6 +582,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -620,6 +629,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -666,6 +676,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -712,6 +723,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -758,6 +770,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -804,6 +817,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -850,6 +864,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -896,6 +911,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -942,6 +958,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -988,6 +1005,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1034,6 +1052,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1082,6 +1101,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1130,6 +1150,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1174,6 +1195,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1218,6 +1240,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1262,6 +1285,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1324,6 +1348,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1373,6 +1398,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1420,6 +1446,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1467,6 +1494,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1514,6 +1542,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1561,6 +1590,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1608,6 +1638,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1787,6 +1818,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1834,6 +1866,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1882,6 +1915,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1929,6 +1963,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1976,6 +2011,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2023,6 +2059,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2070,6 +2107,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2117,6 +2155,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2163,6 +2202,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2209,6 +2249,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2255,6 +2296,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2301,6 +2343,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2347,6 +2390,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2393,6 +2437,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2439,6 +2484,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2485,6 +2531,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2531,6 +2578,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2577,6 +2625,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2623,6 +2672,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2671,6 +2721,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2719,6 +2770,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2767,6 +2819,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2811,6 +2864,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2855,6 +2909,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", diff --git a/src/sagemaker/image_uri_config/tensorflow.json b/src/sagemaker/image_uri_config/tensorflow.json index 37fa7ee46d..ded83e59a4 100644 --- a/src/sagemaker/image_uri_config/tensorflow.json +++ b/src/sagemaker/image_uri_config/tensorflow.json @@ -631,6 +631,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -674,6 +675,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -717,6 +719,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -760,6 +763,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -803,6 +807,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -846,6 +851,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -889,6 +895,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -932,6 +939,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -975,6 +983,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1018,6 +1027,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1061,6 +1071,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1104,6 +1115,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1147,6 +1159,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1190,6 +1203,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1233,6 +1247,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1276,6 +1291,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1319,6 +1335,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1362,6 +1379,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1405,6 +1423,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1448,6 +1467,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1491,6 +1511,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1534,6 +1555,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1577,6 +1599,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1620,6 +1643,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1663,6 +1687,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1706,6 +1731,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1749,6 +1775,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1792,6 +1819,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1835,6 +1863,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1878,6 +1907,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1921,6 +1951,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -1964,6 +1995,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2007,6 +2039,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2050,6 +2083,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2093,6 +2127,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2136,6 +2171,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2179,6 +2215,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2222,6 +2259,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2267,6 +2305,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2312,6 +2351,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2353,6 +2393,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2414,6 +2455,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2463,6 +2505,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2512,6 +2555,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -2561,6 +2605,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3065,6 +3110,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3112,6 +3158,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3160,6 +3207,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3208,6 +3256,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3256,6 +3305,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3304,6 +3354,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3351,6 +3402,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3398,6 +3450,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3445,6 +3498,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3492,6 +3546,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3539,6 +3594,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3586,6 +3642,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3633,6 +3690,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3680,6 +3738,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3727,6 +3786,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3773,6 +3833,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3819,6 +3880,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3865,6 +3927,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3911,6 +3974,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -3957,6 +4021,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4003,6 +4068,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4049,6 +4115,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4095,6 +4162,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4141,6 +4209,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4187,6 +4256,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4233,6 +4303,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4279,6 +4350,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4325,6 +4397,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4371,6 +4444,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4417,6 +4491,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4463,6 +4538,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4509,6 +4585,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4555,6 +4632,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4601,6 +4679,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4645,6 +4724,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4693,6 +4773,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4741,6 +4822,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -4785,6 +4867,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", From 6b96afaea3e77ff970dcdb1510947b565a2d242f Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Wed, 16 Apr 2025 14:18:18 +0000 Subject: [PATCH 058/164] change: update image_uri_configs 04-16-2025 07:18:18 PST --- .../image_uri_config/huggingface-llm.json | 55 ++++++++++++++++++- .../image_uri_config/tensorflow.json | 1 + 2 files changed, 55 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm.json b/src/sagemaker/image_uri_config/huggingface-llm.json index 127b341d6a..ed85f0d2bf 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm.json +++ b/src/sagemaker/image_uri_config/huggingface-llm.json @@ -15,7 +15,7 @@ "2.0": "2.4.0", "2.3": "2.3.1", "3.0": "3.0.1", - "3.2": "3.2.0", + "3.2": "3.2.3", "3.1": "3.1.1" }, "versions": { @@ -1078,6 +1078,59 @@ "container_version": { "gpu": "cu124-ubuntu22.04" } + }, + "3.2.3": { + "py_versions": [ + "py311" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "tag_prefix": "2.6.0-tgi3.2.3", + "repository": "huggingface-pytorch-tgi-inference", + "container_version": { + "gpu": "cu124-ubuntu22.04" + } } } } diff --git a/src/sagemaker/image_uri_config/tensorflow.json b/src/sagemaker/image_uri_config/tensorflow.json index ded83e59a4..097baafa9b 100644 --- a/src/sagemaker/image_uri_config/tensorflow.json +++ b/src/sagemaker/image_uri_config/tensorflow.json @@ -2655,6 +2655,7 @@ "registries": { "af-south-1": "626614931356", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", From 79c4dddc5fa6261537bd58bf226dc2de5f830d28 Mon Sep 17 00:00:00 2001 From: Molly He Date: Thu, 17 Apr 2025 10:03:29 -0700 Subject: [PATCH 059/164] update pr test to deprecate py38 and add py312 (#5133) --- .github/workflows/codebuild-ci-health.yml | 2 +- .github/workflows/codebuild-ci.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/codebuild-ci-health.yml b/.github/workflows/codebuild-ci-health.yml index 7ecefd310f..119b9dbe9c 100644 --- a/.github/workflows/codebuild-ci-health.yml +++ b/.github/workflows/codebuild-ci-health.yml @@ -26,7 +26,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ["py38", "py39", "py310", "py311"] + python-version: ["py39", "py310", "py311","py312"] steps: - name: Configure AWS Credentials uses: aws-actions/configure-aws-credentials@v4 diff --git a/.github/workflows/codebuild-ci.yml b/.github/workflows/codebuild-ci.yml index 8c6bd6b337..eef53ff06c 100644 --- a/.github/workflows/codebuild-ci.yml +++ b/.github/workflows/codebuild-ci.yml @@ -63,7 +63,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ["py38","py39","py310","py311"] + python-version: ["py39","py310","py311","py312"] steps: - name: Configure AWS Credentials uses: aws-actions/configure-aws-credentials@v4 From 2d095edc39e06717c6f2fdbb9ad29d2e28af9aca Mon Sep 17 00:00:00 2001 From: Molly He Date: Fri, 18 Apr 2025 21:18:53 -0700 Subject: [PATCH 060/164] Py312 upgrade step 2: Update dependencies, integ tests and unit tests (#5123) * clean up * bump maxdepth for doc/api/training to fix readthedocs * change maxdepth for readthedocs rendering doc/api/training page * change maxdepth for readthedocs rendering doc/api/training page * change maxdepth for readthedocs rendering doc/api/training page --- .githooks/pre-push | 4 +- .pylintrc | 21 +- .readthedocs.yaml | 4 +- doc/api/inference/model_builder.rst | 12 +- doc/api/training/index.rst | 2 +- doc/conf.py | 11 +- doc/requirements.txt | 8 +- pyproject.toml | 10 +- requirements/extras/local_requirements.txt | 2 +- requirements/extras/scipy_requirements.txt | 2 +- requirements/extras/test_requirements.txt | 15 +- requirements/tox/doc8_requirements.txt | 4 +- requirements/tox/flake8_requirements.txt | 4 +- requirements/tox/pylint_requirements.txt | 4 +- requirements/tox/spelling_requirements.txt | 2 +- src/sagemaker/config/config_schema.py | 24 +- .../feature_store/dataset_builder.py | 2 +- src/sagemaker/jumpstart/factory/model.py | 2 +- src/sagemaker/local/entities.py | 6 +- .../model_monitor/clarify_model_monitoring.py | 6 +- .../multi_model_server/prepare.py | 3 +- .../serve/utils/conda_in_process.yml | 10 +- .../serve/utils/in_process_requirements.txt | 4 +- .../model_step/pytorch_mnist/requirements.txt | 2 +- tests/data/remote_function/requirements.txt | 2 +- .../serve_resources/mlflow/pytorch/conda.yaml | 2 +- .../mlflow/pytorch/requirements.txt | 6 +- .../mlflow/xgboost/requirements.txt | 4 +- tests/data/workflow/requirements.txt | 2 +- tests/integ/sagemaker/experiments/test_run.py | 4 +- .../jumpstart/private_hub/test_hub_content.py | 2 +- .../serve/test_serve_js_deep_unit_tests.py | 54 +- tests/integ/sagemaker/workflow/helpers.py | 4 +- .../integ/sagemaker/workflow/test_workflow.py | 8 +- tests/integ/test_feature_store.py | 16 +- .../lineage/test_feature_processor_lineage.py | 2116 +++++++++-------- .../sagemaker/huggingface/test_llm_utils.py | 4 +- tests/unit/sagemaker/jumpstart/constants.py | 2 +- .../estimator/test_sagemaker_config.py | 100 +- .../jumpstart/model/test_sagemaker_config.py | 44 +- tests/unit/sagemaker/jumpstart/test_utils.py | 24 +- .../sagemaker/local/test_local_entities.py | 7 +- .../modules/train/test_model_trainer.py | 5 +- .../serve/detector/test_dependency_manager.py | 4 +- .../detector/test_pickle_dependencies.py | 45 +- .../djl_serving/test_djl_prepare.py | 6 +- .../test_multi_model_server_prepare.py | 6 +- .../model_server/tgi/test_tgi_prepare.py | 6 +- .../unit/sagemaker/workflow/test_pipeline.py | 61 +- tests/unit/test_exception_on_bad_status.py | 8 +- tests/unit/test_hyperparameter.py | 2 +- tests/unit/test_predictor_async.py | 4 +- tests/unit/test_tuner.py | 49 +- tox.ini | 30 +- 54 files changed, 1555 insertions(+), 1236 deletions(-) diff --git a/.githooks/pre-push b/.githooks/pre-push index 995ab70108..f73fa492b3 100755 --- a/.githooks/pre-push +++ b/.githooks/pre-push @@ -12,5 +12,5 @@ start_time=`date +%s` tox -e sphinx,doc8 --parallel all ./ci-scripts/displaytime.sh 'sphinx,doc8' $start_time start_time=`date +%s` -tox -e py38,py39,py310 --parallel all -- tests/unit -./ci-scripts/displaytime.sh 'py38,py39,py310 unit' $start_time +tox -e py39,py310,py311,py312 --parallel all -- tests/unit +./ci-scripts/displaytime.sh 'py39,py310,py311,py312 unit' $start_time diff --git a/.pylintrc b/.pylintrc index 5428b86be0..223580f4d3 100644 --- a/.pylintrc +++ b/.pylintrc @@ -94,7 +94,24 @@ disable= useless-object-inheritance, # TODO: Enable this check and fix code once Python 2 is no longer supported. super-with-arguments, raise-missing-from, - E1136, + C0116, # Missing function or method docstring + C0209, # Use f-string instead of format + E0015, # Unrecognized option found in config + E0702, # Raising a string instead of an exception + E1101, # Module has no member (likely dynamic attr) + E1136, # Value assigned to something inferred as None + R0022, # Useless option value in config + R1710, # Inconsistent return statements + R1714, # Consider using `in` with comparisons + R1729, # Use a generator + R1732, + R1735, # Consider using a dict or list literal + W0237, # Argument renamed in override + W0613, # Unused argument + W0621, # Redefining name from outer scope + W0719 + W1404, # Implicit string concatenation + W1514, # `open()` used without encoding [REPORTS] # Set the output format. Available formats are text, parseable, colorized, msvs @@ -436,4 +453,4 @@ analyse-fallback-blocks=no # Exceptions that will emit a warning when being caught. Defaults to # "Exception" -overgeneral-exceptions=Exception +overgeneral-exceptions=builtins.Exception diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 0a6e3928b5..0dcc70b9c3 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -5,9 +5,9 @@ version: 2 build: - os: ubuntu-20.04 + os: ubuntu-22.04 tools: - python: "3.9" + python: "3.12" python: diff --git a/doc/api/inference/model_builder.rst b/doc/api/inference/model_builder.rst index 3099441850..3cfbcbc2c7 100644 --- a/doc/api/inference/model_builder.rst +++ b/doc/api/inference/model_builder.rst @@ -3,14 +3,14 @@ Model Builder This module contains classes related to Amazon Sagemaker Model Builder -.. autoclass:: sagemaker.serve.builder.model_builder.ModelBuilder +.. autoclass:: sagemaker.serve.ModelBuilder -.. automethod:: sagemaker.serve.builder.model_builder.ModelBuilder.build +.. automethod:: sagemaker.serve.ModelBuilder.build -.. automethod:: sagemaker.serve.builder.model_builder.ModelBuilder.save +.. automethod:: sagemaker.serve.ModelBuilder.save -.. autoclass:: sagemaker.serve.spec.inference_spec.InferenceSpec +.. autoclass:: sagemaker.serve.InferenceSpec -.. autoclass:: sagemaker.serve.builder.schema_builder.SchemaBuilder +.. autoclass:: sagemaker.serve.SchemaBuilder -.. autoclass:: sagemaker.serve.marshalling.custom_payload_translator.CustomPayloadTranslator +.. autoclass:: sagemaker.serve.CustomPayloadTranslator diff --git a/doc/api/training/index.rst b/doc/api/training/index.rst index 0f61cd1931..285d9f266d 100644 --- a/doc/api/training/index.rst +++ b/doc/api/training/index.rst @@ -3,7 +3,7 @@ Training APIs ############# .. toctree:: - :maxdepth: 4 + :maxdepth: 1 model_trainer algorithm diff --git a/doc/conf.py b/doc/conf.py index 94a5c4d9c6..6c88ddd0e7 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -83,16 +83,11 @@ html_css_files = [ "https://cdn.datatables.net/1.10.23/css/jquery.dataTables.min.css", + "theme_overrides.css", + "pagination.css", + "search_accessories.css", ] -html_context = { - "css_files": [ - "_static/theme_overrides.css", - "_static/pagination.css", - "_static/search_accessories.css", - ] -} - # Example configuration for intersphinx: refer to the Python standard library. intersphinx_mapping = {"python": ("http://docs.python.org/", None)} diff --git a/doc/requirements.txt b/doc/requirements.txt index 71a95f7633..11098e2bc1 100644 --- a/doc/requirements.txt +++ b/doc/requirements.txt @@ -1,7 +1,7 @@ -sphinx==5.1.1 -sphinx-rtd-theme==0.5.0 -docutils==0.15.2 -packaging==20.9 +sphinx==7.2.6 +sphinx-rtd-theme==3.0.0 +docutils>=0.18.1,<0.21 +packaging>=23.0,<25 jinja2==3.1.6 schema==0.7.5 accelerate>=0.24.1,<=0.27.0 diff --git a/pyproject.toml b/pyproject.toml index 0122a6bf3c..c5c9bf9874 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,7 @@ name = "sagemaker" dynamic = ["version", "optional-dependencies"] description = "Open source library for training and deploying models on Amazon SageMaker." readme = "README.rst" -requires-python = ">=3.8" +requires-python = ">=3.9" authors = [ { name = "Amazon Web Services" }, ] @@ -25,10 +25,10 @@ classifiers = [ "License :: OSI Approved :: Apache Software License", "Natural Language :: English", "Programming Language :: Python", - "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", ] dependencies = [ "attrs>=23.1.0,<24", @@ -39,15 +39,15 @@ dependencies = [ "google-pasta", "importlib-metadata>=1.4.0,<7.0", "jsonschema", - "numpy>=1.9.0,<2.0", + "numpy==1.26.4", "omegaconf>=2.2,<=2.3", - "packaging>=20.0", + "packaging>=23.0,<25", "pandas", "pathos", "platformdirs", "protobuf>=3.12,<6.0", "psutil", - "PyYAML~=6.0", + "PyYAML>=6.0.1", "requests", "sagemaker-core>=1.0.17,<2.0.0", "schema", diff --git a/requirements/extras/local_requirements.txt b/requirements/extras/local_requirements.txt index 68b9a1bcb3..ea57b82e9a 100644 --- a/requirements/extras/local_requirements.txt +++ b/requirements/extras/local_requirements.txt @@ -1,3 +1,3 @@ urllib3>=1.26.8,<3.0.0 docker>=5.0.2,<8.0.0 -PyYAML>=5.4.1,<7 +PyYAML>=6.0.1,<7 diff --git a/requirements/extras/scipy_requirements.txt b/requirements/extras/scipy_requirements.txt index 0e99587e6e..44ce1d9331 100644 --- a/requirements/extras/scipy_requirements.txt +++ b/requirements/extras/scipy_requirements.txt @@ -1 +1 @@ -scipy==1.10.1 +scipy==1.11.3 diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index a0087a8e13..3e6200ee3e 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -1,7 +1,7 @@ tox==3.24.5 -numpy>=1.24.0 +numpy==1.26.4 build[virtualenv]==1.2.1 -flake8==4.0.1 +flake8==7.1.2 pytest==6.2.5 pytest-cov==3.0.0 pytest-rerunfailures==10.2 @@ -14,10 +14,10 @@ awslogs==0.14.0 black==24.3.0 stopit==1.1.2 # Update tox.ini to have correct version of airflow constraints file -apache-airflow==2.9.3 +apache-airflow==2.10.4 apache-airflow-providers-amazon==7.2.1 attrs>=23.1.0,<24 -fabric==2.6.0 +fabric==3.2.2 requests==2.32.2 sagemaker-experiments==0.1.35 Jinja2==3.1.6 @@ -26,13 +26,13 @@ pandas==1.4.4 scikit-learn==1.3.0 cloudpickle==2.2.1 jsonpickle<4.0.0 -PyYAML==6.0 +PyYAML>=6.0.1 # TODO find workaround xgboost>=1.6.2,<=1.7.6 pillow>=10.0.1,<=11 opentelemetry-proto==1.27.0 protobuf==4.25.5 -tensorboard>=2.9.0,<=2.15.2 +tensorboard>=2.16.2,<=2.18.0 transformers==4.48.0 sentencepiece==0.1.99 # https://github.com/triton-inference-server/server/issues/6246 @@ -42,7 +42,7 @@ onnx==1.17.0 nbformat>=5.9,<6 accelerate>=0.24.1,<=0.27.0 schema==0.7.5 -tensorflow>=2.9.0,<=2.15.1 +tensorflow>=2.16.2,<=2.18.0 mlflow>=2.12.2,<2.13 huggingface_hub==0.26.2 uvicorn>=0.30.1 @@ -51,3 +51,4 @@ nest-asyncio sagemaker-mlflow>=0.1.0 deepdiff>=8.0.0 orderly-set<5.4.0 +lexicon diff --git a/requirements/tox/doc8_requirements.txt b/requirements/tox/doc8_requirements.txt index e4a040dd4d..8707c06621 100644 --- a/requirements/tox/doc8_requirements.txt +++ b/requirements/tox/doc8_requirements.txt @@ -1,2 +1,2 @@ -doc8==0.10.1 -Pygments==2.15.0 +doc8==1.1.2 +Pygments==2.18.0 diff --git a/requirements/tox/flake8_requirements.txt b/requirements/tox/flake8_requirements.txt index b3ccfca84f..63a79da444 100644 --- a/requirements/tox/flake8_requirements.txt +++ b/requirements/tox/flake8_requirements.txt @@ -1,2 +1,2 @@ -flake8==4.0.1 -flake8-future-import==0.4.6 +flake8==7.1.2 +flake8-future-import==0.4.7 diff --git a/requirements/tox/pylint_requirements.txt b/requirements/tox/pylint_requirements.txt index b307f21762..0e5db209fe 100644 --- a/requirements/tox/pylint_requirements.txt +++ b/requirements/tox/pylint_requirements.txt @@ -1,2 +1,2 @@ -pylint==2.6.2 -astroid==2.4.2 +pylint==3.0.3 +astroid==3.0.2 diff --git a/requirements/tox/spelling_requirements.txt b/requirements/tox/spelling_requirements.txt index 769415eb2c..94d6bc314e 100644 --- a/requirements/tox/spelling_requirements.txt +++ b/requirements/tox/spelling_requirements.txt @@ -1,2 +1,2 @@ pyenchant==3.2.2 -pylint==2.6.2 +pylint==3.0.3 diff --git a/src/sagemaker/config/config_schema.py b/src/sagemaker/config/config_schema.py index 34a98c0b8e..61da17e7cf 100644 --- a/src/sagemaker/config/config_schema.py +++ b/src/sagemaker/config/config_schema.py @@ -540,7 +540,8 @@ def _simple_path(*args: str): "minItems": 0, "maxItems": 50, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment "environmentVariables": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, @@ -553,13 +554,15 @@ def _simple_path(*args: str): }, "maxProperties": 48, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_S3DataSource.html#sagemaker-Type-S3DataSource-S3Uri + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_S3DataSource.html#sagemaker-Type-S3DataSource-S3Uri "s3Uri": { TYPE: "string", "pattern": "^(https|s3)://([^/]+)/?(.*)$", "maxLength": 1024, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AlgorithmSpecification.html#sagemaker-Type-AlgorithmSpecification-ContainerEntrypoint + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_AlgorithmSpecification.html#sagemaker-Type-AlgorithmSpecification-ContainerEntrypoint "preExecutionCommand": {TYPE: "string", "pattern": r".*"}, # Regex based on https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_PipelineDefinitionS3Location.html # except with an additional ^ and $ for the beginning and the end to closer align to @@ -570,7 +573,8 @@ def _simple_path(*args: str): "minLength": 3, "maxLength": 63, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_MonitoringJobDefinition.html#sagemaker-Type-MonitoringJobDefinition-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_MonitoringJobDefinition.html#sagemaker-Type-MonitoringJobDefinition-Environment "environment-Length256-Properties50": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, @@ -583,7 +587,8 @@ def _simple_path(*args: str): }, "maxProperties": 50, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html#sagemaker-CreateTransformJob-request-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_CreateTransformJob.html#sagemaker-CreateTransformJob-request-Environment "environment-Length10240-Properties16": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, @@ -596,7 +601,8 @@ def _simple_path(*args: str): }, "maxProperties": 16, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html#sagemaker-Type-ContainerDefinition-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_ContainerDefinition.html#sagemaker-Type-ContainerDefinition-Environment "environment-Length1024-Properties16": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, @@ -609,7 +615,8 @@ def _simple_path(*args: str): }, "maxProperties": 16, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html#sagemaker-CreateProcessingJob-request-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_CreateProcessingJob.html#sagemaker-CreateProcessingJob-request-Environment "environment-Length256-Properties100": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, @@ -622,7 +629,8 @@ def _simple_path(*args: str): }, "maxProperties": 100, }, - # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment + # Regex is taken from https://docs.aws.amazon.com/sagemaker/latest/APIReference/ + # API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment "environment-Length512-Properties48": { TYPE: OBJECT, ADDITIONAL_PROPERTIES: False, diff --git a/src/sagemaker/feature_store/dataset_builder.py b/src/sagemaker/feature_store/dataset_builder.py index 289fa1ee0c..fc9f9372b1 100644 --- a/src/sagemaker/feature_store/dataset_builder.py +++ b/src/sagemaker/feature_store/dataset_builder.py @@ -929,7 +929,7 @@ def _construct_query_string(self, base: FeatureGroupToBeMerged) -> str: selected_features += ", " selected_features += ", ".join( [ - f'fg_{i}."{feature_name}" as "{feature_name}.{(i+1)}"' + f'fg_{i}."{feature_name}" as "{feature_name}.{(i + 1)}"' for feature_name in feature_group.projected_feature_names ] ) diff --git a/src/sagemaker/jumpstart/factory/model.py b/src/sagemaker/jumpstart/factory/model.py index 4245c5ac91..53ded3f275 100644 --- a/src/sagemaker/jumpstart/factory/model.py +++ b/src/sagemaker/jumpstart/factory/model.py @@ -104,7 +104,7 @@ def get_default_predictor( """ # if there's a non-default predictor, do not mutate -- return as is - if type(predictor) != Predictor: # pylint: disable=C0123 + if not isinstance(predictor, Predictor): raise RuntimeError( "Can only get default predictor from base Predictor class. " f"Using Predictor class '{type(predictor).__name__}'." diff --git a/src/sagemaker/local/entities.py b/src/sagemaker/local/entities.py index a21a375f54..0cf6c6d55a 100644 --- a/src/sagemaker/local/entities.py +++ b/src/sagemaker/local/entities.py @@ -845,10 +845,10 @@ def _initialize_and_validate_parameters(self, overridden_parameters): ) raise ClientError(error_msg, "start_pipeline_execution") parameter_type = default_parameters[param_name].parameter_type - if type(param_value) != parameter_type.python_type: # pylint: disable=C0123 + if not isinstance(param_value, parameter_type.python_type): error_msg = self._construct_validation_exception_message( - "Unexpected type for parameter '{}'. Expected {} but found " - "{}.".format(param_name, parameter_type.python_type, type(param_value)) + f"Unexpected type for parameter '{param_name}'. Expected \ + {parameter_type.python_type} but found {type(param_value)}." ) raise ClientError(error_msg, "start_pipeline_execution") if param_value == "": diff --git a/src/sagemaker/model_monitor/clarify_model_monitoring.py b/src/sagemaker/model_monitor/clarify_model_monitoring.py index 3edfabc747..2d9a4a69e4 100644 --- a/src/sagemaker/model_monitor/clarify_model_monitoring.py +++ b/src/sagemaker/model_monitor/clarify_model_monitoring.py @@ -86,11 +86,9 @@ def __init__( object that configures network isolation, encryption of inter-container traffic, security group IDs, and subnets. """ - if type(self) == __class__: # pylint: disable=unidiomatic-typecheck + if self.__class__ is __class__: raise TypeError( - "{} is abstract, please instantiate its subclasses instead.".format( - __class__.__name__ - ) + f"{__class__.__name__} is abstract, please instantiate its subclasses instead." ) session = sagemaker_session or Session() diff --git a/src/sagemaker/serve/model_server/multi_model_server/prepare.py b/src/sagemaker/serve/model_server/multi_model_server/prepare.py index 48cf5c878a..e3abc70dd6 100644 --- a/src/sagemaker/serve/model_server/multi_model_server/prepare.py +++ b/src/sagemaker/serve/model_server/multi_model_server/prepare.py @@ -84,7 +84,8 @@ def prepare_for_mms( image_uri: str, inference_spec: InferenceSpec = None, ) -> str: - """Prepares for InferenceSpec using model_path, writes inference.py, and captures dependencies to generate secret_key. + """Prepares for InferenceSpec using model_path, writes inference.py, \ + and captures dependencies to generate secret_key. Args:to model_path (str) : Argument diff --git a/src/sagemaker/serve/utils/conda_in_process.yml b/src/sagemaker/serve/utils/conda_in_process.yml index 61badaa52f..1f3fe322ef 100644 --- a/src/sagemaker/serve/utils/conda_in_process.yml +++ b/src/sagemaker/serve/utils/conda_in_process.yml @@ -12,15 +12,15 @@ dependencies: - boto3>=1.34.142,<2.0 - cloudpickle==2.2.1 - google-pasta - - numpy>=1.9.0,<2.0 + - numpy==1.26.4 - protobuf>=3.12,<5.0 - smdebug_rulesconfig==1.0.1 - importlib-metadata>=1.4.0,<7.0 - - packaging>=20.0 + - packaging>=23.0,<25 - pandas - pathos - schema - - PyYAML~=6.0 + - PyYAML>=6.0.1 - jsonschema - platformdirs - tblib>=1.7.0,<4 @@ -43,7 +43,7 @@ dependencies: - colorama>=0.4.4 - contextlib2>=21.6.0 - decorator>=5.1.1 - - dill>=0.3.6 + - dill>=0.3.9 - docutils>=0.16 - entrypoints>=0.4 - filelock>=3.11.0 @@ -82,7 +82,7 @@ dependencies: - python-dateutil>=2.8.2 - pytz>=2023.3 - pytz-deprecation-shim>=0.1.0.post0 - - pyyaml>=5.4.1 + - pyyaml>=6.0.1 - regex>=2023.3.23 - requests>=2.28.2 - rich>=13.3.4 diff --git a/src/sagemaker/serve/utils/in_process_requirements.txt b/src/sagemaker/serve/utils/in_process_requirements.txt index e356e1720d..da1fd8e617 100644 --- a/src/sagemaker/serve/utils/in_process_requirements.txt +++ b/src/sagemaker/serve/utils/in_process_requirements.txt @@ -11,7 +11,7 @@ cloudpickle==2.2.1 colorama>=0.4.4 contextlib2>=21.6.0 decorator>=5.1.1 -dill>=0.3.6 +dill>=0.3.9 docutils>=0.16 entrypoints>=0.4 filelock>=3.11.0 @@ -50,7 +50,7 @@ pyrsistent>=0.19.3 python-dateutil>=2.8.2 pytz>=2023.3 pytz-deprecation-shim>=0.1.0.post0 -pyyaml>=5.4.1 +pyyaml>=6.0.1 regex>=2023.3.23 requests>=2.28.2 rich>=13.3.4 diff --git a/tests/data/pipeline/model_step/pytorch_mnist/requirements.txt b/tests/data/pipeline/model_step/pytorch_mnist/requirements.txt index 56d09228be..c25fca7e9f 100644 --- a/tests/data/pipeline/model_step/pytorch_mnist/requirements.txt +++ b/tests/data/pipeline/model_step/pytorch_mnist/requirements.txt @@ -1 +1 @@ -scipy>=1.8.1 +scipy>=1.11.3 diff --git a/tests/data/remote_function/requirements.txt b/tests/data/remote_function/requirements.txt index 0e99587e6e..44ce1d9331 100644 --- a/tests/data/remote_function/requirements.txt +++ b/tests/data/remote_function/requirements.txt @@ -1 +1 @@ -scipy==1.10.1 +scipy==1.11.3 diff --git a/tests/data/serve_resources/mlflow/pytorch/conda.yaml b/tests/data/serve_resources/mlflow/pytorch/conda.yaml index beecdbab08..b740d25b70 100644 --- a/tests/data/serve_resources/mlflow/pytorch/conda.yaml +++ b/tests/data/serve_resources/mlflow/pytorch/conda.yaml @@ -9,7 +9,7 @@ dependencies: - cffi==1.16.0 - cloudpickle==2.2.1 - defusedxml==0.7.1 - - dill==0.3.8 + - dill==0.3.9 - gmpy2==2.1.2 - numpy==1.26.4 - opt-einsum==3.3.0 diff --git a/tests/data/serve_resources/mlflow/pytorch/requirements.txt b/tests/data/serve_resources/mlflow/pytorch/requirements.txt index 450bcbfada..aacc85cb91 100644 --- a/tests/data/serve_resources/mlflow/pytorch/requirements.txt +++ b/tests/data/serve_resources/mlflow/pytorch/requirements.txt @@ -3,11 +3,11 @@ astunparse==1.6.3 cffi==1.16.0 cloudpickle==2.2.1 defusedxml==0.7.1 -dill==0.3.8 +dill==0.3.9 gmpy2==2.1.2 -numpy==1.24.4 +numpy==1.26.4 opt-einsum==3.3.0 -packaging==21.3 +packaging>=23.0,<25 pandas==2.2.1 pyyaml==6.0.1 requests==2.32.2 diff --git a/tests/data/serve_resources/mlflow/xgboost/requirements.txt b/tests/data/serve_resources/mlflow/xgboost/requirements.txt index 1130dcaec5..6f879340a7 100644 --- a/tests/data/serve_resources/mlflow/xgboost/requirements.txt +++ b/tests/data/serve_resources/mlflow/xgboost/requirements.txt @@ -1,8 +1,8 @@ mlflow==2.13.2 lz4==4.3.2 -numpy==1.24.4 +numpy==1.26.4 pandas==2.0.3 psutil==5.9.8 scikit-learn==1.3.2 -scipy==1.10.1 +scipy==1.11.3 xgboost==1.7.1 diff --git a/tests/data/workflow/requirements.txt b/tests/data/workflow/requirements.txt index 0e99587e6e..44ce1d9331 100644 --- a/tests/data/workflow/requirements.txt +++ b/tests/data/workflow/requirements.txt @@ -1 +1 @@ -scipy==1.10.1 +scipy==1.11.3 diff --git a/tests/integ/sagemaker/experiments/test_run.py b/tests/integ/sagemaker/experiments/test_run.py index 4f59d11c54..f00f53a5ad 100644 --- a/tests/integ/sagemaker/experiments/test_run.py +++ b/tests/integ/sagemaker/experiments/test_run.py @@ -720,8 +720,8 @@ def _generate_processor( ) return FrameworkProcessor( estimator_cls=PyTorch, - framework_version="1.10", - py_version="py38", + framework_version="1.13.1", + py_version="py39", instance_count=1, instance_type="ml.m5.xlarge", role=execution_role, diff --git a/tests/integ/sagemaker/jumpstart/private_hub/test_hub_content.py b/tests/integ/sagemaker/jumpstart/private_hub/test_hub_content.py index b25cff2d62..04b945a457 100644 --- a/tests/integ/sagemaker/jumpstart/private_hub/test_hub_content.py +++ b/tests/integ/sagemaker/jumpstart/private_hub/test_hub_content.py @@ -38,7 +38,7 @@ def test_hub_model_reference(setup): describe_model_response = hub_instance.describe_model(model_name=model_id) assert describe_model_response is not None - assert type(describe_model_response) == DescribeHubContentResponse + assert isinstance(describe_model_response, DescribeHubContentResponse) assert describe_model_response.hub_content_name == model_id assert describe_model_response.hub_content_type == "ModelReference" diff --git a/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py b/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py index e13e672bec..ea65f998c8 100644 --- a/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py +++ b/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py @@ -24,11 +24,12 @@ def test_js_model_with_optimize_speculative_decoding_config_gated_requests_are_expected( sagemaker_session, ): - with patch.object( - Session, "create_model", return_value="mock_model" - ) as mock_create_model, patch.object( - Session, "endpoint_from_production_variants" - ) as mock_endpoint_from_production_variants: + with ( + patch.object(Session, "create_model", return_value="mock_model") as mock_create_model, + patch.object( + Session, "endpoint_from_production_variants" + ) as mock_endpoint_from_production_variants, + ): iam_client = sagemaker_session.boto_session.client("iam") role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"] @@ -100,17 +101,18 @@ def test_js_model_with_optimize_speculative_decoding_config_gated_requests_are_e def test_js_model_with_optimize_sharding_and_resource_requirements_requests_are_expected( sagemaker_session, ): - with patch.object( - Session, - "wait_for_optimization_job", - return_value={"OptimizationJobName": "mock_optimization_job"}, - ), patch.object( - Session, "create_model", return_value="mock_model" - ) as mock_create_model, patch.object( - Session, "endpoint_from_production_variants", return_value="mock_endpoint_name" - ) as mock_endpoint_from_production_variants, patch.object( - Session, "create_inference_component" - ) as mock_create_inference_component: + with ( + patch.object( + Session, + "wait_for_optimization_job", + return_value={"OptimizationJobName": "mock_optimization_job"}, + ), + patch.object(Session, "create_model", return_value="mock_model") as mock_create_model, + patch.object( + Session, "endpoint_from_production_variants", return_value="mock_endpoint_name" + ) as mock_endpoint_from_production_variants, + patch.object(Session, "create_inference_component") as mock_create_inference_component, + ): iam_client = sagemaker_session.boto_session.client("iam") role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"] @@ -185,15 +187,17 @@ def test_js_model_with_optimize_sharding_and_resource_requirements_requests_are_ def test_js_model_with_optimize_quantization_on_pre_optimized_model_requests_are_expected( sagemaker_session, ): - with patch.object( - Session, - "wait_for_optimization_job", - return_value={"OptimizationJobName": "mock_optimization_job"}, - ), patch.object( - Session, "create_model", return_value="mock_model" - ) as mock_create_model, patch.object( - Session, "endpoint_from_production_variants", return_value="mock_endpoint_name" - ) as mock_endpoint_from_production_variants: + with ( + patch.object( + Session, + "wait_for_optimization_job", + return_value={"OptimizationJobName": "mock_optimization_job"}, + ), + patch.object(Session, "create_model", return_value="mock_model") as mock_create_model, + patch.object( + Session, "endpoint_from_production_variants", return_value="mock_endpoint_name" + ) as mock_endpoint_from_production_variants, + ): iam_client = sagemaker_session.boto_session.client("iam") role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"] diff --git a/tests/integ/sagemaker/workflow/helpers.py b/tests/integ/sagemaker/workflow/helpers.py index 20365ef169..9f0176c5c2 100644 --- a/tests/integ/sagemaker/workflow/helpers.py +++ b/tests/integ/sagemaker/workflow/helpers.py @@ -70,8 +70,8 @@ def create_and_execute_pipeline( assert execution_steps[0]["StepStatus"] == step_status if step_result_type: result = execution.result(execution_steps[0]["StepName"]) - assert ( - type(result) == step_result_type + assert isinstance( + result, step_result_type ), f"Expected {step_result_type}, instead found {type(result)}" if step_result_value: diff --git a/tests/integ/sagemaker/workflow/test_workflow.py b/tests/integ/sagemaker/workflow/test_workflow.py index 2643a3b88e..9ef0b14a04 100644 --- a/tests/integ/sagemaker/workflow/test_workflow.py +++ b/tests/integ/sagemaker/workflow/test_workflow.py @@ -1122,8 +1122,8 @@ def test_model_registration_with_tuning_model( entry_point=entry_point, source_dir=base_dir, role=role, - framework_version="1.10", - py_version="py38", + framework_version="1.13.1", + py_version="py39", instance_count=instance_count, instance_type=instance_type, sagemaker_session=pipeline_session, @@ -1159,8 +1159,8 @@ def test_model_registration_with_tuning_model( ), entry_point=entry_point, source_dir=base_dir, - framework_version="1.10", - py_version="py38", + framework_version="1.13.1", + py_version="py39", sagemaker_session=pipeline_session, ) step_model_regis_args = model.register( diff --git a/tests/integ/test_feature_store.py b/tests/integ/test_feature_store.py index 43db78527a..75f1807148 100644 --- a/tests/integ/test_feature_store.py +++ b/tests/integ/test_feature_store.py @@ -1645,9 +1645,11 @@ def test_create_dataset_with_feature_group_base( feature_store_session, feature_group, offline_store_s3_uri ) - with timeout(minutes=10) and cleanup_offline_store( - base, feature_store_session - ) and cleanup_offline_store(feature_group, feature_store_session): + with ( + timeout(minutes=10) + and cleanup_offline_store(base, feature_store_session) + and cleanup_offline_store(feature_group, feature_store_session) + ): feature_store = FeatureStore(sagemaker_session=feature_store_session) df, query_string = ( feature_store.create_dataset(base=base, output_path=offline_store_s3_uri) @@ -1832,9 +1834,11 @@ def test_create_dataset_with_feature_group_base_with_additional_params( feature_store_session, feature_group, offline_store_s3_uri ) - with timeout(minutes=10) and cleanup_offline_store( - base, feature_store_session - ) and cleanup_offline_store(feature_group, feature_store_session): + with ( + timeout(minutes=10) + and cleanup_offline_store(base, feature_store_session) + and cleanup_offline_store(feature_group, feature_store_session) + ): feature_store = FeatureStore(sagemaker_session=feature_store_session) df, query_string = ( feature_store.create_dataset(base=base, output_path=offline_store_s3_uri) diff --git a/tests/unit/sagemaker/feature_store/feature_processor/lineage/test_feature_processor_lineage.py b/tests/unit/sagemaker/feature_store/feature_processor/lineage/test_feature_processor_lineage.py index 118800dd0f..f149823b2f 100644 --- a/tests/unit/sagemaker/feature_store/feature_processor/lineage/test_feature_processor_lineage.py +++ b/tests/unit/sagemaker/feature_store/feature_processor/lineage/test_feature_processor_lineage.py @@ -113,69 +113,85 @@ def test_create_lineage_when_no_lineage_exists_with_fg_only(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - side_effect=RESOURCE_NOT_FOUND_EXCEPTION, - ) as load_pipeline_context_method, patch.object( - PipelineLineageEntityHandler, - "create_pipeline_context", - return_value=PIPELINE_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - [], - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + side_effect=RESOURCE_NOT_FOUND_EXCEPTION, + ) as load_pipeline_context_method, + patch.object( + PipelineLineageEntityHandler, + "create_pipeline_context", + return_value=PIPELINE_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + [], + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + ): lineage_handler.create_lineage() retrieve_feature_group_context_arns_method.assert_has_calls( @@ -259,75 +275,92 @@ def test_create_lineage_when_no_lineage_exists_with_raw_data_only(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - side_effect=RESOURCE_NOT_FOUND_EXCEPTION, - ) as load_pipeline_context_method, patch.object( - PipelineLineageEntityHandler, - "create_pipeline_context", - return_value=PIPELINE_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - [], - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + side_effect=RESOURCE_NOT_FOUND_EXCEPTION, + ) as load_pipeline_context_method, + patch.object( + PipelineLineageEntityHandler, + "create_pipeline_context", + return_value=PIPELINE_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + [], + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_called_once_with( @@ -408,75 +441,92 @@ def test_create_lineage_when_no_lineage_exists_with_fg_and_raw_data_with_tags(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - side_effect=RESOURCE_NOT_FOUND_EXCEPTION, - ) as load_pipeline_context_method, patch.object( - PipelineLineageEntityHandler, - "create_pipeline_context", - return_value=PIPELINE_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - [], - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + side_effect=RESOURCE_NOT_FOUND_EXCEPTION, + ) as load_pipeline_context_method, + patch.object( + PipelineLineageEntityHandler, + "create_pipeline_context", + return_value=PIPELINE_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + [], + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -569,75 +619,92 @@ def test_create_lineage_when_no_lineage_exists_with_no_transformation_code(): output=FEATURE_GROUP_DATA_SOURCE[0].name, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=None, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - side_effect=RESOURCE_NOT_FOUND_EXCEPTION, - ) as load_pipeline_context_method, patch.object( - PipelineLineageEntityHandler, - "create_pipeline_context", - return_value=PIPELINE_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - [], - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=None, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + side_effect=RESOURCE_NOT_FOUND_EXCEPTION, + ) as load_pipeline_context_method, + patch.object( + PipelineLineageEntityHandler, + "create_pipeline_context", + return_value=PIPELINE_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + [], + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -728,78 +795,96 @@ def test_create_lineage_when_already_exist_with_no_version_change(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=PIPELINE_CONTEXT, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as create_pipeline_version_context_method, patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=PIPELINE_CONTEXT, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as create_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -925,73 +1010,91 @@ def test_create_lineage_when_already_exist_with_changed_raw_data(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[RAW_DATA_INPUT_ARTIFACTS[0], RAW_DATA_INPUT_ARTIFACTS[1]], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[RAW_DATA_INPUT_ARTIFACTS[0], RAW_DATA_INPUT_ARTIFACTS[1]], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -1140,74 +1243,92 @@ def test_create_lineage_when_already_exist_with_changed_input_fg(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[FEATURE_GROUP_INPUT[0], FEATURE_GROUP_INPUT[0]], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[FEATURE_GROUP_INPUT[0], FEATURE_GROUP_INPUT[0]], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -1354,78 +1475,96 @@ def test_create_lineage_when_already_exist_with_changed_output_fg(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[1], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_1, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[1], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_1, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -1576,78 +1715,96 @@ def test_create_lineage_when_already_exist_with_changed_transformation_code(): transformation_code=TRANSFORMATION_CODE_INPUT_2, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_2, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_2, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -1778,78 +1935,96 @@ def test_create_lineage_when_already_exist_with_last_transformation_code_as_none transformation_code=TRANSFORMATION_CODE_INPUT_2, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_2, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_2, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -1968,77 +2143,95 @@ def test_create_lineage_when_already_exist_with_all_previous_transformation_code transformation_code=TRANSFORMATION_CODE_INPUT_2, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=TRANSFORMATION_CODE_ARTIFACT_2, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - iter([]), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=TRANSFORMATION_CODE_ARTIFACT_2, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + iter([]), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -2154,78 +2347,96 @@ def test_create_lineage_when_already_exist_with_removed_transformation_code(): output=FEATURE_GROUP_DATA_SOURCE[0].name, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - FeatureGroupLineageEntityHandler, - "retrieve_feature_group_context_arns", - side_effect=[ - FEATURE_GROUP_INPUT[0], - FEATURE_GROUP_INPUT[1], - FEATURE_GROUP_INPUT[0], - ], - ) as retrieve_feature_group_context_arns_method, patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - S3LineageEntityHandler, - "create_transformation_code_artifact", - return_value=None, - ) as create_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - generate_pipeline_version_upstream_transformation_code(), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, - "load_artifact_from_arn", - return_value=transformation_code_1, - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, - "update_transformation_code_artifact", - ) as update_transformation_code_artifact_method, patch.object( - PipelineLineageEntityHandler, - "update_pipeline_context", - ) as update_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "create_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ), patch.object( - LineageAssociationHandler, "add_upstream_feature_group_data_associations" - ) as add_upstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_downstream_feature_group_data_associations" - ) as add_downstream_feature_group_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_raw_data_associations" - ) as add_upstream_raw_data_associations_method, patch.object( - LineageAssociationHandler, "add_upstream_transformation_code_associations" - ) as add_upstream_transformation_code_associations_method, patch.object( - LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" - ) as add_pipeline_and_pipeline_version_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + FeatureGroupLineageEntityHandler, + "retrieve_feature_group_context_arns", + side_effect=[ + FEATURE_GROUP_INPUT[0], + FEATURE_GROUP_INPUT[1], + FEATURE_GROUP_INPUT[0], + ], + ) as retrieve_feature_group_context_arns_method, + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + S3LineageEntityHandler, + "create_transformation_code_artifact", + return_value=None, + ) as create_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + generate_pipeline_version_upstream_transformation_code(), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, + "load_artifact_from_arn", + return_value=transformation_code_1, + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, + "update_transformation_code_artifact", + ) as update_transformation_code_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "update_pipeline_context", + ) as update_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "create_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ), + patch.object( + LineageAssociationHandler, "add_upstream_feature_group_data_associations" + ) as add_upstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_downstream_feature_group_data_associations" + ) as add_downstream_feature_group_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_raw_data_associations" + ) as add_upstream_raw_data_associations_method, + patch.object( + LineageAssociationHandler, "add_upstream_transformation_code_associations" + ) as add_upstream_transformation_code_associations_method, + patch.object( + LineageAssociationHandler, "add_pipeline_and_pipeline_version_association" + ) as add_pipeline_and_pipeline_version_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_lineage(TAGS) retrieve_feature_group_context_arns_method.assert_has_calls( @@ -2370,15 +2581,18 @@ def test_get_pipeline_lineage_names_when_lineage_exists(): transformation_code=TRANSFORMATION_CODE_INPUT_1, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=PIPELINE_CONTEXT, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method: + with ( + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=PIPELINE_CONTEXT, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + ): return_value = lineage_handler.get_pipeline_lineage_names() assert return_value == dict( @@ -2416,28 +2630,34 @@ def test_create_schedule_lineage(): pipeline=PIPELINE, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=PIPELINE_CONTEXT, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - S3LineageEntityHandler, - "retrieve_pipeline_schedule_artifact", - return_value=SCHEDULE_ARTIFACT_RESULT, - ) as retrieve_pipeline_schedule_artifact_method, patch.object( - LineageAssociationHandler, - "add_upstream_schedule_associations", - ) as add_upstream_schedule_associations_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=PIPELINE_CONTEXT, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + S3LineageEntityHandler, + "retrieve_pipeline_schedule_artifact", + return_value=SCHEDULE_ARTIFACT_RESULT, + ) as retrieve_pipeline_schedule_artifact_method, + patch.object( + LineageAssociationHandler, + "add_upstream_schedule_associations", + ) as add_upstream_schedule_associations_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_schedule_lineage( pipeline_name=PIPELINE_NAME, schedule_arn=SCHEDULE_ARN, @@ -2487,28 +2707,34 @@ def test_create_trigger_lineage(): pipeline=PIPELINE, sagemaker_session=SAGEMAKER_SESSION_MOCK, ) - with patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=PIPELINE_CONTEXT, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - S3LineageEntityHandler, - "retrieve_pipeline_trigger_artifact", - return_value=PIPELINE_TRIGGER_ARTIFACT, - ) as retrieve_pipeline_trigger_artifact_method, patch.object( - LineageAssociationHandler, - "_add_association", - ) as add_association_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags: + with ( + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=PIPELINE_CONTEXT, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + S3LineageEntityHandler, + "retrieve_pipeline_trigger_artifact", + return_value=PIPELINE_TRIGGER_ARTIFACT, + ) as retrieve_pipeline_trigger_artifact_method, + patch.object( + LineageAssociationHandler, + "_add_association", + ) as add_association_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + ): lineage_handler.create_trigger_lineage( pipeline_name=PIPELINE_NAME, trigger_arn=TRIGGER_ARN, @@ -2564,56 +2790,68 @@ def test_upsert_tags_for_lineage_resources(): ) lineage_handler.sagemaker_session.boto_session = Mock() lineage_handler.sagemaker_session.sagemaker_client = Mock() - with patch.object( - S3LineageEntityHandler, - "retrieve_raw_data_artifact", - side_effect=[ - RAW_DATA_INPUT_ARTIFACTS[0], - RAW_DATA_INPUT_ARTIFACTS[1], - RAW_DATA_INPUT_ARTIFACTS[2], - RAW_DATA_INPUT_ARTIFACTS[3], - ], - ) as retrieve_raw_data_artifact_method, patch.object( - PipelineLineageEntityHandler, - "load_pipeline_context", - return_value=pipeline_context, - ) as load_pipeline_context_method, patch.object( - PipelineVersionLineageEntityHandler, - "load_pipeline_version_context", - return_value=PIPELINE_VERSION_CONTEXT, - ) as load_pipeline_version_context_method, patch.object( - LineageAssociationHandler, - "list_upstream_associations", - side_effect=[ - generate_pipeline_version_upstream_feature_group_list(), - generate_pipeline_version_upstream_raw_data_list(), - iter([]), - ], - ) as list_upstream_associations_method, patch.object( - LineageAssociationHandler, - "list_downstream_associations", - return_value=generate_pipeline_version_downstream_feature_group(), - ) as list_downstream_associations_method, patch.object( - S3LineageEntityHandler, "load_artifact_from_arn", return_value=ARTIFACT_RESULT - ) as load_artifact_from_arn_method, patch.object( - S3LineageEntityHandler, "_load_artifact_from_s3_uri", return_value=ARTIFACT_SUMMARY - ) as load_artifact_from_s3_uri_method, patch.object( - Artifact, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as artifact_set_tags, patch.object( - Context, - "set_tags", - return_value={ - "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] - }, - ) as context_set_tags, patch.object( - EventBridgeSchedulerHelper, "describe_schedule", return_value=dict(Arn="schedule_arn") - ) as get_event_bridge_schedule, patch.object( - EventBridgeRuleHelper, "describe_rule", return_value=dict(Arn="rule_arn") - ) as get_event_bridge_rule: + with ( + patch.object( + S3LineageEntityHandler, + "retrieve_raw_data_artifact", + side_effect=[ + RAW_DATA_INPUT_ARTIFACTS[0], + RAW_DATA_INPUT_ARTIFACTS[1], + RAW_DATA_INPUT_ARTIFACTS[2], + RAW_DATA_INPUT_ARTIFACTS[3], + ], + ) as retrieve_raw_data_artifact_method, + patch.object( + PipelineLineageEntityHandler, + "load_pipeline_context", + return_value=pipeline_context, + ) as load_pipeline_context_method, + patch.object( + PipelineVersionLineageEntityHandler, + "load_pipeline_version_context", + return_value=PIPELINE_VERSION_CONTEXT, + ) as load_pipeline_version_context_method, + patch.object( + LineageAssociationHandler, + "list_upstream_associations", + side_effect=[ + generate_pipeline_version_upstream_feature_group_list(), + generate_pipeline_version_upstream_raw_data_list(), + iter([]), + ], + ) as list_upstream_associations_method, + patch.object( + LineageAssociationHandler, + "list_downstream_associations", + return_value=generate_pipeline_version_downstream_feature_group(), + ) as list_downstream_associations_method, + patch.object( + S3LineageEntityHandler, "load_artifact_from_arn", return_value=ARTIFACT_RESULT + ) as load_artifact_from_arn_method, + patch.object( + S3LineageEntityHandler, "_load_artifact_from_s3_uri", return_value=ARTIFACT_SUMMARY + ) as load_artifact_from_s3_uri_method, + patch.object( + Artifact, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as artifact_set_tags, + patch.object( + Context, + "set_tags", + return_value={ + "Tags": [dict(Key="key_1", Value="value_1"), dict(Key="key_2", Value="value_2")] + }, + ) as context_set_tags, + patch.object( + EventBridgeSchedulerHelper, "describe_schedule", return_value=dict(Arn="schedule_arn") + ) as get_event_bridge_schedule, + patch.object( + EventBridgeRuleHelper, "describe_rule", return_value=dict(Arn="rule_arn") + ) as get_event_bridge_rule, + ): lineage_handler.upsert_tags_for_lineage_resources(TAGS) retrieve_raw_data_artifact_method.assert_has_calls( diff --git a/tests/unit/sagemaker/huggingface/test_llm_utils.py b/tests/unit/sagemaker/huggingface/test_llm_utils.py index 675a6fd885..9bb1b451a1 100644 --- a/tests/unit/sagemaker/huggingface/test_llm_utils.py +++ b/tests/unit/sagemaker/huggingface/test_llm_utils.py @@ -65,7 +65,7 @@ def test_huggingface_model_metadata_unauthorized_exception(self, mock_urllib): "Trying to access a gated/private HuggingFace model without valid credentials. " "Please provide a HUGGING_FACE_HUB_TOKEN in env_vars" ) - self.assertEquals(expected_error_msg, str(context.exception)) + self.assertEqual(expected_error_msg, str(context.exception)) @patch("sagemaker.huggingface.llm_utils.urllib") def test_huggingface_model_metadata_general_exception(self, mock_urllib): @@ -76,7 +76,7 @@ def test_huggingface_model_metadata_general_exception(self, mock_urllib): expected_error_msg = ( f"Did not find model metadata for the following HuggingFace Model ID {MOCK_HF_ID}" ) - self.assertEquals(expected_error_msg, str(context.exception)) + self.assertEqual(expected_error_msg, str(context.exception)) @patch("huggingface_hub.snapshot_download") def test_download_huggingface_model_metadata(self, mock_snapshot_download): diff --git a/tests/unit/sagemaker/jumpstart/constants.py b/tests/unit/sagemaker/jumpstart/constants.py index 2eb7469e21..ae02c597da 100644 --- a/tests/unit/sagemaker/jumpstart/constants.py +++ b/tests/unit/sagemaker/jumpstart/constants.py @@ -14360,7 +14360,7 @@ "jmespath==1.0.1", "jsonschema==4.17.3", "multiprocess==0.70.14", - "numpy==1.24.3", + "numpy==1.26.4", "oscrypto==1.3.0", "packaging==23.1", "pandas==2.0.2", diff --git a/tests/unit/sagemaker/jumpstart/estimator/test_sagemaker_config.py b/tests/unit/sagemaker/jumpstart/estimator/test_sagemaker_config.py index 073921d5ba..39eca166ee 100644 --- a/tests/unit/sagemaker/jumpstart/estimator/test_sagemaker_config.py +++ b/tests/unit/sagemaker/jumpstart/estimator/test_sagemaker_config.py @@ -123,16 +123,16 @@ def test_without_arg_overwrites_without_kwarg_collisions_with_config( mock_retrieve_model_init_kwargs.return_value = {} - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), config_role) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), config_role) assert "enable_network_isolation" not in mock_estimator_init.call_args[1] assert "encrypt_inter_container_traffic" not in mock_estimator_init.call_args[1] estimator.deploy() - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), config_inference_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), config_inference_role) assert "enable_network_isolation" not in mock_estimator_deploy.call_args[1] @@ -181,13 +181,13 @@ def test_without_arg_overwrites_with_kwarg_collisions_with_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), config_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), config_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), config_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), config_intercontainer_encryption, ) @@ -200,11 +200,11 @@ def test_without_arg_overwrites_with_kwarg_collisions_with_config( estimator.deploy() - self.assertEquals(mock_get_sagemaker_config_value.call_count, 6) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 6) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), config_inference_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), config_inference_role) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), config_inference_enable_network_isolation, ) @@ -257,13 +257,13 @@ def test_with_arg_overwrites_with_kwarg_collisions_with_config( encrypt_inter_container_traffic=override_encrypt_inter_container_traffic, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), override_encrypt_inter_container_traffic, ) @@ -280,13 +280,13 @@ def test_with_arg_overwrites_with_kwarg_collisions_with_config( enable_network_isolation=override_inference_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("role"), mock_inference_override_role ) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), override_inference_enable_network_isolation, ) @@ -336,13 +336,13 @@ def test_with_arg_overwrites_without_kwarg_collisions_with_config( encrypt_inter_container_traffic=override_encrypt_inter_container_traffic, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), override_encrypt_inter_container_traffic, ) @@ -355,13 +355,13 @@ def test_with_arg_overwrites_without_kwarg_collisions_with_config( enable_network_isolation=override_inference_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("role"), mock_inference_override_role ) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), override_inference_enable_network_isolation, ) @@ -412,8 +412,8 @@ def test_without_arg_overwrites_without_kwarg_collisions_without_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), execution_role) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), execution_role) assert "enable_network_isolation" not in mock_estimator_init.call_args[1] assert "encrypt_inter_container_traffic" not in mock_estimator_init.call_args[1] @@ -421,9 +421,9 @@ def test_without_arg_overwrites_without_kwarg_collisions_without_config( mock_retrieve_model_init_kwargs.return_value = {} - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), execution_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), execution_role) assert "enable_network_isolation" not in mock_estimator_deploy.call_args[1] @@ -475,13 +475,13 @@ def test_without_arg_overwrites_with_kwarg_collisions_without_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), execution_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), execution_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), metadata_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), metadata_intercontainer_encryption, ) @@ -492,11 +492,11 @@ def test_without_arg_overwrites_with_kwarg_collisions_without_config( estimator.deploy() - self.assertEquals(mock_get_sagemaker_config_value.call_count, 6) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 6) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), execution_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), execution_role) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), metadata_inference_enable_network_isolation, ) @@ -548,13 +548,13 @@ def test_with_arg_overwrites_with_kwarg_collisions_without_config( encrypt_inter_container_traffic=override_encrypt_inter_container_traffic, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), override_encrypt_inter_container_traffic, ) @@ -568,11 +568,11 @@ def test_with_arg_overwrites_with_kwarg_collisions_without_config( enable_network_isolation=override_inference_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), override_inference_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), override_inference_role) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), override_inference_enable_network_isolation, ) @@ -618,13 +618,13 @@ def test_with_arg_overwrites_without_kwarg_collisions_without_config( enable_network_isolation=override_enable_network_isolation, encrypt_inter_container_traffic=override_encrypt_inter_container_traffic, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_estimator_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_estimator_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_estimator_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) - self.assertEquals( + self.assertEqual( mock_estimator_init.call_args[1].get("encrypt_inter_container_traffic"), override_encrypt_inter_container_traffic, ) @@ -634,11 +634,11 @@ def test_with_arg_overwrites_without_kwarg_collisions_without_config( enable_network_isolation=override_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 3) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 3) - self.assertEquals(mock_estimator_deploy.call_args[1].get("role"), override_inference_role) + self.assertEqual(mock_estimator_deploy.call_args[1].get("role"), override_inference_role) - self.assertEquals( + self.assertEqual( mock_estimator_deploy.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) diff --git a/tests/unit/sagemaker/jumpstart/model/test_sagemaker_config.py b/tests/unit/sagemaker/jumpstart/model/test_sagemaker_config.py index 2be4bde7e4..a0299ebb1a 100644 --- a/tests/unit/sagemaker/jumpstart/model/test_sagemaker_config.py +++ b/tests/unit/sagemaker/jumpstart/model/test_sagemaker_config.py @@ -99,9 +99,9 @@ def test_without_arg_overwrites_without_kwarg_collisions_with_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), config_role) + self.assertEqual(mock_model_init.call_args[1].get("role"), config_role) assert "enable_network_isolation" not in mock_model_init.call_args[1] @@ -147,10 +147,10 @@ def test_all_arg_overwrites_without_kwarg_collisions_with_config( role=override_role, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) @@ -197,10 +197,10 @@ def test_without_arg_overwrites_all_kwarg_collisions_with_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 2) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 2) - self.assertEquals(mock_model_init.call_args[1].get("role"), config_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), config_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), config_enable_network_isolation, ) @@ -249,10 +249,10 @@ def test_with_arg_overwrites_all_kwarg_collisions_with_config( enable_network_isolation=override_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) @@ -299,10 +299,10 @@ def test_without_arg_overwrites_all_kwarg_collisions_without_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 2) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 2) - self.assertEquals(mock_model_init.call_args[1].get("role"), execution_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), execution_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), metadata_enable_network_isolation, ) @@ -350,10 +350,10 @@ def test_with_arg_overwrites_all_kwarg_collisions_without_config( enable_network_isolation=override_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) @@ -398,9 +398,9 @@ def test_without_arg_overwrites_without_kwarg_collisions_without_config( model_id=model_id, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), execution_role) + self.assertEqual(mock_model_init.call_args[1].get("role"), execution_role) assert "enable_network_isolation" not in mock_model_init.call_args[1] @mock.patch( @@ -445,10 +445,10 @@ def test_with_arg_overwrites_without_kwarg_collisions_without_config( enable_network_isolation=override_enable_network_isolation, ) - self.assertEquals(mock_get_sagemaker_config_value.call_count, 1) + self.assertEqual(mock_get_sagemaker_config_value.call_count, 1) - self.assertEquals(mock_model_init.call_args[1].get("role"), override_role) - self.assertEquals( + self.assertEqual(mock_model_init.call_args[1].get("role"), override_role) + self.assertEqual( mock_model_init.call_args[1].get("enable_network_isolation"), override_enable_network_isolation, ) diff --git a/tests/unit/sagemaker/jumpstart/test_utils.py b/tests/unit/sagemaker/jumpstart/test_utils.py index e3e3110da8..de9be1d51d 100644 --- a/tests/unit/sagemaker/jumpstart/test_utils.py +++ b/tests/unit/sagemaker/jumpstart/test_utils.py @@ -1388,7 +1388,7 @@ def test_no_model_id_no_version_found(self): mock_sagemaker_session.list_tags = mock_list_tags mock_list_tags.return_value = [{"Key": "blah", "Value": "blah1"}] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, None, None), ) @@ -1403,7 +1403,7 @@ def test_model_id_no_version_found(self): {"Key": JumpStartTag.MODEL_ID, "Value": "model_id"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), ("model_id", None, None, None), ) @@ -1418,7 +1418,7 @@ def test_no_model_id_version_found(self): {"Key": JumpStartTag.MODEL_VERSION, "Value": "model_version"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, "model_version", None, None), ) @@ -1430,7 +1430,7 @@ def test_no_config_name_found(self): mock_sagemaker_session.list_tags = mock_list_tags mock_list_tags.return_value = [{"Key": "blah", "Value": "blah1"}] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, None, None), ) @@ -1445,7 +1445,7 @@ def test_inference_config_name_found(self): {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "config_name"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, "config_name", None), ) @@ -1460,7 +1460,7 @@ def test_training_config_name_found(self): {"Key": JumpStartTag.TRAINING_CONFIG_NAME, "Value": "config_name"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, None, "config_name"), ) @@ -1476,7 +1476,7 @@ def test_both_config_name_found(self): {"Key": JumpStartTag.TRAINING_CONFIG_NAME, "Value": "training_config_name"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, "inference_config_name", "training_config_name"), ) @@ -1492,7 +1492,7 @@ def test_model_id_version_found(self): {"Key": JumpStartTag.MODEL_VERSION, "Value": "model_version"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), ("model_id", "model_version", None, None), ) @@ -1510,7 +1510,7 @@ def test_multiple_model_id_versions_found(self): {"Key": JumpStartTag.MODEL_VERSION, "Value": "model_version_2"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, None, None), ) @@ -1528,7 +1528,7 @@ def test_multiple_model_id_versions_found_aliases_consistent(self): {"Key": random.choice(EXTRA_MODEL_VERSION_TAGS), "Value": "model_version_1"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), ("model_id_1", "model_version_1", None, None), ) @@ -1546,7 +1546,7 @@ def test_multiple_model_id_versions_found_aliases_inconsistent(self): {"Key": random.choice(EXTRA_MODEL_VERSION_TAGS), "Value": "model_version_2"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), (None, None, None, None), ) @@ -1564,7 +1564,7 @@ def test_multiple_config_names_found_aliases_inconsistent(self): {"Key": JumpStartTag.INFERENCE_CONFIG_NAME, "Value": "config_name_2"}, ] - self.assertEquals( + self.assertEqual( utils.get_jumpstart_model_info_from_resource_arn("some-arn", mock_sagemaker_session), ("model_id_1", "model_version_1", None, None), ) diff --git a/tests/unit/sagemaker/local/test_local_entities.py b/tests/unit/sagemaker/local/test_local_entities.py index 6a026c316b..74a361cf73 100644 --- a/tests/unit/sagemaker/local/test_local_entities.py +++ b/tests/unit/sagemaker/local/test_local_entities.py @@ -12,6 +12,7 @@ # language governing permissions and limitations under the License. from __future__ import absolute_import +import re import os import pytest @@ -290,10 +291,10 @@ def test_start_local_pipeline_with_wrong_parameter_type(sagemaker_local_session) local_pipeline = sagemaker.local.entities._LocalPipeline(pipeline) with pytest.raises(ClientError) as error: local_pipeline.start(PipelineParameters={"MyStr": True}) - assert ( - f"Unexpected type for parameter '{parameter.name}'. Expected " - f"{parameter.parameter_type.python_type} but found {type(True)}." in str(error.value) + expected_error_pattern = ( + r"Unexpected type for parameter 'MyStr'\. Expected .* but found \." ) + assert re.search(expected_error_pattern, str(error.value)) def test_start_local_pipeline_with_empty_parameter_string_value( diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 770420c354..13530a3983 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -1049,15 +1049,16 @@ def mock_upload_data(path, bucket, key_prefix): model_trainer.train() - assert mock_local_container.train.called_once_with( + mock_local_container.assert_called_once_with( training_job_name=unique_name, instance_type=compute.instance_type, instance_count=compute.instance_count, image=training_image, container_root=local_container_root, sagemaker_session=modules_session, - container_entry_point=DEFAULT_ENTRYPOINT, + container_entrypoint=DEFAULT_ENTRYPOINT, container_arguments=DEFAULT_ARGUMENTS, + input_data_config=ANY, hyper_parameters=hyperparameters, environment=environment, ) diff --git a/tests/unit/sagemaker/serve/detector/test_dependency_manager.py b/tests/unit/sagemaker/serve/detector/test_dependency_manager.py index 491968dd25..52e9822e57 100644 --- a/tests/unit/sagemaker/serve/detector/test_dependency_manager.py +++ b/tests/unit/sagemaker/serve/detector/test_dependency_manager.py @@ -21,7 +21,7 @@ DEPENDENCY_LIST = [ "requests==2.26.0", - "numpy>=1.20.0", + "numpy==1.26.4", "pandas<=1.3.3", "matplotlib<3.5.0", "scikit-learn>0.24.1", @@ -34,7 +34,7 @@ EXPECTED_DEPENDENCY_MAP = { "requests": "==2.26.0", - "numpy": ">=1.20.0", + "numpy": "==1.26.4", "pandas": "<=1.3.3", "matplotlib": "<3.5.0", "scikit-learn": ">0.24.1", diff --git a/tests/unit/sagemaker/serve/detector/test_pickle_dependencies.py b/tests/unit/sagemaker/serve/detector/test_pickle_dependencies.py index 34cab8a526..ced9555fc5 100644 --- a/tests/unit/sagemaker/serve/detector/test_pickle_dependencies.py +++ b/tests/unit/sagemaker/serve/detector/test_pickle_dependencies.py @@ -93,13 +93,14 @@ def create_mock_modules(name, doc, file): # happy case def test_generate_requirements_exact_match(monkeypatch): - with patch("cloudpickle.load"), patch("tqdm.tqdm"), patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.run" - ) as subprocess_run, patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.Popen" - ) as subprocess_popen, patch( - "builtins.open" - ) as mocked_open, monkeypatch.context() as m: + with ( + patch("cloudpickle.load"), + patch("tqdm.tqdm"), + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.run") as subprocess_run, + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.Popen") as subprocess_popen, + patch("builtins.open") as mocked_open, + monkeypatch.context() as m, + ): mock_run_stdout = MagicMock() mock_run_stdout.stdout = json.dumps(INSTALLED_PKG_JSON).encode("utf-8") subprocess_run.return_value = mock_run_stdout @@ -147,13 +148,14 @@ def test_generate_requirements_exact_match(monkeypatch): def test_generate_requirements_txt_pruning_unused_packages(monkeypatch): - with patch("cloudpickle.load"), patch("tqdm.tqdm"), patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.run" - ) as subprocess_run, patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.Popen" - ) as subprocess_popen, patch( - "builtins.open" - ) as mocked_open, monkeypatch.context() as m: + with ( + patch("cloudpickle.load"), + patch("tqdm.tqdm"), + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.run") as subprocess_run, + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.Popen") as subprocess_popen, + patch("builtins.open") as mocked_open, + monkeypatch.context() as m, + ): mock_run_stdout = MagicMock() mock_run_stdout.stdout = json.dumps(INSTALLED_PKG_JSON_UNUSED).encode("utf-8") subprocess_run.return_value = mock_run_stdout @@ -201,13 +203,14 @@ def test_generate_requirements_txt_pruning_unused_packages(monkeypatch): def test_generate_requirements_txt_no_currently_used_packages(monkeypatch): - with patch("cloudpickle.load"), patch("tqdm.tqdm"), patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.run" - ) as subprocess_run, patch( - "sagemaker.serve.detector.pickle_dependencies.subprocess.Popen" - ) as subprocess_popen, patch( - "builtins.open" - ) as mocked_open, monkeypatch.context() as m: + with ( + patch("cloudpickle.load"), + patch("tqdm.tqdm"), + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.run") as subprocess_run, + patch("sagemaker.serve.detector.pickle_dependencies.subprocess.Popen") as subprocess_popen, + patch("builtins.open") as mocked_open, + monkeypatch.context() as m, + ): mock_run_stdout = MagicMock() mock_run_stdout.stdout = json.dumps([]).encode("utf-8") subprocess_run.return_value = mock_run_stdout diff --git a/tests/unit/sagemaker/serve/model_server/djl_serving/test_djl_prepare.py b/tests/unit/sagemaker/serve/model_server/djl_serving/test_djl_prepare.py index 183d15d13e..aa99e1971c 100644 --- a/tests/unit/sagemaker/serve/model_server/djl_serving/test_djl_prepare.py +++ b/tests/unit/sagemaker/serve/model_server/djl_serving/test_djl_prepare.py @@ -52,8 +52,8 @@ def test_create_dir_structure_from_new(self, mock_path, mock_disk_usage, mock_di mock_disk_space.assert_called_once_with(mock_model_path) mock_disk_usage.assert_called_once() - self.assertEquals(ret_model_path, mock_model_path) - self.assertEquals(ret_code_dir, mock_code_dir) + self.assertEqual(ret_model_path, mock_model_path) + self.assertEqual(ret_code_dir, mock_code_dir) @patch("sagemaker.serve.model_server.djl_serving.prepare.Path") def test_create_dir_structure_invalid_path(self, mock_path): @@ -65,7 +65,7 @@ def test_create_dir_structure_invalid_path(self, mock_path): with self.assertRaises(ValueError) as context: _create_dir_structure(mock_model_path) - self.assertEquals("model_dir is not a valid directory", str(context.exception)) + self.assertEqual("model_dir is not a valid directory", str(context.exception)) @patch("sagemaker.serve.model_server.djl_serving.prepare.S3Downloader") @patch("builtins.open", new_callable=mock_open, read_data="data") diff --git a/tests/unit/sagemaker/serve/model_server/multi_model_server/test_multi_model_server_prepare.py b/tests/unit/sagemaker/serve/model_server/multi_model_server/test_multi_model_server_prepare.py index e877c1e7e9..567a72182a 100644 --- a/tests/unit/sagemaker/serve/model_server/multi_model_server/test_multi_model_server_prepare.py +++ b/tests/unit/sagemaker/serve/model_server/multi_model_server/test_multi_model_server_prepare.py @@ -91,8 +91,8 @@ def test_create_dir_structure_from_new(self, mock_path, mock_disk_usage, mock_di mock_disk_space.assert_called_once_with(mock_model_path) mock_disk_usage.assert_called_once() - self.assertEquals(ret_model_path, mock_model_path) - self.assertEquals(ret_code_dir, mock_code_dir) + self.assertEqual(ret_model_path, mock_model_path) + self.assertEqual(ret_code_dir, mock_code_dir) @patch("sagemaker.serve.model_server.multi_model_server.prepare.Path") def test_create_dir_structure_invalid_path(self, mock_path): @@ -104,4 +104,4 @@ def test_create_dir_structure_invalid_path(self, mock_path): with self.assertRaises(ValueError) as context: _create_dir_structure(mock_model_path) - self.assertEquals("model_dir is not a valid directory", str(context.exception)) + self.assertEqual("model_dir is not a valid directory", str(context.exception)) diff --git a/tests/unit/sagemaker/serve/model_server/tgi/test_tgi_prepare.py b/tests/unit/sagemaker/serve/model_server/tgi/test_tgi_prepare.py index 88d109831d..ed94f10ce9 100644 --- a/tests/unit/sagemaker/serve/model_server/tgi/test_tgi_prepare.py +++ b/tests/unit/sagemaker/serve/model_server/tgi/test_tgi_prepare.py @@ -50,8 +50,8 @@ def test_create_dir_structure_from_new(self, mock_path, mock_disk_usage, mock_di mock_disk_space.assert_called_once_with(mock_model_path) mock_disk_usage.assert_called_once() - self.assertEquals(ret_model_path, mock_model_path) - self.assertEquals(ret_code_dir, mock_code_dir) + self.assertEqual(ret_model_path, mock_model_path) + self.assertEqual(ret_code_dir, mock_code_dir) @patch("sagemaker.serve.model_server.tgi.prepare.Path") def test_create_dir_structure_invalid_path(self, mock_path): @@ -63,7 +63,7 @@ def test_create_dir_structure_invalid_path(self, mock_path): with self.assertRaises(ValueError) as context: _create_dir_structure(mock_model_path) - self.assertEquals("model_dir is not a valid directory", str(context.exception)) + self.assertEqual("model_dir is not a valid directory", str(context.exception)) @patch("sagemaker.serve.model_server.tgi.prepare.S3Downloader") @patch("builtins.open", read_data="data") diff --git a/tests/unit/sagemaker/workflow/test_pipeline.py b/tests/unit/sagemaker/workflow/test_pipeline.py index 14c2d442eb..523b981736 100644 --- a/tests/unit/sagemaker/workflow/test_pipeline.py +++ b/tests/unit/sagemaker/workflow/test_pipeline.py @@ -99,7 +99,7 @@ def test_pipeline_create_and_update_with_config_injection(sagemaker_session_mock RoleArn=pipeline_role_arn, ) pipeline.upsert() - assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.update_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=pipeline_role_arn, @@ -130,7 +130,7 @@ def test_pipeline_create_with_parallelism_config(sagemaker_session_mock, role_ar role_arn=role_arn, parallelism_config=dict(MaxParallelExecutionSteps=10), ) - assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.create_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn, @@ -149,7 +149,7 @@ def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_moc role_arn=role_arn, parallelism_config=dict(MaxParallelExecutionSteps=10), ) - assert sagemaker_session_mock.sagemaker_client.create_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.create_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn, @@ -168,7 +168,7 @@ def test_pipeline_create_and_start_with_parallelism_config(sagemaker_session_moc # Specify ParallelismConfiguration to another value which will be honored in backend pipeline.start(parallelism_config=dict(MaxParallelExecutionSteps=20)) - assert sagemaker_session_mock.sagemaker_client.start_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.start_pipeline_execution.assert_called_with( PipelineName="MyPipeline", ParallelismConfiguration={"MaxParallelExecutionSteps": 20}, ) @@ -209,7 +209,7 @@ def test_pipeline_update(sagemaker_session_mock, role_arn): assert not pipeline.steps pipeline.update(role_arn=role_arn) assert len(json.loads(pipeline.definition())["Steps"]) == 0 - assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.update_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn ) @@ -253,7 +253,7 @@ def test_pipeline_update(sagemaker_session_mock, role_arn): pipeline.update(role_arn=role_arn) assert len(json.loads(pipeline.definition())["Steps"]) == 3 - assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.update_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn ) @@ -345,7 +345,11 @@ def test_pipeline_update_with_parallelism_config(sagemaker_session_mock, role_ar role_arn=role_arn, parallelism_config=dict(MaxParallelExecutionSteps=10), ) - assert sagemaker_session_mock.sagemaker_client.update_pipeline.called_with( + pipeline.update( + role_arn=role_arn, + parallelism_config={"MaxParallelExecutionSteps": 10}, + ) + sagemaker_session_mock.sagemaker_client.update_pipeline.assert_called_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn, @@ -418,13 +422,11 @@ def _raise_does_already_exists_client_error(**kwargs): sagemaker_session_mock.sagemaker_client.update_pipeline.assert_called_once_with( PipelineName="MyPipeline", PipelineDefinition=pipeline.definition(), RoleArn=role_arn ) - assert sagemaker_session_mock.sagemaker_client.list_tags.called_with( - ResourceArn="mock_pipeline_arn" - ) + sagemaker_session_mock.sagemaker_client.list_tags.assert_called_with(ResourceArn="pipeline-arn") tags.append({"Key": "dummy", "Value": "dummy_tag"}) - assert sagemaker_session_mock.sagemaker_client.add_tags.called_with( - ResourceArn="mock_pipeline_arn", Tags=tags + sagemaker_session_mock.sagemaker_client.add_tags.assert_called_with( + ResourceArn="pipeline-arn", Tags=tags ) @@ -523,7 +525,7 @@ def test_pipeline_delete(sagemaker_session_mock): sagemaker_session=sagemaker_session_mock, ) pipeline.delete() - assert sagemaker_session_mock.sagemaker_client.delete_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.delete_pipeline.assert_called_with( PipelineName="MyPipeline", ) @@ -536,7 +538,7 @@ def test_pipeline_describe(sagemaker_session_mock): sagemaker_session=sagemaker_session_mock, ) pipeline.describe() - assert sagemaker_session_mock.sagemaker_client.describe_pipeline.called_with( + sagemaker_session_mock.sagemaker_client.describe_pipeline.assert_called_with( PipelineName="MyPipeline", ) @@ -552,17 +554,17 @@ def test_pipeline_start(sagemaker_session_mock): sagemaker_session=sagemaker_session_mock, ) pipeline.start() - assert sagemaker_session_mock.start_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.start_pipeline_execution.assert_called_with( PipelineName="MyPipeline", ) pipeline.start(execution_display_name="pipeline-execution") - assert sagemaker_session_mock.start_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.start_pipeline_execution.assert_called_with( PipelineName="MyPipeline", PipelineExecutionDisplayName="pipeline-execution" ) pipeline.start(parameters=dict(alpha="epsilon")) - assert sagemaker_session_mock.start_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.start_pipeline_execution.assert_called_with( PipelineName="MyPipeline", PipelineParameters=[{"Name": "alpha", "Value": "epsilon"}] ) @@ -821,10 +823,8 @@ def test_pipeline_build_parameters_from_execution(sagemaker_session_mock): pipeline_execution_arn=reference_execution_arn, parameter_value_overrides=parameter_value_overrides, ) - assert ( - sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.called_with( - PipelineExecutionArn=reference_execution_arn - ) + sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.assert_called_with( + PipelineExecutionArn=reference_execution_arn ) assert len(parameters) == 1 assert parameters["TestParameterName"] == "NewParameterValue" @@ -850,10 +850,8 @@ def test_pipeline_build_parameters_from_execution_with_invalid_overrides(sagemak + f"are not present in the pipeline execution: {reference_execution_arn}" in str(error) ) - assert ( - sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.called_with( - PipelineExecutionArn=reference_execution_arn - ) + sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.assert_called_with( + PipelineExecutionArn=reference_execution_arn ) @@ -908,24 +906,23 @@ def test_pipeline_execution_basics(sagemaker_session_mock): ) execution = pipeline.start() execution.stop() - assert sagemaker_session_mock.sagemaker_client.stop_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.stop_pipeline_execution.assert_called_with( PipelineExecutionArn="my:arn" ) execution.describe() - assert sagemaker_session_mock.sagemaker_client.describe_pipeline_execution.called_with( + sagemaker_session_mock.sagemaker_client.describe_pipeline_execution.assert_called_with( PipelineExecutionArn="my:arn" ) steps = execution.list_steps() - assert sagemaker_session_mock.sagemaker_client.describe_pipeline_execution_steps.called_with( + sagemaker_session_mock.sagemaker_client.list_pipeline_execution_steps.assert_called_with( PipelineExecutionArn="my:arn" ) assert len(steps) == 1 list_parameters_response = execution.list_parameters() - assert ( - sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.called_with( - PipelineExecutionArn="my:arn" - ) + sagemaker_session_mock.sagemaker_client.list_pipeline_parameters_for_execution.assert_called_with( + PipelineExecutionArn="my:arn" ) + parameter_list = list_parameters_response["PipelineParameters"] assert len(parameter_list) == 1 assert parameter_list[0]["Name"] == "TestParameterName" diff --git a/tests/unit/test_exception_on_bad_status.py b/tests/unit/test_exception_on_bad_status.py index 2ef017efd3..dc53c97799 100644 --- a/tests/unit/test_exception_on_bad_status.py +++ b/tests/unit/test_exception_on_bad_status.py @@ -52,7 +52,7 @@ def test_raise_when_failed_created_package(): False ), "sagemaker.exceptions.UnexpectedStatusException should have been raised but was not" except Exception as e: - assert type(e) == sagemaker.exceptions.UnexpectedStatusException + assert isinstance(e, sagemaker.exceptions.UnexpectedStatusException) assert e.actual_status == "EnRoute" assert "Completed" in e.allowed_statuses @@ -73,7 +73,7 @@ def test_does_raise_when_incorrect_job_status(): False ), "sagemaker.exceptions.UnexpectedStatusException should have been raised but was not" except Exception as e: - assert type(e) == sagemaker.exceptions.UnexpectedStatusException + assert isinstance(e, sagemaker.exceptions.UnexpectedStatusException) assert e.actual_status == "Failed" assert "Completed" in e.allowed_statuses assert "Stopped" in e.allowed_statuses @@ -92,7 +92,7 @@ def test_does_raise_capacity_error_when_incorrect_job_status(): ) assert False, "sagemaker.exceptions.CapacityError should have been raised but was not" except Exception as e: - assert type(e) == sagemaker.exceptions.CapacityError + assert isinstance(e, sagemaker.exceptions.CapacityError) assert e.actual_status == "Failed" assert "Completed" in e.allowed_statuses assert "Stopped" in e.allowed_statuses @@ -114,6 +114,6 @@ def test_raise_when_failed_to_deploy_endpoint(): False ), "sagemaker.exceptions.UnexpectedStatusException should have been raised but was not" except Exception as e: - assert type(e) == sagemaker.exceptions.UnexpectedStatusException + assert isinstance(e, sagemaker.exceptions.UnexpectedStatusException) assert e.actual_status == "Failed" assert "InService" in e.allowed_statuses diff --git a/tests/unit/test_hyperparameter.py b/tests/unit/test_hyperparameter.py index ba7a363c40..edb2de97ee 100644 --- a/tests/unit/test_hyperparameter.py +++ b/tests/unit/test_hyperparameter.py @@ -62,7 +62,7 @@ def test_validated(): def test_data_type(): x = Test() x.validated = 66 - assert type(x.validated) == Test.__dict__["validated"].data_type + assert isinstance(x.validated, Test.__dict__["validated"].data_type) def test_from_string(): diff --git a/tests/unit/test_predictor_async.py b/tests/unit/test_predictor_async.py index fa2d6da6c7..c9f12ff023 100644 --- a/tests/unit/test_predictor_async.py +++ b/tests/unit/test_predictor_async.py @@ -233,7 +233,7 @@ def test_async_predict_call_verify_exceptions(): with pytest.raises( PollingTimeoutError, match=f"No result at {ASYNC_OUTPUT_LOCATION} after polling for " - f"{DEFAULT_WAITER_CONFIG.delay*DEFAULT_WAITER_CONFIG.max_attempts}" + f"{DEFAULT_WAITER_CONFIG.delay * DEFAULT_WAITER_CONFIG.max_attempts}" f" seconds. Inference could still be running", ): predictor_async.predict(input_path=input_location, waiter_config=DEFAULT_WAITER_CONFIG) @@ -253,7 +253,7 @@ def test_async_predict_call_verify_exceptions_with_null_failure_path(): with pytest.raises( PollingTimeoutError, match=f"No result at {ASYNC_OUTPUT_LOCATION} after polling for " - f"{DEFAULT_WAITER_CONFIG.delay*DEFAULT_WAITER_CONFIG.max_attempts}" + f"{DEFAULT_WAITER_CONFIG.delay * DEFAULT_WAITER_CONFIG.max_attempts}" f" seconds. Inference could still be running", ): predictor_async.predict(input_path=input_location, waiter_config=DEFAULT_WAITER_CONFIG) diff --git a/tests/unit/test_tuner.py b/tests/unit/test_tuner.py index f0325b79e9..b4d21008b5 100644 --- a/tests/unit/test_tuner.py +++ b/tests/unit/test_tuner.py @@ -46,7 +46,54 @@ from sagemaker.workflow.parameters import ParameterString, ParameterInteger from src.sagemaker.tuner import InstanceConfig -from .tuner_test_utils import * # noqa: F403 +from .tuner_test_utils import ( + BASE_JOB_NAME, + BUCKET_NAME, + CategoricalParameter, + ContinuousParameter, + DATA_DIR, + EARLY_STOPPING_TYPE, + Estimator, + ESTIMATOR, + ESTIMATOR_NAME, + ESTIMATOR_NAME_TWO, + ESTIMATOR_TWO, + FRAMEWORK_VERSION, + HYPERPARAMETER_RANGES, + HYPERPARAMETER_RANGES_TWO, + IMAGE_NAME, + INPUTS, + INSTANCE_COUNT, + INSTANCE_TYPE, + IntegerParameter, + JOB_NAME, + LIST_TAGS_RESULT, + MAX_JOBS, + MAX_PARALLEL_JOBS, + METRIC_DEFINITIONS, + MODEL_DATA, + MULTI_ALGO_TUNING_JOB_DETAILS, + NUM_COMPONENTS, + OBJECTIVE_METRIC_NAME, + OBJECTIVE_METRIC_NAME_TWO, + OBJECTIVE_TYPE, + PCA, + PY_VERSION, + REGION, + ROLE, + SAGEMAKER_SESSION, + SCRIPT_NAME, + STRATEGY, + TAGS, + TRAINING_JOB_DESCRIPTION, + TRAINING_JOB_NAME, + TUNING_JOB_DETAILS, + WarmStartConfig, + WarmStartTypes, + WARM_START_CONFIG, + ENDPOINT_DESC, + ENDPOINT_CONFIG_DESC, +) @pytest.fixture() diff --git a/tox.ini b/tox.ini index b16c0d2f0b..c47d206380 100644 --- a/tox.ini +++ b/tox.ini @@ -5,7 +5,7 @@ [tox] isolated_build = true -envlist = black-format,flake8,pylint,docstyle,sphinx,doc8,twine,py38,py39,py310,py311 +envlist = black-format,flake8,pylint,docstyle,sphinx,doc8,twine,py39,py310,py311,py312 skip_missing_interpreters = False @@ -21,13 +21,13 @@ exclude = tests/data/ venv/ env/ - tests/unit/test_tensorboard.py # excluding this file for time being + tests/unit/test_tensorboard.py max-complexity = 10 ignore = C901, - E203, # whitespace before ':': Black disagrees with and explicitly violates this. + E203, FI10, FI12, FI13, @@ -35,7 +35,7 @@ ignore = FI15, FI16, FI17, - FI18, # __future__ import "annotations" missing -> check only Python 3.7 compatible + FI18, FI50, FI51, FI52, @@ -67,7 +67,7 @@ markers = [testenv] setenv = PYTHONHASHSEED=42 -pip_version = pip==21.3 +pip_version = pip==24.3 passenv = AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY @@ -82,15 +82,18 @@ passenv = # Can be used to specify which tests to run, e.g.: tox -- -s commands = python -c "import os; os.system('install-custom-pkgs --install-boto-wheels')" - pip install 'apache-airflow==2.9.3' --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.9.3/constraints-3.8.txt" - pip install 'torch==2.0.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' - pip install 'torchvision==0.15.2+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' - pip install 'dill>=0.3.8' + pip install 'apache-airflow==2.10.4' --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.10.4/constraints-3.9.txt" + pip install 'torch==2.3.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' + pip install 'torchvision==0.18.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' + pip install 'dill>=0.3.9' pytest {posargs} deps = .[test] depends = - {py38,py39,py310,p311}: clean + {py39,py310,py311,py312}: clean + +[testenv:py312] +basepython = python3.12 [testenv:runcoverage] description = run unit tests with coverage @@ -105,6 +108,7 @@ deps = -r requirements/tox/flake8_requirements.txt commands = flake8 +basepython = python3.12 [testenv:pylint] skipdist = true @@ -112,7 +116,7 @@ skip_install = true deps = -r requirements/tox/pylint_requirements.txt commands = - python -m pylint --rcfile=.pylintrc -j 0 src/sagemaker + python -m pylint --rcfile=.pylintrc -j 0 src/sagemaker --fail-under=9.9 [testenv:spelling] skipdist = true @@ -132,14 +136,14 @@ commands = twine check dist/*.tar.gz [testenv:sphinx] -pip_version = pip==21.3 +pip_version = pip==24.3 changedir = doc # pip install requirements.txt is separate as RTD does it in separate steps # having the requirements.txt installed in deps above results in Double Requirement exception # https://github.com/pypa/pip/issues/988 commands = pip install --exists-action=w -r requirements.txt - sphinx-build -T -W -b html -d _build/doctrees-readthedocs -D language=en . _build/html + sphinx-build -T -b html -d _build/doctrees-readthedocs -D language=en . _build/html [testenv:doc8] deps = From 06801a4936bed9bccf8b41e6eb9651bdf0691aa2 Mon Sep 17 00:00:00 2001 From: rsareddy0329 Date: Sat, 19 Apr 2025 19:11:58 -0700 Subject: [PATCH 061/164] Revert the PR changes 5122 (#5134) * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * documentation: Removed a line about python version requirements of training script which can misguide users.Training script can be of latest version based on the support provided by framework_version of the container * feature: Enabled update_endpoint through model_builder * fix: fix unit test, black-check, pylint errors * fix: fix black-check, pylint errors * fix:Added handler for pipeline variable while creating process job * fix: Added handler for pipeline variable while creating process job * Revert the PR changes: #5122, due to issue https://t.corp.amazon.com/P223568185/overview * Fix: fix the issue, https://t.corp.amazon.com/P223568185/communication * Revert PR 5122 changes, due to issues with other processor codeflows --------- Co-authored-by: Roja Reddy Sareddy Co-authored-by: Zhaoqi --- src/sagemaker/processing.py | 11 - .../workflow/test_processing_step.py | 18 +- tests/unit/test_processing.py | 249 +----------------- 3 files changed, 3 insertions(+), 275 deletions(-) diff --git a/src/sagemaker/processing.py b/src/sagemaker/processing.py index eda4ffc01e..103be47caf 100644 --- a/src/sagemaker/processing.py +++ b/src/sagemaker/processing.py @@ -17,7 +17,6 @@ and interpretation on Amazon SageMaker. """ from __future__ import absolute_import -import json import logging import os import pathlib @@ -315,16 +314,6 @@ def _normalize_args( + "rather than a pipeline variable" ) - if arguments is not None: - processed_arguments = [] - for arg in arguments: - if isinstance(arg, PipelineVariable): - processed_value = json.dumps(arg.expr) - processed_arguments.append(processed_value) - else: - processed_arguments.append(arg) - arguments = processed_arguments - self._current_job_name = self._generate_current_job_name(job_name=job_name) inputs_with_code = self._include_code_in_inputs(inputs, code, kms_key) diff --git a/tests/unit/sagemaker/workflow/test_processing_step.py b/tests/unit/sagemaker/workflow/test_processing_step.py index 9ee8242a45..0dcd7c2495 100644 --- a/tests/unit/sagemaker/workflow/test_processing_step.py +++ b/tests/unit/sagemaker/workflow/test_processing_step.py @@ -825,13 +825,6 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session): processor.sagemaker_session = pipeline_session processor.role = ROLE - arguments_output = [ - "--input", - "input-data-uri", - "--output", - '{"Get": "Parameters.MyArgOutput"}', - ] - run_inputs["inputs"] = processing_input step_args = processor.run(**run_inputs) @@ -842,7 +835,7 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session): step_args = get_step_args_helper(step_args, "Processing") - assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output + assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"] entry_points = step_args["AppSpecification"]["ContainerEntrypoint"] entry_points_expr = [] @@ -1027,13 +1020,6 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_ processor.sagemaker_session = pipeline_session processor.role = ROLE - arguments_output = [ - "--input", - "input-data-uri", - "--output", - '{"Get": "Parameters.MyArgOutput"}', - ] - run_inputs["inputs"] = processing_input step_args = processor.run(**run_inputs) @@ -1044,7 +1030,7 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_ step_args = get_step_args_helper(step_args, "Processing") - assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output + assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"] entry_points = step_args["AppSpecification"]["ContainerEntrypoint"] entry_points_expr = [] diff --git a/tests/unit/test_processing.py b/tests/unit/test_processing.py index 7b020c61bf..06d2cde02e 100644 --- a/tests/unit/test_processing.py +++ b/tests/unit/test_processing.py @@ -46,9 +46,8 @@ from sagemaker.fw_utils import UploadedCode from sagemaker.workflow.pipeline_context import PipelineSession, _PipelineConfig from sagemaker.workflow.functions import Join -from sagemaker.workflow.execution_variables import ExecutionVariable, ExecutionVariables +from sagemaker.workflow.execution_variables import ExecutionVariables from tests.unit import SAGEMAKER_CONFIG_PROCESSING_JOB -from sagemaker.workflow.parameters import ParameterString BUCKET_NAME = "mybucket" REGION = "us-west-2" @@ -1718,249 +1717,3 @@ def _get_describe_response_inputs_and_ouputs(): "ProcessingInputs": _get_expected_args_all_parameters(None)["inputs"], "ProcessingOutputConfig": _get_expected_args_all_parameters(None)["output_config"], } - - -# Parameters -def _get_data_inputs_with_parameters(): - return [ - ProcessingInput( - source=ParameterString(name="input_data", default_value="s3://dummy-bucket/input"), - destination="/opt/ml/processing/input", - input_name="input-1", - ) - ] - - -def _get_data_outputs_with_parameters(): - return [ - ProcessingOutput( - source="/opt/ml/processing/output", - destination=ParameterString( - name="output_data", default_value="s3://dummy-bucket/output" - ), - output_name="output-1", - ) - ] - - -def _get_expected_args_with_parameters(job_name): - return { - "inputs": [ - { - "InputName": "input-1", - "S3Input": { - "S3Uri": "s3://dummy-bucket/input", - "LocalPath": "/opt/ml/processing/input", - "S3DataType": "S3Prefix", - "S3InputMode": "File", - "S3DataDistributionType": "FullyReplicated", - "S3CompressionType": "None", - }, - } - ], - "output_config": { - "Outputs": [ - { - "OutputName": "output-1", - "S3Output": { - "S3Uri": "s3://dummy-bucket/output", - "LocalPath": "/opt/ml/processing/output", - "S3UploadMode": "EndOfJob", - }, - } - ] - }, - "job_name": job_name, - "resources": { - "ClusterConfig": { - "InstanceType": "ml.m4.xlarge", - "InstanceCount": 1, - "VolumeSizeInGB": 100, - "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", - } - }, - "stopping_condition": {"MaxRuntimeInSeconds": 3600}, - "app_specification": { - "ImageUri": "custom-image-uri", - "ContainerArguments": [ - "--input-data", - "s3://dummy-bucket/input-param", - "--output-path", - "s3://dummy-bucket/output-param", - ], - "ContainerEntrypoint": ["python3"], - }, - "environment": {"my_env_variable": "my_env_variable_value"}, - "network_config": { - "EnableNetworkIsolation": True, - "EnableInterContainerTrafficEncryption": True, - "VpcConfig": { - "Subnets": ["my_subnet_id"], - "SecurityGroupIds": ["my_security_group_id"], - }, - }, - "role_arn": "dummy/role", - "tags": [{"Key": "my-tag", "Value": "my-tag-value"}], - "experiment_config": {"ExperimentName": "AnExperiment"}, - } - - -@patch("os.path.exists", return_value=True) -@patch("os.path.isfile", return_value=True) -@patch("sagemaker.utils.repack_model") -@patch("sagemaker.utils.create_tar_file") -@patch("sagemaker.session.Session.upload_data") -def test_script_processor_with_parameter_string( - upload_data_mock, - create_tar_file_mock, - repack_model_mock, - exists_mock, - isfile_mock, - sagemaker_session, -): - """Test ScriptProcessor with ParameterString arguments""" - upload_data_mock.return_value = "s3://mocked_s3_uri_from_upload_data" - - # Setup processor - processor = ScriptProcessor( - role="arn:aws:iam::012345678901:role/SageMakerRole", # Updated role ARN - image_uri="custom-image-uri", - command=["python3"], - instance_type="ml.m4.xlarge", - instance_count=1, - volume_size_in_gb=100, - volume_kms_key="arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", - output_kms_key="arn:aws:kms:us-west-2:012345678901:key/output-kms-key", - max_runtime_in_seconds=3600, - base_job_name="test_processor", - env={"my_env_variable": "my_env_variable_value"}, - tags=[{"Key": "my-tag", "Value": "my-tag-value"}], - network_config=NetworkConfig( - subnets=["my_subnet_id"], - security_group_ids=["my_security_group_id"], - enable_network_isolation=True, - encrypt_inter_container_traffic=True, - ), - sagemaker_session=sagemaker_session, - ) - - input_param = ParameterString(name="input_param", default_value="s3://dummy-bucket/input-param") - output_param = ParameterString( - name="output_param", default_value="s3://dummy-bucket/output-param" - ) - exec_var = ExecutionVariable(name="ExecutionTest") - join_var = Join(on="/", values=["s3://bucket", "prefix", "file.txt"]) - dummy_str_var = "test-variable" - - # Define expected arguments - expected_args = { - "inputs": [ - { - "InputName": "input-1", - "AppManaged": False, - "S3Input": { - "S3Uri": ParameterString( - name="input_data", default_value="s3://dummy-bucket/input" - ), - "LocalPath": "/opt/ml/processing/input", - "S3DataType": "S3Prefix", - "S3InputMode": "File", - "S3DataDistributionType": "FullyReplicated", - "S3CompressionType": "None", - }, - }, - { - "InputName": "code", - "AppManaged": False, - "S3Input": { - "S3Uri": "s3://mocked_s3_uri_from_upload_data", - "LocalPath": "/opt/ml/processing/input/code", - "S3DataType": "S3Prefix", - "S3InputMode": "File", - "S3DataDistributionType": "FullyReplicated", - "S3CompressionType": "None", - }, - }, - ], - "output_config": { - "Outputs": [ - { - "OutputName": "output-1", - "AppManaged": False, - "S3Output": { - "S3Uri": ParameterString( - name="output_data", default_value="s3://dummy-bucket/output" - ), - "LocalPath": "/opt/ml/processing/output", - "S3UploadMode": "EndOfJob", - }, - } - ], - "KmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/output-kms-key", - }, - "job_name": "test_job", - "resources": { - "ClusterConfig": { - "InstanceType": "ml.m4.xlarge", - "InstanceCount": 1, - "VolumeSizeInGB": 100, - "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key", - } - }, - "stopping_condition": {"MaxRuntimeInSeconds": 3600}, - "app_specification": { - "ImageUri": "custom-image-uri", - "ContainerArguments": [ - "--input-data", - '{"Get": "Parameters.input_param"}', - "--output-path", - '{"Get": "Parameters.output_param"}', - "--exec-arg", - '{"Get": "Execution.ExecutionTest"}', - "--join-arg", - '{"Std:Join": {"On": "/", "Values": ["s3://bucket", "prefix", "file.txt"]}}', - "--string-param", - "test-variable", - ], - "ContainerEntrypoint": ["python3", "/opt/ml/processing/input/code/processing_code.py"], - }, - "environment": {"my_env_variable": "my_env_variable_value"}, - "network_config": { - "EnableNetworkIsolation": True, - "EnableInterContainerTrafficEncryption": True, - "VpcConfig": { - "SecurityGroupIds": ["my_security_group_id"], - "Subnets": ["my_subnet_id"], - }, - }, - "role_arn": "arn:aws:iam::012345678901:role/SageMakerRole", - "tags": [{"Key": "my-tag", "Value": "my-tag-value"}], - "experiment_config": {"ExperimentName": "AnExperiment"}, - } - - # Run processor - processor.run( - code="/local/path/to/processing_code.py", - inputs=_get_data_inputs_with_parameters(), - outputs=_get_data_outputs_with_parameters(), - arguments=[ - "--input-data", - input_param, - "--output-path", - output_param, - "--exec-arg", - exec_var, - "--join-arg", - join_var, - "--string-param", - dummy_str_var, - ], - wait=True, - logs=False, - job_name="test_job", - experiment_config={"ExperimentName": "AnExperiment"}, - ) - - # Assert - sagemaker_session.process.assert_called_with(**expected_args) - assert "test_job" in processor._current_job_name From ba559e64e27ea1e646bd2a2032a897a1d221024f Mon Sep 17 00:00:00 2001 From: Molly He Date: Mon, 21 Apr 2025 17:53:09 -0700 Subject: [PATCH 062/164] update readme to reflect py312 upgrade --- README.rst | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.rst b/README.rst index 68cf79c55b..f115b1f25b 100644 --- a/README.rst +++ b/README.rst @@ -94,10 +94,10 @@ Supported Python Versions SageMaker Python SDK is tested on: -- Python 3.8 - Python 3.9 - Python 3.10 - Python 3.11 +- Python 3.12 Telemetry ~~~~~~~~~~~~~~~ @@ -191,9 +191,9 @@ Setup a Python environment, and install the dependencies listed in ``doc/require :: # conda - conda create -n sagemaker python=3.7 + conda create -n sagemaker python=3.12 conda activate sagemaker - conda install sphinx=3.1.1 sphinx_rtd_theme=0.5.0 + conda install sphinx=5.1.1 sphinx_rtd_theme=0.5.0 # pip pip install -r doc/requirements.txt From 57f483dc7611cb7c204c0facf266444afcf70f9c Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 23 Apr 2025 13:35:58 +0000 Subject: [PATCH 063/164] prepare release v2.243.3 --- CHANGELOG.md | 12 ++++++++++++ VERSION | 2 +- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index e59d964bd1..7db2fff71d 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,17 @@ # Changelog +## v2.243.3 (2025-04-23) + +### Bug Fixes and Other Changes + + * update readme to reflect py312 upgrade + * Revert the PR changes 5122 + * Py312 upgrade step 2: Update dependencies, integ tests and unit tests + * update pr test to deprecate py38 and add py312 + * update image_uri_configs 04-16-2025 07:18:18 PST + * update image_uri_configs 04-15-2025 07:18:10 PST + * update image_uri_configs 04-11-2025 07:18:19 PST + ## v2.243.2 (2025-04-16) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index 4e55ec1ee4..d65cfeaf42 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.3.dev0 +2.243.3 From 201500ce1cb6abd77f3e03a96b13a2f5dccbaf62 Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 23 Apr 2025 13:36:03 +0000 Subject: [PATCH 064/164] update development version to v2.243.4.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index d65cfeaf42..250b3d6920 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.3 +2.243.4.dev0 From 15cb303f9283960ecb19c596f35b858b7e83bc04 Mon Sep 17 00:00:00 2001 From: varunmoris <176621270+varunmoris@users.noreply.github.com> Date: Wed, 23 Apr 2025 16:31:26 -0400 Subject: [PATCH 065/164] chore: add huggingface images (#5142) --- .../image_uri_config/huggingface.json | 153 +++++++++++++++++- 1 file changed, 151 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface.json b/src/sagemaker/image_uri_config/huggingface.json index c314436346..475a82aeec 100644 --- a/src/sagemaker/image_uri_config/huggingface.json +++ b/src/sagemaker/image_uri_config/huggingface.json @@ -14,7 +14,9 @@ "4.26": "4.26.0", "4.28": "4.28.1", "4.36": "4.36.0", - "4.46": "4.46.1" + "4.46": "4.46.1", + "4.48": "4.48.0", + "4.49": "4.49.0" }, "versions": { "4.4.2": { @@ -1066,6 +1068,100 @@ "gpu": "cu121-ubuntu20.04" } } + }, + "4.48.0": { + "version_aliases": { + "pytorch2.3": "pytorch2.3.0" + }, + "pytorch2.3.0": { + "py_versions": [ + "py311" + ], + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "me-central-1": "914824155844", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "huggingface-pytorch-training", + "container_version": { + "gpu": "cu121-ubuntu20.04" + } + } + }, + "4.49.0": { + "version_aliases": { + "pytorch2.5": "pytorch2.5.1" + }, + "pytorch2.5.1": { + "py_versions": [ + "py311" + ], + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "me-central-1": "914824155844", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "huggingface-pytorch-training", + "container_version": { + "gpu": "cu124-ubuntu22.04" + } + } } } }, @@ -1082,7 +1178,8 @@ "4.17": "4.17.0", "4.26": "4.26.0", "4.28": "4.28.1", - "4.37": "4.37.0" + "4.37": "4.37.0", + "4.49": "4.49.0" }, "versions": { "4.6.1": { @@ -1983,6 +2080,58 @@ "cpu": "ubuntu22.04" } } + }, + "4.49.0": { + "version_aliases": { + "pytorch2.6": "pytorch2.6.0" + }, + "pytorch2.6.0": { + "py_versions": [ + "py312" + ], + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "me-south-1": "217643126080", + "me-central-1": "914824155844", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "huggingface-pytorch-inference", + "container_version": { + "gpu": "cu124-ubuntu22.04", + "cpu": "ubuntu22.04" + } + } } } } From 8120f6cbc989116876b1a4f4dedc47d753525852 Mon Sep 17 00:00:00 2001 From: Molly He Date: Fri, 25 Apr 2025 14:50:42 -0700 Subject: [PATCH 066/164] Update ModelTrainer to support s3 uri and tar.gz file as source_dir (#5144) * add s3 uri check to modeltrainer data source * update ModelTrainer to support s3 uri and tar.gz file as source_dir * black-format * add unit and integ tests * update logic and unit test to raise value error if the file is not .tar.gz --- src/sagemaker/modules/configs.py | 3 +- src/sagemaker/modules/train/model_trainer.py | 64 ++++++++++++------ tests/data/modules/script_mode/code.tar.gz | Bin 0 -> 37983 bytes .../modules/train/test_model_trainer.py | 18 +++++ .../modules/train/test_model_trainer.py | 55 +++++++++++++-- 5 files changed, 112 insertions(+), 28 deletions(-) create mode 100644 tests/data/modules/script_mode/code.tar.gz diff --git a/src/sagemaker/modules/configs.py b/src/sagemaker/modules/configs.py index 458c596a36..ac54e2ad0b 100644 --- a/src/sagemaker/modules/configs.py +++ b/src/sagemaker/modules/configs.py @@ -88,7 +88,8 @@ class SourceCode(BaseConfig): Parameters: source_dir (Optional[str]): - The local directory containing the source code to be used in the training job container. + The local directory, s3 uri, or path to tar.gz file stored locally or in s3 that contains + the source code to be used in the training job container. requirements (Optional[str]): The path within ``source_dir`` to a ``requirements.txt`` file. If specified, the listed requirements will be installed in the training job container. diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index aef6e3312b..4183fb87cd 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -407,28 +407,45 @@ def _validate_source_code(self, source_code: Optional[SourceCode]): "If 'requirements' or 'entry_script' is provided in 'source_code', " + "'source_dir' must also be provided.", ) - if not _is_valid_path(source_dir, path_type="Directory"): + if not ( + _is_valid_path(source_dir, path_type="Directory") + or _is_valid_s3_uri(source_dir, path_type="Directory") + or ( + _is_valid_path(source_dir, path_type="File") + and source_dir.endswith(".tar.gz") + ) + or ( + _is_valid_s3_uri(source_dir, path_type="File") + and source_dir.endswith(".tar.gz") + ) + ): raise ValueError( - f"Invalid 'source_dir' path: {source_dir}. " + "Must be a valid directory.", + f"Invalid 'source_dir' path: {source_dir}. " + + "Must be a valid local directory, " + "s3 uri or path to tar.gz file stored locally or in s3.", ) if requirements: - if not _is_valid_path( - f"{source_dir}/{requirements}", - path_type="File", - ): - raise ValueError( - f"Invalid 'requirements': {requirements}. " - + "Must be a valid file within the 'source_dir'.", - ) + if not source_dir.endswith(".tar.gz"): + if not _is_valid_path( + f"{source_dir}/{requirements}", path_type="File" + ) and not _is_valid_s3_uri( + f"{source_dir}/{requirements}", path_type="File" + ): + raise ValueError( + f"Invalid 'requirements': {requirements}. " + + "Must be a valid file within the 'source_dir'.", + ) if entry_script: - if not _is_valid_path( - f"{source_dir}/{entry_script}", - path_type="File", - ): - raise ValueError( - f"Invalid 'entry_script': {entry_script}. " - + "Must be a valid file within the 'source_dir'.", - ) + if not source_dir.endswith(".tar.gz"): + if not _is_valid_path( + f"{source_dir}/{entry_script}", path_type="File" + ) and not _is_valid_s3_uri( + f"{source_dir}/{entry_script}", path_type="File" + ): + raise ValueError( + f"Invalid 'entry_script': {entry_script}. " + + "Must be a valid file within the 'source_dir'.", + ) def model_post_init(self, __context: Any): """Post init method to perform custom validation and set default values.""" @@ -838,12 +855,17 @@ def _prepare_train_script( install_requirements = "" if source_code.requirements: - install_requirements = "echo 'Installing requirements'\n" - install_requirements = f"$SM_PIP_CMD install -r {source_code.requirements}" + install_requirements = ( + "echo 'Installing requirements'\n" + + f"$SM_PIP_CMD install -r {source_code.requirements}" + ) working_dir = "" if source_code.source_dir: - working_dir = f"cd {SM_CODE_CONTAINER_PATH}" + working_dir = f"cd {SM_CODE_CONTAINER_PATH} \n" + if source_code.source_dir.endswith(".tar.gz"): + tarfile_name = os.path.basename(source_code.source_dir) + working_dir += f"tar --strip-components=1 -xzf {tarfile_name} \n" if base_command: execute_driver = EXECUTE_BASE_COMMANDS.format(base_command=base_command) diff --git a/tests/data/modules/script_mode/code.tar.gz b/tests/data/modules/script_mode/code.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..7c43f35f576640607e79a6f70ccaf84ce897feaa GIT binary patch literal 37983 zcmV)!K#;#5iwFSYjtXc11MGbTSXEiqKizSYG_F{nNSA?oDTs=RVh18z1f?Vt?C!ws z?!v^@jg1Wo7J@Vgij<`B-{&4SI>+&y?|r|S`JVqf?&q23aL(DW_R8N{`&`GuE8Hh6 zAT+`&D8yGP_t!KlD=SBPdx`Ao;3&IV+1RmH_HSE>wVk7*y{)yqt*y1h%G%D>-ce3s z^%v3en-&=!;T=Xu2?_}ejQ0OI3rIIVzke|gyA?^p_5YWqtfwlcASc(y+egxGpk%0| zzA?|_)X9G~!o0y2yWfF7^otvhWTK4U}4hhJ{R$ z273qlNaf@e|y z{$x6SxBbKI-_}YJ6cG?4b+&f2v$M8qZ)4To!pVwA!QRf!NyFYz(z|EZE(2V8^c>vH zBFZ}=BFy6V%+`**{}1ocM2JP3+(PuOjIC_7AuJ@8xgdyWfEkdLJoHYnP9PI4=9sK9$ zXl4Bi|NSlP7ykQ4x9{!$8y5U?{lFjEKNtVmkO1KL3;+Ec?f3DYjh&s9t&ROJ{P$nq zzPJCsCi?%8{aX`rx8}xwI|r*@@&E5=%_V+;-V>xw9VEda6TLM8f+I5H?STH+lp2@a)?Lc-}^;n59$28N6q7Z5y--i{9s32x}+9~lu4Nbe#-!hHOH zb7K)4EL$L0!!Il(sQwufQ*81p1t8o>?=jg}3R z>2si$uhfr@8z*IzJWxY}AyOJ9ai-K-kaxXh&rH3%g1v*JUS4MPoh-=2y`__+fu^*t zYqze0x;MP`_Vw-I9qb!OhSClLBf_NKLG&r%jYW8bZ%AZ>nVE)9WLTIqIKs;}fLT2x z+#=LF!ry}2F^ihgd+)K~%$3mM7ZAwMVy2;?!R&wn1(z%*2``!Mn%2)_X8z-=`iXwSW@>J(p#F{hZ0<^}oww zGUTUBs$Y%eFuCC{_(IY|Aev3n|i*oCg~S! zT5p>_@RTuY8B=8)Bz_@b5<;+)n2e9~w@mbvP73gm5>Bv7vbUxtK9RoOCXxWZ`p3+z zML@Wh_ayItK<}}EQd2XDG%#E$G4TnFG+`OTF6I2qJ(zy?T*hTD;`k$^gj}BpQ+8e% z?;AEDX)7_YWV?q(_)~_n52Ta4>4f#%W1mNan6fle-UI}PMn*8a36oBYWCS@j#5dYp zLhp!DMKF#dB05ycVVbKnTpAYO9T+f0D$~EvFe&leQW+n~-wfFSA;Ihdzhxrf)9=kM zadwuNFi>ZgLgHF+^ldw$ zz`qZI=HJD$p9bFVJi7Te_xzIp@;x^hbNCHkYnPXMrIhp|bH~y(0)33TM27v&6wp_DmWY;^WUyV9mw`sdpGN$SaKa zIr7xX!up4p(V(FwznO3<2^tNvF*kHBN&Q??r<+(1KORK1_uD`^#{9QSvka==cRimN z*Zd9fQO=W*-_J&nrJrA*)Y&sEQrf^aSE*k>u=HCvA&Z5ChfDk-gIR~j$UY>LWWHpI zus;q3@JFxfkd`|jK5@Ca$> zcQ0A?w55v9Rcb#ISqFl5WY_7EcAaJGkO$1A0r(L9GluiH(^>cw`U>G?tR@;TYrknNgu(0l~y4jtrL3M)a-&afxIq z8X_8KALuvA<4{8w!v^RMZLm)2ZqedB|im0 zEWn`Pjo=GksTbp{DO(!GFmEis0g~X5hz7qdBPZPScV_vH(acsRkjZ|x+wV%<#D(N% z5yX3X6Y~fpUPa;^LHty+21oUKGu3mG&0#HkLI{UVxYZKE|DO`^n}I*%sDCi{H`Ehx zGX7OImbf#LA%-(?;5$eA6Z$m>due(r!+2g^L5x{?)nmJQg&GhUEOX$$2`A%2#!4(K zEJg-XllXIB(>G5~%;EpK5b_UgzdiqBFfxIKK?F*LTSP=f{5fmH7QzMs)ZGC|JOwSKem4dN3Q)_+5Gzc@9$~9 z|NY;;`aDlV!za)?JY3RO8X4vt*jE~1${c)#_(lfOZ&R2L6TG|vf&(JFyiCKTfqvf| z*n~%hO2bUeEE?W_JEdWITKM@`vq!1D1A?XAVWv*z5~m-!*l@cz{LsbrH(eaeCDsi` z7k1!^D`i{J)Z{MkS2m6~+l1!t%JF)!MCp=(WP)L9;?Pl{sH%bh7!Trc1 z>buX)>W`Z{X#D2D`5S|O{DkOF^OwKH|I8N)f7Z<3n$^Gk`)_+2$6xmU_q1R5{~z6c zAOHWke&7%7|A*gyJ6c&g{KEf#NBha|f1K=W?QMVI|Ns8>z5UBRoBRvb_#^wb`r-HA z_SQBIzkdJyceEemZz22G>`z_e-^YIrHg>=M{hz<5{lb6$==OvCe*=MknjiQN@E^JP zh5!DJ_7nW)XzS=;?eGi#{nxi2?4PmvKN$r6`}mLj_rHGOzrViy9{yv#$o@0e_z&=( zoz<`JfB&BL3;+G2+rPqpf0iHkxAC8im9_1!?|=W6_LK8}tM>MGcI|)RzyJF7BmQHo z{?7$~{{jB9VZQ(Wh5!Eg_7nMAczyS8wES<^u=@AE|8%go`-T7hmi7z({iEAY?Ef1I z{1g1ZAKJf_Blr7HJ8P?7`0wv%Htl~G|5-aY+1UMpfB*gMC-(m*M*lyue;ZpXyC3pD zJKJC9e}79`(|1sx{=?+uCdo~0?JFhP(7J=9btgZk*5;Ddej#B*3xd5u!bl(>&)vKO z!=>c8>>nZ__omiFQ08XllIfEFv}qK~sa@axiV%({ExobHO9x)}GTIZFEQV6Iyj5r@ z51t)d=pS)M09~WbOuV^S40`FgCRc?#c=&*6m1tp2nZmnlAq=ZcRQ{;VgI&93&RHrJ zz`_GV?%B8s;pRz;;63uH5GSs?UwnuMPwdx(oNccURjY6NHy)%4swH|o`gc-+r2D4p zM{MT7iIsgv)x1-Hoq_kn>A70qYIkw&iwk^Mc++`(=QC=sF<3A+UPBkM4ecuWg$h70 zq0~%nzaD7%Xm-)L_XT~N*Rn}}2TeE+bF%KdkO#eMUk9I3&c!&yw(E%?BZ8ML51&(cCV*k_O2KJ;M9|iL z>Q399F5SZ=u>uvyd6Tr1T&I;7=dcd`%>14cgU~Gwn7~a`E84x{{2dlirA-46xiVq%(X1N?(tpi`qt!`{Q+laN_Wg^h4 zJafZqjSxiW_UpL4dJviLFjTSgSCkaJeAMoXVo-OQ*T%k130A=6Sg#Z6z);sbiw6&i z@80Oz&H%RB?mpufRZr(j1Mr*M+a}CG2qPz#doG-&2di8y_Y4hIge2vU?ZRt~!F=7m0qP84Bh;XHvZ+SJVr}T6LnLuY86w=)R;qYufE!~7 z)jD9pFnFr~Eb<489JHR;V@A7}olZ*7ZFc8Xt=|e@dbE6HlDY`^@(cU#Q_+K4PBVoX z9=Z_SuO0>ie3oc(mKe z*8_A|KXF$b=Wq}B}2_X-W86PP_pLyE-j(hT9ZMx&t%HHxY_}rAfQ@m8* zA7x!I_FcW|^a*XK{$$lPszL~EMF+>vDNuqN+RPI%+}p5CE}ZKx5%EnZXCn2hT#8U5VSzyM4<54}`eE`nFa)4XlgX~D}) zUGwcLwSfq?Q%@2{r2BfB6%hY-UVcYYw*moJk|=Rm*#PvD&pmh>rUlMrs)~=(j9~J- zr*rf_ljoNU+V(ij2VzZ1c1hZB=15H0nnF34wPRu?`18U1+!-T*zCJj55=+h0hKa*V zb|07Up!qoOejP6hApY_BP)Uv!Yga+~pvNe3wixVsDI_PC31GYx@$5=`Al9>DHL;gn z?TCVj<>2IQm8Vvn)ZyXrJh^M1gkX4Y@g%VgA8yZAY&J|z1tv(ZTYe1JhHEh?$F`S? 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"763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:2.0.0-cpu-py310" +TAR_FILE_SOURCE_DIR = f"{DATA_DIR}/modules/script_mode/code.tar.gz" +TAR_FILE_SOURCE_CODE = SourceCode( + source_dir=TAR_FILE_SOURCE_DIR, + requirements="requirements.txt", + entry_script="custom_script.py", +) + + +def test_source_dir_local_tar_file(modules_sagemaker_session): + model_trainer = ModelTrainer( + sagemaker_session=modules_sagemaker_session, + training_image=DEFAULT_CPU_IMAGE, + source_code=TAR_FILE_SOURCE_CODE, + base_job_name="source_dir_local_tar_file", + ) + + model_trainer.train() + def test_hp_contract_basic_py_script(modules_sagemaker_session): model_trainer = ModelTrainer( diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 13530a3983..6001c5db36 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -92,9 +92,6 @@ source_dir=DEFAULT_SOURCE_DIR, entry_script="custom_script.py", ) -UNSUPPORTED_SOURCE_CODE = SourceCode( - entry_script="train.py", -) DEFAULT_ENTRYPOINT = ["/bin/bash"] DEFAULT_ARGUMENTS = [ "-c", @@ -152,7 +149,19 @@ def model_trainer(): { "init_params": { "training_image": DEFAULT_IMAGE, - "source_code": UNSUPPORTED_SOURCE_CODE, + "source_code": SourceCode( + entry_script="train.py", + ), + }, + "should_throw": True, + }, + { + "init_params": { + "training_image": DEFAULT_IMAGE, + "source_code": SourceCode( + source_dir="s3://bucket/requirements.txt", + entry_script="custom_script.py", + ), }, "should_throw": True, }, @@ -163,13 +172,47 @@ def model_trainer(): }, "should_throw": False, }, + { + "init_params": { + "training_image": DEFAULT_IMAGE, + "source_code": SourceCode( + source_dir=f"{DEFAULT_SOURCE_DIR}/code.tar.gz", + entry_script="custom_script.py", + ), + }, + "should_throw": False, + }, + { + "init_params": { + "training_image": DEFAULT_IMAGE, + "source_code": SourceCode( + source_dir="s3://bucket/code/", + entry_script="custom_script.py", + ), + }, + "should_throw": False, + }, + { + "init_params": { + "training_image": DEFAULT_IMAGE, + "source_code": SourceCode( + source_dir="s3://bucket/code/code.tar.gz", + entry_script="custom_script.py", + ), + }, + "should_throw": False, + }, ], ids=[ "no_params", "training_image_and_algorithm_name", "only_training_image", - "unsupported_source_code", - "supported_source_code", + "unsupported_source_code_missing_source_dir", + "unsupported_source_code_s3_other_file", + "supported_source_code_local_dir", + "supported_source_code_local_tar_file", + "supported_source_code_s3_dir", + "supported_source_code_s3_tar_file", ], ) def test_model_trainer_param_validation(test_case, modules_session): From 9ba3997aa10ffc08d402e44cec6b00ceeb8143ea Mon Sep 17 00:00:00 2001 From: Pravali Uppugunduri <46845440+pravali96@users.noreply.github.com> Date: Mon, 28 Apr 2025 09:18:07 -0700 Subject: [PATCH 067/164] feature:support custom workflow deployment in ModelBuilder using SMD image. (#5143) * feature:support custom workflow deployment in ModelBuilder using SMD image. (#1661) * feature:support custom workflow deployment in ModelBuilder using SMD inference image. * Rename test case and pass session. * Address PR comments. * Tweak resource cleanup logic in integ test. * Fixing CodeBuild integ test failures. * Renamed integ test. * Remove unused integ test, restore once GA. --------- Co-authored-by: Joseph Zhang * Cache client as instance attribute in property@ decorator. (#1668) * Remove property@ decorator from ABC definition. * Cache client as instance attribute in @property. * Fix flake8 issue. --------- Co-authored-by: Joseph Zhang * Bugfixes from e2e testing. (#1670) * Fix Alabtross Inference component tests * trigger integ tests --------- Co-authored-by: cj-zhang <32367995+cj-zhang@users.noreply.github.com> Co-authored-by: Joseph Zhang Co-authored-by: Pravali Uppugunduri --- .../sagemaker-distribution.json | 37 ++ src/sagemaker/serve/builder/model_builder.py | 485 ++++++++++++++++-- .../serve/mode/sagemaker_endpoint_mode.py | 14 + .../smd/custom_execution_inference.py | 72 +++ .../serve/model_server/smd/prepare.py | 74 +++ .../serve/model_server/smd/server.py | 59 +++ src/sagemaker/serve/spec/inference_base.py | 45 ++ src/sagemaker/serve/utils/telemetry_logger.py | 1 + src/sagemaker/serve/utils/types.py | 1 + tests/integ/sagemaker/serve/constants.py | 1 + ...model_builder_inference_component_happy.py | 149 ++++++ .../sagemaker/image_uris/expected_uris.py | 9 + .../image_uris/test_sagemaker_distribution.py | 47 ++ .../serve/builder/test_model_builder.py | 83 ++- 14 files changed, 1039 insertions(+), 38 deletions(-) create mode 100644 src/sagemaker/image_uri_config/sagemaker-distribution.json create mode 100644 src/sagemaker/serve/model_server/smd/custom_execution_inference.py create mode 100644 src/sagemaker/serve/model_server/smd/prepare.py create mode 100644 src/sagemaker/serve/model_server/smd/server.py create mode 100644 src/sagemaker/serve/spec/inference_base.py create mode 100644 tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py create mode 100644 tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py diff --git a/src/sagemaker/image_uri_config/sagemaker-distribution.json b/src/sagemaker/image_uri_config/sagemaker-distribution.json new file mode 100644 index 0000000000..d9ffca5d7b --- /dev/null +++ b/src/sagemaker/image_uri_config/sagemaker-distribution.json @@ -0,0 +1,37 @@ +{ + "processors": ["cpu", "gpu"], + "scope": ["inference"], + "version_aliases": { + "3.0": "3.0.0" + }, + "versions": { + "3.0.0": { + "registries": { + "us-east-1": "885854791233", + "us-east-2": "137914896644", + "us-west-1": "053634841547", + "us-west-2": "542918446943", + "af-south-1": "238384257742", + "ap-east-1": "523751269255", + "ap-south-1": "245090515133", + "ap-northeast-2": "064688005998", + "ap-southeast-1": "022667117163", + "ap-southeast-2": "648430277019", + "ap-northeast-1": "010972774902", + "ca-central-1": "481561238223", + "eu-central-1": "545423591354", + "eu-west-1": "819792524951", + "eu-west-2": "021081402939", + "eu-west-3": "856416204555", + "eu-north-1": "175620155138", + "eu-south-1": "810671768855", + "sa-east-1": "567556641782", + "ap-northeast-3": "564864627153", + "ap-southeast-3": "370607712162", + "me-south-1": "523774347010", + "me-central-1": "358593528301" + }, + "repository": "sagemaker-distribution-prod" + } + } +} diff --git a/src/sagemaker/serve/builder/model_builder.py b/src/sagemaker/serve/builder/model_builder.py index 9122f22e44..ed5455daec 100644 --- a/src/sagemaker/serve/builder/model_builder.py +++ b/src/sagemaker/serve/builder/model_builder.py @@ -11,7 +11,7 @@ # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. """Holds the ModelBuilder class and the ModelServer enum.""" -from __future__ import absolute_import +from __future__ import absolute_import, annotations import importlib.util import json @@ -24,6 +24,7 @@ from pathlib import Path +from botocore.exceptions import ClientError from sagemaker_core.main.resources import TrainingJob from sagemaker.transformer import Transformer @@ -37,6 +38,7 @@ from sagemaker.s3 import S3Downloader from sagemaker import Session from sagemaker.model import Model +from sagemaker.jumpstart.model import JumpStartModel from sagemaker.base_predictor import PredictorBase from sagemaker.serializers import NumpySerializer, TorchTensorSerializer from sagemaker.deserializers import JSONDeserializer, TorchTensorDeserializer @@ -75,6 +77,7 @@ ) from sagemaker.serve.save_retrive.version_1_0_0.metadata.metadata import Metadata from sagemaker.serve.spec.inference_spec import InferenceSpec +from sagemaker.serve.spec.inference_base import CustomOrchestrator, AsyncCustomOrchestrator from sagemaker.serve.utils import task from sagemaker.serve.utils.exceptions import TaskNotFoundException from sagemaker.serve.utils.lineage_utils import _maintain_lineage_tracking_for_mlflow_model @@ -102,6 +105,7 @@ _get_model_base, ) from sagemaker.serve.model_server.torchserve.prepare import prepare_for_torchserve +from sagemaker.serve.model_server.smd.prepare import prepare_for_smd from sagemaker.serve.model_server.triton.triton_builder import Triton from sagemaker.serve.utils.telemetry_logger import _capture_telemetry from sagemaker.serve.utils.types import ModelServer, ModelHub @@ -131,6 +135,7 @@ ModelServer.MMS, ModelServer.TGI, ModelServer.TEI, + ModelServer.SMD, } @@ -220,6 +225,18 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing, available for providing s3 path to fine-tuned model artifacts. ``FINE_TUNING_JOB_NAME`` is available for providing fine-tuned job name. Both ``FINE_TUNING_MODEL_PATH`` and ``FINE_TUNING_JOB_NAME`` are mutually exclusive. + inference_component_name (Optional[str]): The name for an inference component + created from this ModelBuilder instance. This or ``resource_requirements`` must be set + to denote that this instance refers to an inference component. + modelbuilder_list: Optional[List[ModelBuilder]] = List of ModelBuilder objects which + can be built in bulk and subsequently deployed in bulk. Currently only supports + deployments for inference components. + resource_requirements: Optional[ResourceRequirements] = Defines the compute resources + allocated to run the model assigned to the inference component. This or + ``inference_component_name`` must be set to denote that this instance refers + to an inference component. If ``inference_component_name`` is set but this is not and a + JumpStart model ID is specified, pre-benchmarked deployment configs will attempt to be + retrieved for the model. """ model_path: Optional[str] = field( @@ -233,7 +250,7 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing, default=None, metadata={"help": "Define sagemaker session for execution"} ) name: Optional[str] = field( - default="model-name-" + uuid.uuid1().hex, + default_factory=lambda: "model-name-" + uuid.uuid1().hex, metadata={"help": "Define the model name"}, ) mode: Optional[Mode] = field( @@ -320,6 +337,23 @@ class ModelBuilder(Triton, DJL, JumpStart, TGI, Transformers, TensorflowServing, "in the Hub, Adding unsupported task types will throw an exception." }, ) + inference_component_name: Optional[str] = field( + default=None, + metadata={ + "help": "Defines the name for an Inference Component created from this ModelBuilder." + }, + ) + modelbuilder_list: Optional[List[ModelBuilder]] = field( + default=None, + metadata={"help": "Defines a list of ModelBuilder objects."}, + ) + resource_requirements: Optional[ResourceRequirements] = field( + default=None, + metadata={ + "help": "Defines the compute resources allocated to run the model assigned" + " to the inference component." + }, + ) def _save_model_inference_spec(self): """Placeholder docstring""" @@ -465,7 +499,7 @@ def _get_client_translators(self): elif self.schema_builder: serializer = self.schema_builder.input_serializer else: - raise Exception("Cannot serialize") + raise Exception("Cannot serialize. Try providing a SchemaBuilder if not present.") deserializer = None if self.accept_type == "application/json": @@ -477,7 +511,7 @@ def _get_client_translators(self): elif self.schema_builder: deserializer = self.schema_builder.output_deserializer else: - raise Exception("Cannot deserialize") + raise Exception("Cannot deserialize. Try providing a SchemaBuilder if not present.") return serializer, deserializer @@ -562,6 +596,83 @@ def _model_builder_deploy_model_package_wrapper(self, *args, **kwargs): self.pysdk_model.model_package_arn = None return predictor + def _deploy_for_ic( + self, + *args, + ic_data: Dict[str, Any], + container_timeout_in_seconds: int = 300, + model_data_download_timeout: int = 3600, + instance_type: Optional[str] = None, + initial_instance_count: Optional[int] = None, + endpoint_name: Optional[str] = None, + **kwargs, + ) -> Predictor: + """Creates an Inference Component from a ModelBuilder.""" + ic_name = ic_data.get("Name", None) + model = ic_data.get("Model", None) + resource_requirements = ic_data.get("ResourceRequirements", {}) + + # Ensure resource requirements are set for non-JumpStart models + if not resource_requirements: + raise ValueError( + f"Cannot create/update inference component {ic_name} without resource requirements." + ) + + # Check if the Inference Component exists + if ic_name and self._does_ic_exist(ic_name=ic_name): + logger.info("Updating Inference Component %s as it already exists.", ic_name) + + # Create spec for updating the IC + startup_parameters = {} + if model_data_download_timeout is not None: + startup_parameters["ModelDataDownloadTimeoutInSeconds"] = ( + model_data_download_timeout + ) + if container_timeout_in_seconds is not None: + startup_parameters["ContainerStartupHealthCheckTimeoutInSeconds"] = ( + container_timeout_in_seconds + ) + compute_rr = resource_requirements.get_compute_resource_requirements() + inference_component_spec = { + "ModelName": self.name, + "StartupParameters": startup_parameters, + "ComputeResourceRequirements": compute_rr, + } + runtime_config = {"CopyCount": resource_requirements.copy_count} + response = self.sagemaker_session.update_inference_component( + inference_component_name=ic_name, + specification=inference_component_spec, + runtime_config=runtime_config, + ) + return Predictor(endpoint_name=response.get("EndpointName"), component_name=ic_name) + else: + kwargs.update( + { + "resources": resource_requirements, + "endpoint_type": EndpointType.INFERENCE_COMPONENT_BASED, + "inference_component_name": ic_name, + "endpoint_logging": False, + } + ) + return model.deploy( + *args, + container_startup_health_check_timeout=container_timeout_in_seconds, + initial_instance_count=initial_instance_count, + instance_type=instance_type, + mode=Mode.SAGEMAKER_ENDPOINT, + endpoint_name=endpoint_name, + **kwargs, + ) + + def _does_ic_exist(self, ic_name: str) -> bool: + """Returns true if an Inference Component exists with the given name.""" + try: + self.sagemaker_session.describe_inference_component(inference_component_name=ic_name) + return True + except ClientError as e: + msg = e.response["Error"]["Message"] + return "Could not find inference component" not in msg + @_capture_telemetry("torchserve.deploy") def _model_builder_deploy_wrapper( self, @@ -615,6 +726,13 @@ def _model_builder_deploy_wrapper( if "endpoint_logging" not in kwargs: kwargs["endpoint_logging"] = True + + if "inference_component_name" not in kwargs and self.inference_component_name: + kwargs["inference_component_name"] = self.inference_component_name + + if "resources" not in kwargs and self.resource_requirements: + kwargs["resources"] = self.resource_requirements + kwargs.pop("mode", None) self.pysdk_model.role = kwargs.pop("role", self.pysdk_model.role) predictor = self._original_deploy( @@ -673,6 +791,24 @@ def _build_for_torchserve(self) -> Type[Model]: self.model = self._create_model() return self.model + def _build_for_smd(self) -> Type[Model]: + """Build the model for SageMaker Distribution""" + self._save_model_inference_spec() + + if self.mode != Mode.IN_PROCESS: + self._auto_detect_container() + + self.secret_key = prepare_for_smd( + model_path=self.model_path, + shared_libs=self.shared_libs, + dependencies=self.dependencies, + inference_spec=self.inference_spec, + ) + + self._prepare_for_mode() + self.model = self._create_model() + return self.model + def _user_agent_decorator(self, func): """Placeholder docstring""" @@ -854,13 +990,225 @@ def _collect_estimator_model_telemetry(self): """Dummy method to collect telemetry for estimator handshake""" return + def build( + self, + mode: Type[Mode] = None, + role_arn: str = None, + sagemaker_session: Optional[Session] = None, + ) -> Union[ModelBuilder, Type[Model]]: + """Creates deployable ``Model`` instances with all provided ``ModelBuilder`` objects. + + Args: + mode (Type[Mode], optional): The mode. Defaults to ``None``. + role_arn (str, optional): The IAM role arn. Defaults to ``None``. + sagemaker_session (Optional[Session]): Session object which manages interactions + with Amazon SageMaker APIs and any other AWS services needed. If not specified, the + function creates one using the default AWS configuration chain. + + Returns: + Union[ModelBuilder, Type[Model]]: A deployable ``ModelBuilder`` object if multiple + ``ModelBuilders`` were built, or a deployable ``Model`` object. + """ + if role_arn: + self.role_arn = role_arn + self.sagemaker_session = sagemaker_session or self.sagemaker_session or Session() + + deployables = {} + + if not self.modelbuilder_list and not isinstance( + self.inference_spec, (CustomOrchestrator, AsyncCustomOrchestrator) + ): + self.serve_settings = self._get_serve_setting() + return self._build_single_modelbuilder( + mode=mode, + role_arn=self.role_arn, + sagemaker_session=sagemaker_session, + ) + + # Multi-ModelBuilder case: deploy + built_ic_models = [] + if self.modelbuilder_list: + logger.info("Detected ModelBuilders in modelbuilder_list.") + for mb in self.modelbuilder_list: + if mb.mode == Mode.IN_PROCESS or mb.mode == Mode.LOCAL_CONTAINER: + raise ValueError( + "Bulk ModelBuilder building is only supported for SageMaker Endpoint Mode." + ) + + if (not mb.resource_requirements and not mb.inference_component_name) and ( + not mb.inference_spec + or not isinstance( + mb.inference_spec, (CustomOrchestrator, AsyncCustomOrchestrator) + ) + ): + raise ValueError( + "Bulk ModelBuilder building is only supported for Inference Components " + + "and custom orchestrators." + ) + + for mb in self.modelbuilder_list: + # Custom orchestrator definition found in inference_spec + mb.serve_settings = mb._get_serve_setting() + # Build for Inference Component + logger.info("Building ModelBuilder %s.", mb.name) + # Get JS deployment configs if ResourceRequirements not set + + mb = mb._get_ic_resource_requirements(mb=mb) + + built_model = mb._build_single_modelbuilder( + role_arn=self.role_arn, sagemaker_session=self.sagemaker_session + ) + built_ic_models.append( + { + "Name": mb.inference_component_name, + "ResourceRequirements": mb.resource_requirements, + "Model": built_model, + } + ) + logger.info( + "=====================Build for %s complete.===================", + mb.model, + ) + deployables["InferenceComponents"] = built_ic_models + + if isinstance(self.inference_spec, (CustomOrchestrator, AsyncCustomOrchestrator)): + logger.info("Building custom orchestrator.") + if self.mode == Mode.IN_PROCESS or self.mode == Mode.LOCAL_CONTAINER: + raise ValueError( + "Custom orchestrator deployment is only supported for" + "SageMaker Endpoint Mode." + ) + self.serve_settings = self._get_serve_setting() + cpu_or_gpu_instance = self._get_processing_unit() + self.image_uri = self._get_smd_image_uri(processing_unit=cpu_or_gpu_instance) + self.model_server = ModelServer.SMD + built_orchestrator = self._build_single_modelbuilder( + mode=Mode.SAGEMAKER_ENDPOINT, + role_arn=role_arn, + sagemaker_session=sagemaker_session, + ) + if not self.resource_requirements: + logger.info( + "Custom orchestrator resource_requirements not found. " + "Building as a SageMaker Endpoint instead of Inference Component." + ) + deployables["CustomOrchestrator"] = { + "Mode": "Endpoint", + "Model": built_orchestrator, + } + else: + # Network isolation of ICs on an endpoint must be consistent + if built_ic_models: + if ( + self.dependencies["auto"] + or "requirements" in self.dependencies + or "custom" in self.dependencies + ): + logger.warning( + "Custom orchestrator network isolation must be False when dependencies " + "are specified or using autocapture. To enable network isolation, " + "package all dependencies in the container or model artifacts " + "ahead of time." + ) + built_orchestrator._enable_network_isolation = False + for model in built_ic_models: + model["Model"]._enable_network_isolation = False + deployables["CustomOrchestrator"] = { + "Name": self.inference_component_name, + "Mode": "InferenceComponent", + "ResourceRequirements": self.resource_requirements, + "Model": built_orchestrator, + } + + logger.info( + "=====================Custom orchestrator build complete.===================", + ) + + self._deployables = deployables + return self + + def _get_processing_unit(self): + """Detects if the resource requirements are intended for a CPU or GPU instance.""" + # Assume custom orchestrator will be deployed as an endpoint to a CPU instance + if not self.resource_requirements or not self.resource_requirements.num_accelerators: + return "cpu" + for ic in self.modelbuilder_list or []: + if ic.resource_requirements.num_accelerators > 0: + return "gpu" + if self.resource_requirements.num_accelerators > 0: + return "gpu" + + return "cpu" + + def _get_ic_resource_requirements(self, mb: ModelBuilder = None) -> ModelBuilder: + """Attempts fetching pre-benchmarked resource requirements for the MB from JumpStart.""" + if mb._is_jumpstart_model_id() and not mb.resource_requirements: + js_model = JumpStartModel(model_id=mb.model) + deployment_configs = js_model.list_deployment_configs() + if not deployment_configs: + raise ValueError( + "No resource requirements were provided for Inference Component " + f"{mb.inference_component_name} and no default deployment" + " configs were found in JumpStart." + ) + compute_requirements = ( + deployment_configs[0].get("DeploymentArgs").get("ComputeResourceRequirements") + ) + logger.info("Retrieved pre-benchmarked deployment configurations from JumpStart.") + mb.resource_requirements = ResourceRequirements( + requests={ + "memory": compute_requirements["MinMemoryRequiredInMb"], + "num_accelerators": compute_requirements.get( + "NumberOfAcceleratorDevicesRequired", None + ), + "copies": 1, + "num_cpus": compute_requirements.get("NumberOfCpuCoresRequired", None), + }, + limits={"memory": compute_requirements.get("MaxMemoryRequiredInMb", None)}, + ) + + return mb + + @_capture_telemetry("build_custom_orchestrator") + def _get_smd_image_uri(self, processing_unit: str = None) -> str: + """Gets the SMD Inference Image URI. + + Returns: + str: SMD Inference Image URI. + """ + from sagemaker import image_uris + import sys + + self.sagemaker_session = self.sagemaker_session or Session() + from packaging.version import Version + + formatted_py_version = f"py{sys.version_info.major}{sys.version_info.minor}" + if Version(f"{sys.version_info.major}{sys.version_info.minor}") < Version("3.12"): + raise ValueError( + f"Found Python version {formatted_py_version} but" + f"Custom orchestrator deployment requires Python version >= 3.12." + ) + + INSTANCE_TYPES = {"cpu": "ml.c5.xlarge", "gpu": "ml.g5.4xlarge"} + + logger.info("Finding SMD inference image URI for a %s instance.", processing_unit) + + smd_uri = image_uris.retrieve( + framework="sagemaker-distribution", + image_scope="inference", + instance_type=INSTANCE_TYPES[processing_unit], + region=self.sagemaker_session.boto_region_name, + ) + logger.info("Found compatible image %s", smd_uri) + return smd_uri + # Model Builder is a class to build the model for deployment. # It supports three modes of deployment # 1/ SageMaker Endpoint # 2/ Local launch with container # 3/ In process mode with Transformers server in beta release @_capture_telemetry("ModelBuilder.build") - def build( # pylint: disable=R0911 + def _build_single_modelbuilder( # pylint: disable=R0911 self, mode: Type[Mode] = None, role_arn: str = None, @@ -1039,6 +1387,9 @@ def _build_for_model_server(self): # pylint: disable=R0911, R1710 if self.model_server == ModelServer.MMS: return self._build_for_transformers() + if self.model_server == ModelServer.SMD: + return self._build_for_smd() + @_capture_telemetry("ModelBuilder.save") def save( self, @@ -1593,6 +1944,8 @@ def _optimize_prepare_for_hf(self): def deploy( self, endpoint_name: str = None, + container_timeout_in_second: int = 300, + instance_type: str = None, initial_instance_count: Optional[int] = 1, inference_config: Optional[ Union[ @@ -1603,7 +1956,10 @@ def deploy( ] ] = None, update_endpoint: Optional[bool] = False, - ) -> Union[Predictor, Transformer]: + custom_orchestrator_instance_type: str = None, + custom_orchestrator_initial_instance_count: int = None, + **kwargs, + ) -> Union[Predictor, Transformer, List[Predictor]]: """Deploys the built Model. Depending on the type of config provided, this function will call deployment accordingly. @@ -1625,42 +1981,43 @@ def deploy( Transformer for Batch Deployments Predictors for all others """ - if not hasattr(self, "built_model"): - raise ValueError("Model Needs to be built before deploying") + if not hasattr(self, "built_model") and not hasattr(self, "_deployables"): + raise ValueError("Model needs to be built before deploying") if not update_endpoint: endpoint_name = unique_name_from_base(endpoint_name) - if not inference_config: # Real-time Deployment - return self.built_model.deploy( - instance_type=self.instance_type, - initial_instance_count=initial_instance_count, - endpoint_name=endpoint_name, - update_endpoint=update_endpoint, - ) + if not hasattr(self, "_deployables"): + if not inference_config: # Real-time Deployment + return self.built_model.deploy( + instance_type=self.instance_type, + initial_instance_count=initial_instance_count, + endpoint_name=endpoint_name, + update_endpoint=update_endpoint, + ) - if isinstance(inference_config, ServerlessInferenceConfig): - return self.built_model.deploy( - serverless_inference_config=inference_config, - endpoint_name=endpoint_name, - update_endpoint=update_endpoint, - ) + if isinstance(inference_config, ServerlessInferenceConfig): + return self.built_model.deploy( + serverless_inference_config=inference_config, + endpoint_name=endpoint_name, + update_endpoint=update_endpoint, + ) - if isinstance(inference_config, AsyncInferenceConfig): - return self.built_model.deploy( - instance_type=self.instance_type, - initial_instance_count=initial_instance_count, - async_inference_config=inference_config, - endpoint_name=endpoint_name, - update_endpoint=update_endpoint, - ) + if isinstance(inference_config, AsyncInferenceConfig): + return self.built_model.deploy( + instance_type=self.instance_type, + initial_instance_count=initial_instance_count, + async_inference_config=inference_config, + endpoint_name=endpoint_name, + update_endpoint=update_endpoint, + ) - if isinstance(inference_config, BatchTransformInferenceConfig): - transformer = self.built_model.transformer( - instance_type=inference_config.instance_type, - output_path=inference_config.output_path, - instance_count=inference_config.instance_count, - ) - return transformer + if isinstance(inference_config, BatchTransformInferenceConfig): + transformer = self.built_model.transformer( + instance_type=inference_config.instance_type, + output_path=inference_config.output_path, + instance_count=inference_config.instance_count, + ) + return transformer if isinstance(inference_config, ResourceRequirements): if update_endpoint: @@ -1678,7 +2035,61 @@ def deploy( update_endpoint=update_endpoint, ) - raise ValueError("Deployment Options not supported") + raise ValueError("Deployment Options not supported") + + # Iterate through deployables for a custom orchestrator deployment. + # Create all Inference Components first before deploying custom orchestrator if present. + predictors = [] + for inference_component in self._deployables.get("InferenceComponents", []): + predictors.append( + self._deploy_for_ic( + ic_data=inference_component, + container_timeout_in_seconds=container_timeout_in_second, + instance_type=instance_type, + initial_instance_count=initial_instance_count, + endpoint_name=endpoint_name, + **kwargs, + ) + ) + if self._deployables.get("CustomOrchestrator", None): + custom_orchestrator = self._deployables.get("CustomOrchestrator") + if not custom_orchestrator_instance_type and not instance_type: + logger.warning( + "Deploying custom orchestrator as an endpoint but no instance type was " + "set. Defaulting to `ml.c5.xlarge`." + ) + custom_orchestrator_instance_type = "ml.c5.xlarge" + custom_orchestrator_initial_instance_count = 1 + if custom_orchestrator["Mode"] == "Endpoint": + logger.info( + "Deploying custom orchestrator on instance type %s.", + custom_orchestrator_instance_type, + ) + predictors.append( + custom_orchestrator["Model"].deploy( + instance_type=custom_orchestrator_instance_type, + initial_instance_count=custom_orchestrator_initial_instance_count, + **kwargs, + ) + ) + elif custom_orchestrator["Mode"] == "InferenceComponent": + logger.info( + "Deploying custom orchestrator as an inference component " + f"to endpoint {endpoint_name}" + ) + predictors.append( + self._deploy_for_ic( + ic_data=custom_orchestrator, + container_timeout_in_seconds=container_timeout_in_second, + instance_type=custom_orchestrator_instance_type or instance_type, + initial_instance_count=custom_orchestrator_initial_instance_count + or initial_instance_count, + endpoint_name=endpoint_name, + **kwargs, + ) + ) + + return predictors def display_benchmark_metrics(self, **kwargs): """Display Markdown Benchmark Metrics for deployment configs.""" diff --git a/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py b/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py index 2f09d3d572..2b4473a706 100644 --- a/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py +++ b/src/sagemaker/serve/mode/sagemaker_endpoint_mode.py @@ -16,10 +16,13 @@ from sagemaker.serve.model_server.djl_serving.server import SageMakerDjlServing from sagemaker.serve.model_server.tgi.server import SageMakerTgiServing from sagemaker.serve.model_server.multi_model_server.server import SageMakerMultiModelServer +from sagemaker.serve.model_server.smd.server import SageMakerSmdServer + logger = logging.getLogger(__name__) +# pylint: disable=R0901 class SageMakerEndpointMode( SageMakerTorchServe, SageMakerTritonServer, @@ -27,6 +30,7 @@ class SageMakerEndpointMode( SageMakerTgiServing, SageMakerMultiModelServer, SageMakerTensorflowServing, + SageMakerSmdServer, ): """Holds the required method to deploy a model to a SageMaker Endpoint""" @@ -144,6 +148,16 @@ def prepare( should_upload_artifacts=should_upload_artifacts, ) + if self.model_server == ModelServer.SMD: + upload_artifacts = self._upload_smd_artifacts( + model_path=model_path, + sagemaker_session=sagemaker_session, + secret_key=secret_key, + s3_model_data_url=s3_model_data_url, + image=image, + should_upload_artifacts=True, + ) + if upload_artifacts or isinstance(self.model_server, ModelServer): return upload_artifacts diff --git a/src/sagemaker/serve/model_server/smd/custom_execution_inference.py b/src/sagemaker/serve/model_server/smd/custom_execution_inference.py new file mode 100644 index 0000000000..f53677fc69 --- /dev/null +++ b/src/sagemaker/serve/model_server/smd/custom_execution_inference.py @@ -0,0 +1,72 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""This module is for SageMaker inference.py.""" + +from __future__ import absolute_import +import asyncio +import os +import platform +import cloudpickle +import logging +from pathlib import Path +from sagemaker.serve.validations.check_integrity import perform_integrity_check + +logger = LOGGER = logging.getLogger("sagemaker") + + +def initialize_custom_orchestrator(): + """Initializes the custom orchestrator.""" + code_dir = os.getenv("SAGEMAKER_INFERENCE_CODE_DIRECTORY", None) + serve_path = Path(code_dir).joinpath("serve.pkl") + with open(str(serve_path), mode="rb") as pkl_file: + return cloudpickle.load(pkl_file) + + +def _run_preflight_diagnostics(): + _py_vs_parity_check() + _pickle_file_integrity_check() + + +def _py_vs_parity_check(): + container_py_vs = platform.python_version() + local_py_vs = os.getenv("LOCAL_PYTHON") + + if not local_py_vs or container_py_vs.split(".")[1] != local_py_vs.split(".")[1]: + logger.warning( + f"The local python version {local_py_vs} differs from the python version " + f"{container_py_vs} on the container. Please align the two to avoid unexpected behavior" + ) + + +def _pickle_file_integrity_check(): + with open("/opt/ml/model/code/serve.pkl", "rb") as f: + buffer = f.read() + + metadata_path = Path("/opt/ml/model/code/metadata.json") + perform_integrity_check(buffer=buffer, metadata_path=metadata_path) + + +_run_preflight_diagnostics() +custom_orchestrator, _ = initialize_custom_orchestrator() + + +async def handler(request): + """Custom service entry point function. + + :param request: raw input from request + :return: outputs to be send back to client + """ + if asyncio.iscoroutinefunction(custom_orchestrator.handle): + return await custom_orchestrator.handle(request.body) + else: + return custom_orchestrator.handle(request.body) diff --git a/src/sagemaker/serve/model_server/smd/prepare.py b/src/sagemaker/serve/model_server/smd/prepare.py new file mode 100644 index 0000000000..6461e4023f --- /dev/null +++ b/src/sagemaker/serve/model_server/smd/prepare.py @@ -0,0 +1,74 @@ +"""Summary of MyModule. + +Extended discussion of my module. +""" + +from __future__ import absolute_import +import os +from pathlib import Path +import shutil +from typing import List + +from sagemaker.serve.spec.inference_spec import InferenceSpec +from sagemaker.serve.detector.dependency_manager import capture_dependencies +from sagemaker.serve.validations.check_integrity import ( + generate_secret_key, + compute_hash, +) +from sagemaker.remote_function.core.serialization import _MetaData +from sagemaker.serve.spec.inference_base import CustomOrchestrator, AsyncCustomOrchestrator + + +def prepare_for_smd( + model_path: str, + shared_libs: List[str], + dependencies: dict, + inference_spec: InferenceSpec = None, +) -> str: + """Prepares artifacts for SageMaker model deployment. + + Args:to + model_path (str) : Argument + shared_libs (List[]) : Argument + dependencies (dict) : Argument + inference_spec (InferenceSpec, optional) : Argument + (default is None) + + Returns: + ( str ) : + + """ + model_path = Path(model_path) + if not model_path.exists(): + model_path.mkdir() + elif not model_path.is_dir(): + raise Exception("model_dir is not a valid directory") + + if inference_spec and isinstance(inference_spec, InferenceSpec): + inference_spec.prepare(str(model_path)) + + code_dir = model_path.joinpath("code") + code_dir.mkdir(exist_ok=True) + + if inference_spec and isinstance(inference_spec, (CustomOrchestrator, AsyncCustomOrchestrator)): + shutil.copy2(Path(__file__).parent.joinpath("custom_execution_inference.py"), code_dir) + os.rename( + str(code_dir.joinpath("custom_execution_inference.py")), + str(code_dir.joinpath("inference.py")), + ) + + shared_libs_dir = model_path.joinpath("shared_libs") + shared_libs_dir.mkdir(exist_ok=True) + for shared_lib in shared_libs: + shutil.copy2(Path(shared_lib), shared_libs_dir) + + capture_dependencies(dependencies=dependencies, work_dir=code_dir) + + secret_key = generate_secret_key() + with open(str(code_dir.joinpath("serve.pkl")), "rb") as f: + buffer = f.read() + hash_value = compute_hash(buffer=buffer, secret_key=secret_key) + with open(str(code_dir.joinpath("metadata.json")), "wb") as metadata: + metadata.write(_MetaData(hash_value).to_json()) + + return secret_key diff --git a/src/sagemaker/serve/model_server/smd/server.py b/src/sagemaker/serve/model_server/smd/server.py new file mode 100644 index 0000000000..c700c39727 --- /dev/null +++ b/src/sagemaker/serve/model_server/smd/server.py @@ -0,0 +1,59 @@ +"""Module for SMD Server""" + +from __future__ import absolute_import + +import logging +import platform +from sagemaker.serve.utils.optimize_utils import _is_s3_uri +from sagemaker.session import Session +from sagemaker.s3_utils import determine_bucket_and_prefix, parse_s3_url +from sagemaker import fw_utils +from sagemaker.serve.utils.uploader import upload + +logger = logging.getLogger(__name__) + + +class SageMakerSmdServer: + """Placeholder docstring""" + + def _upload_smd_artifacts( + self, + model_path: str, + sagemaker_session: Session, + secret_key: str, + s3_model_data_url: str = None, + image: str = None, + should_upload_artifacts: bool = False, + ): + """Tar the model artifact and upload to S3 bucket, then prepare for the environment variables""" + s3_upload_path = None + if _is_s3_uri(model_path): + s3_upload_path = model_path + elif should_upload_artifacts: + if s3_model_data_url: + bucket, key_prefix = parse_s3_url(url=s3_model_data_url) + else: + bucket, key_prefix = None, None + + code_key_prefix = fw_utils.model_code_key_prefix(key_prefix, None, image) + + bucket, code_key_prefix = determine_bucket_and_prefix( + bucket=bucket, key_prefix=code_key_prefix, sagemaker_session=sagemaker_session + ) + + logger.debug( + "Uploading the model resources to bucket=%s, key_prefix=%s.", + bucket, + code_key_prefix, + ) + s3_upload_path = upload(sagemaker_session, model_path, bucket, code_key_prefix) + logger.debug("Model resources uploaded to: %s", s3_upload_path) + + env_vars = { + "SAGEMAKER_INFERENCE_CODE_DIRECTORY": "/opt/ml/model/code", + "SAGEMAKER_INFERENCE_CODE": "inference.handler", + "SAGEMAKER_REGION": sagemaker_session.boto_region_name, + "SAGEMAKER_SERVE_SECRET_KEY": secret_key, + "LOCAL_PYTHON": platform.python_version(), + } + return s3_upload_path, env_vars diff --git a/src/sagemaker/serve/spec/inference_base.py b/src/sagemaker/serve/spec/inference_base.py new file mode 100644 index 0000000000..23ea6cb01d --- /dev/null +++ b/src/sagemaker/serve/spec/inference_base.py @@ -0,0 +1,45 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Holds templated classes to enable users to provide custom inference scripting capabilities""" +from __future__ import absolute_import +from abc import ABC, abstractmethod + + +class CustomOrchestrator(ABC): + """Templated class to standardize sync entrypoint-based inference scripts""" + + def __init__(self): + self._client = None + + @property + def client(self): + """Boto3 SageMaker runtime client to use with custom orchestrator""" + if not hasattr(self, "_client") or not self._client: + from boto3 import Session + + self._client = Session().client("sagemaker-runtime") + return self._client + + @abstractmethod + def handle(self, data, context=None): + """Abstract class for defining an entrypoint for the model server""" + return NotImplemented + + +class AsyncCustomOrchestrator(ABC): + """Templated class to standardize async entrypoint-based inference scripts""" + + @abstractmethod + async def handle(self, data, context=None): + """Abstract class for defining an aynchronous entrypoint for the model server""" + return NotImplemented diff --git a/src/sagemaker/serve/utils/telemetry_logger.py b/src/sagemaker/serve/utils/telemetry_logger.py index c02fe9bf78..6e7db9043b 100644 --- a/src/sagemaker/serve/utils/telemetry_logger.py +++ b/src/sagemaker/serve/utils/telemetry_logger.py @@ -64,6 +64,7 @@ str(ModelServer.TRITON): 5, str(ModelServer.TGI): 6, str(ModelServer.TEI): 7, + str(ModelServer.SMD): 8, } MLFLOW_MODEL_PATH_CODE = { diff --git a/src/sagemaker/serve/utils/types.py b/src/sagemaker/serve/utils/types.py index e50be62440..b405d85b21 100644 --- a/src/sagemaker/serve/utils/types.py +++ b/src/sagemaker/serve/utils/types.py @@ -19,6 +19,7 @@ def __str__(self): TRITON = 5 TGI = 6 TEI = 7 + SMD = 8 class HardwareType(Enum): diff --git a/tests/integ/sagemaker/serve/constants.py b/tests/integ/sagemaker/serve/constants.py index d5e7a56f83..3f25f6a575 100644 --- a/tests/integ/sagemaker/serve/constants.py +++ b/tests/integ/sagemaker/serve/constants.py @@ -25,6 +25,7 @@ PYTHON_VERSION_IS_NOT_38 = platform.python_version_tuple()[1] != "8" PYTHON_VERSION_IS_NOT_310 = platform.python_version_tuple()[1] != "10" +PYTHON_VERSION_IS_NOT_312 = platform.python_version_tuple()[1] != "12" XGB_RESOURCE_DIR = os.path.join(DATA_DIR, "serve_resources", "xgboost") PYTORCH_SQUEEZENET_RESOURCE_DIR = os.path.join(DATA_DIR, "serve_resources", "pytorch") diff --git a/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py b/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py new file mode 100644 index 0000000000..b72b84aeac --- /dev/null +++ b/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py @@ -0,0 +1,149 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +import pytest +import tests.integ + +from botocore.exceptions import ClientError +from sagemaker.predictor import Predictor +from sagemaker.serve.builder.model_builder import ModelBuilder +from sagemaker.serve.builder.schema_builder import SchemaBuilder +from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements +from sagemaker.utils import unique_name_from_base + +from tests.integ.sagemaker.serve.constants import ( + SERVE_SAGEMAKER_ENDPOINT_TIMEOUT, +) +from tests.integ.timeout import timeout +import logging + +logger = logging.getLogger(__name__) + +sample_input = {"inputs": "What are falcons?", "parameters": {"max_new_tokens": 32}} + +sample_output = [ + { + "generated_text": "Falcons are small to medium-sized birds of prey related to hawks and eagles." + } +] + +LLAMA_2_7B_JS_ID = "meta-textgeneration-llama-2-7b" +LLAMA_IC_NAME = "llama2-mb-ic" +INSTANCE_TYPE = "ml.g5.24xlarge" + + +@pytest.fixture +def model_builder_llama_inference_component(): + return ModelBuilder( + model=LLAMA_2_7B_JS_ID, + schema_builder=SchemaBuilder(sample_input, sample_output), + resource_requirements=ResourceRequirements( + requests={"memory": 98304, "num_accelerators": 4, "copies": 1, "num_cpus": 40} + ), + ) + + +@pytest.mark.skipif( + tests.integ.test_region() not in "us-west-2", + reason="G5 capacity available in PDX.", +) +def test_model_builder_ic_sagemaker_endpoint( + sagemaker_session, + model_builder_llama_inference_component, +): + logger.info("Running in SAGEMAKER_ENDPOINT mode...") + caught_ex = None + + model_builder_llama_inference_component.sagemaker_session = sagemaker_session + model_builder_llama_inference_component.instance_type = INSTANCE_TYPE + + model_builder_llama_inference_component.inference_component_name = unique_name_from_base( + LLAMA_IC_NAME + ) + + iam_client = sagemaker_session.boto_session.client("iam") + role_arn = iam_client.get_role(RoleName="SageMakerRole")["Role"]["Arn"] + + chain = ModelBuilder( + modelbuilder_list=[ + model_builder_llama_inference_component, + ], + role_arn=role_arn, + sagemaker_session=sagemaker_session, + ) + + chain.build() + + with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT): + try: + logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...") + endpoint_name = "llama-ic-endpoint-name" + predictors = chain.deploy( + instance_type=INSTANCE_TYPE, + initial_instance_count=1, + accept_eula=True, + endpoint_name=endpoint_name, + ) + logger.info("Inference components successfully deployed.") + predictors[0].predict(sample_input) + assert len(predictors) == 1 + except Exception as e: + caught_ex = e + finally: + if caught_ex: + logger.exception(caught_ex) + cleanup_resources(sagemaker_session, [LLAMA_IC_NAME]) + assert False, f"{caught_ex} thrown when running mb-IC deployment test." + + cleanup_resources(sagemaker_session, [LLAMA_IC_NAME]) + + +def cleanup_resources(sagemaker_session, ic_base_names): + sm_client = sagemaker_session.sagemaker_client + + endpoint_names = set() + for ic_base_name in ic_base_names: + response = sm_client.list_inference_components( + NameContains=ic_base_name, StatusEquals="InService" + ) + ics = response["InferenceComponents"] + + logger.info(f"Cleaning up {len(ics)} ICs with base name {ic_base_name}.") + for ic in ics: + ic_name = ic["InferenceComponentName"] + ep_name = ic["EndpointName"] + + try: + logger.info(f"Deleting IC with name {ic_name}") + Predictor( + endpoint_name=ep_name, + component_name=ic_name, + sagemaker_session=sagemaker_session, + ).delete_predictor() + sagemaker_session.wait_for_inference_component_deletion( + inference_component_name=ic_name, + poll=10, + ) + endpoint_names.add(ep_name) + except ClientError as e: + logger.warning(e) + + for endpoint_name in endpoint_names: + logger.info(f"Deleting endpoint with name {endpoint_name}") + try: + Predictor( + endpoint_name=endpoint_name, sagemaker_session=sagemaker_session + ).delete_endpoint() + except ClientError as e: + logger.warning(e) diff --git a/tests/unit/sagemaker/image_uris/expected_uris.py b/tests/unit/sagemaker/image_uris/expected_uris.py index 01e4d4991f..eb198454fc 100644 --- a/tests/unit/sagemaker/image_uris/expected_uris.py +++ b/tests/unit/sagemaker/image_uris/expected_uris.py @@ -107,3 +107,12 @@ def base_python_uri(repo, account, region=REGION): domain = ALTERNATE_DOMAINS.get(region, DOMAIN) tag = "1.0" return IMAGE_URI_FORMAT.format(account, region, domain, repo, tag) + + +def sagemaker_distribution_uri(repo, account, tag, processor, region=REGION): + domain = ALTERNATE_DOMAINS.get(region, DOMAIN) + if processor == "cpu": + tag = f"{tag}-cpu" + else: + tag = f"{tag}-gpu" + return IMAGE_URI_FORMAT.format(account, region, domain, repo, tag) diff --git a/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py b/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py new file mode 100644 index 0000000000..d339a50b2e --- /dev/null +++ b/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py @@ -0,0 +1,47 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +import pytest +from sagemaker import image_uris +from tests.unit.sagemaker.image_uris import expected_uris + +INSTANCE_TYPES = {"cpu": "ml.c4.xlarge", "gpu": "ml.p2.xlarge"} + + +def _test_ecr_uri(account, region, version, tag, instance_type, processor): + actual_uri = image_uris.retrieve( + "sagemaker-distribution", region=region, instance_type=instance_type, version=version + ) + expected_uri = expected_uris.sagemaker_distribution_uri( + "sagemaker-distribution-prod", account, tag, processor, region + ) + return expected_uri == actual_uri + + +@pytest.mark.parametrize("load_config", ["sagemaker-distribution.json"], indirect=True) +def test_sagemaker_distribution_ecr_uri(load_config): + VERSIONS = load_config["versions"] + processors = load_config["processors"] + for version in VERSIONS: + SAGEMAKER_DISTRIBUTION_ACCOUNTS = load_config["versions"][version]["registries"] + for region in SAGEMAKER_DISTRIBUTION_ACCOUNTS.keys(): + for processor in processors: + assert _test_ecr_uri( + account=SAGEMAKER_DISTRIBUTION_ACCOUNTS[region], + region=region, + version=version, + tag="3.0.0", + instance_type=INSTANCE_TYPES[processor], + processor=processor, + ) diff --git a/tests/unit/sagemaker/serve/builder/test_model_builder.py b/tests/unit/sagemaker/serve/builder/test_model_builder.py index 6661c6e2bf..de4304d63d 100644 --- a/tests/unit/sagemaker/serve/builder/test_model_builder.py +++ b/tests/unit/sagemaker/serve/builder/test_model_builder.py @@ -74,6 +74,7 @@ ModelServer.MMS, ModelServer.TGI, ModelServer.TEI, + ModelServer.SMD, } mock_session = MagicMock() @@ -2890,6 +2891,86 @@ def test_optimize_for_hf_without_custom_s3_path( }, ) + @patch("sagemaker.serve.builder.model_builder._ServeSettings") + @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_jumpstart") + @patch( + "sagemaker.serve.builder.model_builder.ModelBuilder._is_jumpstart_model_id", + return_value=True, + ) + @patch( + "sagemaker.serve.builder.jumpstart_builder.JumpStart._create_pre_trained_js_model", + return_value=MagicMock(), + ) + def test_build_multiple_inference_component_modelbuilders( + self, + mock_pre_trained_model, + mock_is_jumpstart_model_id, + mock_build_for_js, + mock_serve_settings, + ): + mock_setting_object = mock_serve_settings.return_value + mock_setting_object.role_arn = mock_role_arn + mock_setting_object.s3_model_data_url = mock_s3_model_data_url + + builder1 = ModelBuilder( + model="gpt_llm_burt", inference_component_name="ic1", resource_requirements=Mock() + ) + builder2 = ModelBuilder( + model="gpt_llm_burt", inference_component_name="ic2", resource_requirements=Mock() + ) + + builder3 = ModelBuilder( + model="gpt_llm_burt", inference_component_name="ic3", resource_requirements=Mock() + ) + + chain_builder = ModelBuilder( + modelbuilder_list=[builder1, builder2, builder3], + ) + chain_builder.build(sagemaker_session=mock_session) + assert mock_build_for_js.call_count == 3 + + @patch("sagemaker.serve.builder.model_builder._ServeSettings") + @patch("sagemaker.serve.builder.model_builder.ModelBuilder._build_for_jumpstart") + @patch( + "sagemaker.serve.builder.model_builder.ModelBuilder._is_jumpstart_model_id", + return_value=True, + ) + @patch( + "sagemaker.serve.builder.jumpstart_builder.JumpStart._create_pre_trained_js_model", + return_value=MagicMock(), + ) + @patch( + "sagemaker.serve.builder.model_builder.ModelBuilder._does_ic_exist", + return_value=True, + ) + @patch( + "sagemaker.session.Session.update_inference_component", + return_value=MagicMock(), + ) + def test_deploy_existing_inference_component_calls_update_inference_component( + self, + mock_update_inference_component, + mock_ic_exists, + mock_pre_trained_model, + mock_is_jumpstart_model_id, + mock_build_for_js, + mock_serve_settings, + ): + mock_setting_object = mock_serve_settings.return_value + mock_setting_object.role_arn = mock_role_arn + mock_setting_object.s3_model_data_url = mock_s3_model_data_url + + builder1 = ModelBuilder( + model="gpt_llm_burt", inference_component_name="ic1", resource_requirements=Mock() + ) + + chain_builder = ModelBuilder( + modelbuilder_list=[builder1], + ).build() + inputs = {"endpoint_name": "endpoint-001"} + chain_builder.deploy(**inputs) + assert mock_update_inference_component.call_count == 1 + def test_deploy_invalid_inputs(self): model_builder = ModelBuilder( model="meta-llama/Meta-Llama-3-8B-Instruct", @@ -2902,7 +2983,7 @@ def test_deploy_invalid_inputs(self): try: model_builder.deploy(**inputs) except ValueError as e: - assert "Model Needs to be built before deploying" in str(e) + assert "Model needs to be built before deploying" in str(e) @patch("sagemaker.serve.builder.model_builder.ModelBuilder._is_jumpstart_model_id") def test_display_benchmark_metrics_non_string_model(self, mock_is_jumpstart): From 0dae5c99d12f64dc4e3824025a1dc27a4bcb85b0 Mon Sep 17 00:00:00 2001 From: Namrata Madan Date: Thu, 1 May 2025 09:26:48 -0700 Subject: [PATCH 068/164] fix: pin mamba version to 24.11.3-2 to avoid inconsistent test runs (#5149) Co-authored-by: Namrata Madan --- tests/integ/sagemaker/conftest.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/integ/sagemaker/conftest.py b/tests/integ/sagemaker/conftest.py index a0a60fc334..fe7e7d61f8 100644 --- a/tests/integ/sagemaker/conftest.py +++ b/tests/integ/sagemaker/conftest.py @@ -46,7 +46,7 @@ 'SHELL ["/bin/bash", "-c"]\n' "RUN apt-get update -y \ && apt-get install -y unzip curl\n\n" - "RUN curl -L -O 'https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh' \ + "RUN curl -L -O 'https://github.com/conda-forge/miniforge/releases/download/24.11.3-2/Miniforge3-Linux-x86_64.sh' \ && bash Miniforge3-Linux-x86_64.sh -b -p '/opt/conda' \ && /opt/conda/bin/conda init bash\n\n" "ENV PATH $PATH:/opt/conda/bin\n" From a896bc604ce4a84935d1993a4c14862db90a83e9 Mon Sep 17 00:00:00 2001 From: Aditi Sharma <165942273+Aditi2424@users.noreply.github.com> Date: Thu, 1 May 2025 14:34:58 -0700 Subject: [PATCH 069/164] Add model server timeout (#5151) Co-authored-by: adishaa --- tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py b/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py index ea65f998c8..3b59cae321 100644 --- a/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py +++ b/tests/integ/sagemaker/serve/test_serve_js_deep_unit_tests.py @@ -64,6 +64,7 @@ def test_js_model_with_optimize_speculative_decoding_config_gated_requests_are_e "Image": ANY, "Environment": { "SAGEMAKER_PROGRAM": "inference.py", + "SAGEMAKER_MODEL_SERVER_TIMEOUT": "3600", "ENDPOINT_SERVER_TIMEOUT": "3600", "MODEL_CACHE_ROOT": "/opt/ml/model", "SAGEMAKER_ENV": "1", @@ -150,6 +151,7 @@ def test_js_model_with_optimize_sharding_and_resource_requirements_requests_are_ "Image": ANY, "Environment": { "SAGEMAKER_PROGRAM": "inference.py", + "SAGEMAKER_MODEL_SERVER_TIMEOUT": "3600", "ENDPOINT_SERVER_TIMEOUT": "3600", "MODEL_CACHE_ROOT": "/opt/ml/model", "SAGEMAKER_ENV": "1", @@ -237,6 +239,7 @@ def test_js_model_with_optimize_quantization_on_pre_optimized_model_requests_are "Image": ANY, "Environment": { "SAGEMAKER_PROGRAM": "inference.py", + "SAGEMAKER_MODEL_SERVER_TIMEOUT": "3600", "ENDPOINT_SERVER_TIMEOUT": "3600", "MODEL_CACHE_ROOT": "/opt/ml/model", "SAGEMAKER_ENV": "1", From 903cb8ae76392eea9e7c60340fa4baf5e65138b4 Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Thu, 1 May 2025 14:40:46 -0700 Subject: [PATCH 070/164] Add Owner ID check for bucket with path when prefix is provided (#5146) * Fix Flake8 Violations * Add Owner ID check for bucket with path when prefix is provided **Description** Previously we called the head_bucket call to ensure the owner ID check, but this doesnt take into consideration cases where the s3 path is provided through the prefix. This change makes sure that director level permissions are supported. **Testing Done** Tested through unit tests, integ tests and manual testing through the installation file. Yes * Address PR comment * Codestyle fixes * Minor fix * Codestyle fixes * Fix Unit tests --- src/sagemaker/session.py | 21 +++++++++++++----- tests/unit/test_default_bucket.py | 37 +++++++++++++++++++++++++++++++ 2 files changed, 53 insertions(+), 5 deletions(-) diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py index 797d559348..2cc18f6989 100644 --- a/src/sagemaker/session.py +++ b/src/sagemaker/session.py @@ -635,7 +635,6 @@ def _create_s3_bucket_if_it_does_not_exist(self, bucket_name, region): elif self._default_bucket_set_by_sdk: self.general_bucket_check_if_user_has_permission(bucket_name, s3, bucket, region, False) - expected_bucket_owner_id = self.account_id() self.expected_bucket_owner_id_bucket_check(bucket_name, s3, expected_bucket_owner_id) @@ -649,9 +648,16 @@ def expected_bucket_owner_id_bucket_check(self, bucket_name, s3, expected_bucket """ try: - s3.meta.client.head_bucket( - Bucket=bucket_name, ExpectedBucketOwner=expected_bucket_owner_id - ) + if self.default_bucket_prefix: + s3.meta.client.list_objects_v2( + Bucket=bucket_name, + Prefix=self.default_bucket_prefix, + ExpectedBucketOwner=expected_bucket_owner_id, + ) + else: + s3.meta.client.head_bucket( + Bucket=bucket_name, ExpectedBucketOwner=expected_bucket_owner_id + ) except ClientError as e: error_code = e.response["Error"]["Code"] message = e.response["Error"]["Message"] @@ -682,7 +688,12 @@ def general_bucket_check_if_user_has_permission( bucket_creation_date_none (bool):Indicating whether S3 bucket already exists or not """ try: - s3.meta.client.head_bucket(Bucket=bucket_name) + if self.default_bucket_prefix: + s3.meta.client.list_objects_v2( + Bucket=bucket_name, Prefix=self.default_bucket_prefix + ) + else: + s3.meta.client.head_bucket(Bucket=bucket_name) except ClientError as e: error_code = e.response["Error"]["Code"] message = e.response["Error"]["Message"] diff --git a/tests/unit/test_default_bucket.py b/tests/unit/test_default_bucket.py index 6ce4b50c75..dca1d3dc85 100644 --- a/tests/unit/test_default_bucket.py +++ b/tests/unit/test_default_bucket.py @@ -39,6 +39,19 @@ def sagemaker_session(): return sagemaker_session +@pytest.fixture() +def sagemaker_session_with_bucket_name_and_prefix(): + boto_mock = MagicMock(name="boto_session", region_name=REGION) + boto_mock.client("sts").get_caller_identity.return_value = {"Account": ACCOUNT_ID} + sagemaker_session = sagemaker.Session( + boto_session=boto_mock, + default_bucket="XXXXXXXXXXXXX", + default_bucket_prefix="sample-prefix", + ) + sagemaker_session.boto_session.resource("s3").Bucket().creation_date = None + return sagemaker_session + + def test_default_bucket_s3_create_call(sagemaker_session): error = ClientError( error_response={"Error": {"Code": "404", "Message": "Not Found"}}, @@ -96,6 +109,30 @@ def test_default_bucket_s3_needs_bucket_owner_access(sagemaker_session, datetime assert sagemaker_session._default_bucket is None +def test_default_bucket_with_prefix_s3_needs_bucket_owner_access( + sagemaker_session_with_bucket_name_and_prefix, datetime_obj, caplog +): + with pytest.raises(ClientError): + error = ClientError( + error_response={"Error": {"Code": "403", "Message": "Forbidden"}}, + operation_name="foo", + ) + sagemaker_session_with_bucket_name_and_prefix.boto_session.resource( + "s3" + ).meta.client.list_objects_v2.side_effect = error + sagemaker_session_with_bucket_name_and_prefix.boto_session.resource("s3").Bucket( + name=DEFAULT_BUCKET_NAME + ).creation_date = None + sagemaker_session_with_bucket_name_and_prefix.default_bucket() + + error_message = "Please try again after adding appropriate access." + assert error_message in caplog.text + assert sagemaker_session_with_bucket_name_and_prefix._default_bucket is None + sagemaker_session_with_bucket_name_and_prefix.boto_session.resource( + "s3" + ).meta.client.list_objects_v2.assert_called_once() + + def test_default_bucket_s3_custom_bucket_input(sagemaker_session, datetime_obj, caplog): sagemaker_session._default_bucket_name_override = "custom-bucket-override" error = ClientError( From 87372dbfd0935b82c8348f375a9dec5cc66297f6 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 2 May 2025 03:24:43 +0000 Subject: [PATCH 071/164] prepare release v2.244.0 --- CHANGELOG.md | 14 ++++++++++++++ VERSION | 2 +- 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 7db2fff71d..eb0278b42a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,19 @@ # Changelog +## v2.244.0 (2025-05-02) + +### Features + + * support custom workflow deployment in ModelBuilder using SMD image. + +### Bug Fixes and Other Changes + + * Add Owner ID check for bucket with path when prefix is provided + * Add model server timeout + * pin mamba version to 24.11.3-2 to avoid inconsistent test runs + * Update ModelTrainer to support s3 uri and tar.gz file as source_dir + * chore: add huggingface images + ## v2.243.3 (2025-04-23) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index 250b3d6920..e5b6de2460 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.243.4.dev0 +2.244.0 From 85056eb1722f3ade678820f84760b6714485e2d9 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 2 May 2025 03:24:47 +0000 Subject: [PATCH 072/164] update development version to v2.244.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index e5b6de2460..d372855290 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.0 +2.244.1.dev0 From bb803c9e6d72e7333202fbecb0430cf2d46df24f Mon Sep 17 00:00:00 2001 From: varunmoris <176621270+varunmoris@users.noreply.github.com> Date: Fri, 2 May 2025 12:34:55 -0400 Subject: [PATCH 073/164] chore: Add tei 1.6.0 image (#5145) * chore: add huggingface images * chore: add tei 1.6 image * chore: add tei 1.6.0 to tei mapping in tests --- .../image_uri_config/huggingface-tei-cpu.json | 50 ++++++++++++++++++- .../image_uri_config/huggingface-tei.json | 50 ++++++++++++++++++- .../image_uris/test_huggingface_llm.py | 2 + 3 files changed, 100 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface-tei-cpu.json b/src/sagemaker/image_uri_config/huggingface-tei-cpu.json index e3139c3d2c..1e81df6de4 100644 --- a/src/sagemaker/image_uri_config/huggingface-tei-cpu.json +++ b/src/sagemaker/image_uri_config/huggingface-tei-cpu.json @@ -5,7 +5,8 @@ ], "version_aliases": { "1.2": "1.2.3", - "1.4": "1.4.0" + "1.4": "1.4.0", + "1.6": "1.6.0" }, "versions": { "1.2.3": { @@ -101,6 +102,53 @@ "container_version": { "cpu": "ubuntu22.04" } + }, + "1.6.0":{ + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "510948584623", + "ap-east-1": "651117190479", + "ap-northeast-1": "354813040037", + "ap-northeast-2": "366743142698", + "ap-northeast-3": "867004704886", + "ap-south-1": "720646828776", + "ap-south-2": "628508329040", + "ap-southeast-1": "121021644041", + "ap-southeast-2": "783357654285", + "ap-southeast-3": "951798379941", + "ap-southeast-4": "106583098589", + "ca-central-1": "341280168497", + "ca-west-1": "190319476487", + "cn-north-1": "450853457545", + "cn-northwest-1": "451049120500", + "eu-central-1": "492215442770", + "eu-central-2": "680994064768", + "eu-north-1": "662702820516", + "eu-south-1": "978288397137", + "eu-south-2": "104374241257", + "eu-west-1": "141502667606", + "eu-west-2": "764974769150", + "eu-west-3": "659782779980", + "il-central-1": "898809789911", + "me-central-1": "272398656194", + "me-south-1": "801668240914", + "sa-east-1": "737474898029", + "us-east-1": "683313688378", + "us-east-2": "257758044811", + "us-gov-east-1": "237065988967", + "us-gov-west-1": "414596584902", + "us-iso-east-1": "833128469047", + "us-isob-east-1": "281123927165", + "us-west-1": "746614075791", + "us-west-2": "246618743249" + }, + "tag_prefix": "2.0.1-tei1.6.0", + "repository": "tei-cpu", + "container_version": { + "cpu": "ubuntu22.04" + } } } } diff --git a/src/sagemaker/image_uri_config/huggingface-tei.json b/src/sagemaker/image_uri_config/huggingface-tei.json index ccf273e451..c2515daf12 100644 --- a/src/sagemaker/image_uri_config/huggingface-tei.json +++ b/src/sagemaker/image_uri_config/huggingface-tei.json @@ -5,7 +5,8 @@ ], "version_aliases": { "1.2": "1.2.3", - "1.4": "1.4.0" + "1.4": "1.4.0", + "1.6": "1.6.0" }, "versions": { "1.2.3": { @@ -101,6 +102,53 @@ "container_version": { "gpu": "cu122-ubuntu22.04" } + }, + "1.6.0": { + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "510948584623", + "ap-east-1": "651117190479", + "ap-northeast-1": "354813040037", + "ap-northeast-2": "366743142698", + "ap-northeast-3": "867004704886", + "ap-south-1": "720646828776", + "ap-south-2": "628508329040", + "ap-southeast-1": "121021644041", + "ap-southeast-2": "783357654285", + "ap-southeast-3": "951798379941", + "ap-southeast-4": "106583098589", + "ca-central-1": "341280168497", + "ca-west-1": "190319476487", + "cn-north-1": "450853457545", + "cn-northwest-1": "451049120500", + "eu-central-1": "492215442770", + "eu-central-2": "680994064768", + "eu-north-1": "662702820516", + "eu-south-1": "978288397137", + "eu-south-2": "104374241257", + "eu-west-1": "141502667606", + "eu-west-2": "764974769150", + "eu-west-3": "659782779980", + "il-central-1": "898809789911", + "me-central-1": "272398656194", + "me-south-1": "801668240914", + "sa-east-1": "737474898029", + "us-east-1": "683313688378", + "us-east-2": "257758044811", + "us-gov-east-1": "237065988967", + "us-gov-west-1": "414596584902", + "us-iso-east-1": "833128469047", + "us-isob-east-1": "281123927165", + "us-west-1": "746614075791", + "us-west-2": "246618743249" + }, + "tag_prefix": "2.0.1-tei1.6.0", + "repository": "tei", + "container_version": { + "gpu": "cu122-ubuntu22.04" + } } } } diff --git a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py index 084c2d1438..6598117027 100644 --- a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py +++ b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py @@ -23,10 +23,12 @@ "gpu": { "1.2.3": "2.0.1-tei1.2.3-gpu-py310-cu122-ubuntu22.04", "1.4.0": "2.0.1-tei1.4.0-gpu-py310-cu122-ubuntu22.04", + "1.6.0": "2.0.1-tei1.6.0-gpu-py310-cu122-ubuntu22.04", }, "cpu": { "1.2.3": "2.0.1-tei1.2.3-cpu-py310-ubuntu22.04", "1.4.0": "2.0.1-tei1.4.0-cpu-py310-ubuntu22.04", + "1.6.0": "2.0.1-tei1.6.0-cpu-py310-ubuntu22.04", }, } HF_VERSIONS_MAPPING = { From b8771e3155e09f82c0cfed9093b1d4fa5392f80f Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 2 May 2025 11:09:47 -0700 Subject: [PATCH 074/164] build(deps): bump mlflow in /tests/data/serve_resources/mlflow/pytorch (#5098) Bumps [mlflow](https://github.com/mlflow/mlflow) from 2.13.2 to 2.20.3. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](https://github.com/mlflow/mlflow/compare/v2.13.2...v2.20.3) --- updated-dependencies: - dependency-name: mlflow dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- tests/data/serve_resources/mlflow/pytorch/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/serve_resources/mlflow/pytorch/requirements.txt b/tests/data/serve_resources/mlflow/pytorch/requirements.txt index aacc85cb91..a3eb04ed4f 100644 --- a/tests/data/serve_resources/mlflow/pytorch/requirements.txt +++ b/tests/data/serve_resources/mlflow/pytorch/requirements.txt @@ -1,4 +1,4 @@ -mlflow==2.13.2 +mlflow==2.20.3 astunparse==1.6.3 cffi==1.16.0 cloudpickle==2.2.1 From a9b38b18c1d506af0242ddf78684eb7f89d3bc71 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sun, 4 May 2025 20:33:10 -0700 Subject: [PATCH 075/164] build(deps): bump mlflow (#5155) Bumps [mlflow](https://github.com/mlflow/mlflow) from 2.13.2 to 2.20.3. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](https://github.com/mlflow/mlflow/compare/v2.13.2...v2.20.3) --- updated-dependencies: - dependency-name: mlflow dependency-version: 2.20.3 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- tests/data/serve_resources/mlflow/tensorflow/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/serve_resources/mlflow/tensorflow/requirements.txt b/tests/data/serve_resources/mlflow/tensorflow/requirements.txt index ff99d3b92e..9b64992ac8 100644 --- a/tests/data/serve_resources/mlflow/tensorflow/requirements.txt +++ b/tests/data/serve_resources/mlflow/tensorflow/requirements.txt @@ -1,4 +1,4 @@ -mlflow==2.13.2 +mlflow==2.20.3 cloudpickle==2.2.1 numpy==1.26.4 tensorflow==2.16.1 From 9ba4faa52a1db28f3793044332139c34675d1705 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sun, 4 May 2025 22:52:31 -0700 Subject: [PATCH 076/164] build(deps): bump scikit-learn (#5156) Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.3.2 to 1.5.1. - [Release notes](https://github.com/scikit-learn/scikit-learn/releases) - [Commits](https://github.com/scikit-learn/scikit-learn/compare/1.3.2...1.5.1) --- updated-dependencies: - dependency-name: scikit-learn dependency-version: 1.5.1 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- tests/data/serve_resources/mlflow/xgboost/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/serve_resources/mlflow/xgboost/requirements.txt b/tests/data/serve_resources/mlflow/xgboost/requirements.txt index 6f879340a7..30fc49cc97 100644 --- a/tests/data/serve_resources/mlflow/xgboost/requirements.txt +++ b/tests/data/serve_resources/mlflow/xgboost/requirements.txt @@ -3,6 +3,6 @@ lz4==4.3.2 numpy==1.26.4 pandas==2.0.3 psutil==5.9.8 -scikit-learn==1.3.2 +scikit-learn==1.5.1 scipy==1.11.3 xgboost==1.7.1 From e747b03dcc5911c152cc9130cea960c73bbafd13 Mon Sep 17 00:00:00 2001 From: "parknate@" Date: Mon, 5 May 2025 17:50:44 -0700 Subject: [PATCH 077/164] Improve error logging and documentation for issue 4007 (#5153) * Improve error logging and documentation for issue 4007 * Add hyperlink to RTDs --- doc/frameworks/pytorch/using_pytorch.rst | 46 ++++++++++++++++++++++++ src/sagemaker/utils.py | 38 ++++++++++++++------ 2 files changed, 74 insertions(+), 10 deletions(-) diff --git a/doc/frameworks/pytorch/using_pytorch.rst b/doc/frameworks/pytorch/using_pytorch.rst index 4141dd84db..9bd48ef984 100644 --- a/doc/frameworks/pytorch/using_pytorch.rst +++ b/doc/frameworks/pytorch/using_pytorch.rst @@ -1048,6 +1048,43 @@ see `For versions 1.1 and lower <#for-versions-1.1-and-lower>`_. Where ``requirements.txt`` is an optional file that specifies dependencies on third-party libraries. +Important Packaging Instructions +-------------------------------- + +When creating your model artifact (``model.tar.gz``), follow these steps to avoid common deployment issues: + +1. Navigate to the directory containing your model files: + + .. code:: bash + + cd my_model + +2. Create the tar archive from within this directory: + + .. code:: bash + + tar czvf ../model.tar.gz * + +**Common Mistakes to Avoid:** + +* Do NOT create the archive from the parent directory using ``tar czvf model.tar.gz my_model/``. + This creates an extra directory level that will cause deployment errors. +* Ensure ``inference.py`` is directly under the ``code/`` directory in your archive. +* Verify your archive structure using: + + .. code:: bash + + tar tvf model.tar.gz + + You should see output similar to: + + :: + + model.pth + code/ + code/inference.py + code/requirements.txt + Create a ``PyTorchModel`` object -------------------------------- @@ -1066,6 +1103,15 @@ Now call the :class:`sagemaker.pytorch.model.PyTorchModel` constructor to create Now you can call the ``predict()`` method to get predictions from your deployed model. +Troubleshooting +--------------- + +If you encounter a ``FileNotFoundError`` for ``inference.py``, check: + +1. That your model artifact is packaged correctly following the instructions above +2. The structure of your ``model.tar.gz`` file matches the expected layout +3. You're creating the archive from within the model directory, not from its parent + *********************************************** Attach an estimator to an existing training job *********************************************** diff --git a/src/sagemaker/utils.py b/src/sagemaker/utils.py index 1a75a3a5cc..d4faa5ad9f 100644 --- a/src/sagemaker/utils.py +++ b/src/sagemaker/utils.py @@ -13,10 +13,12 @@ """Placeholder docstring""" from __future__ import absolute_import +import abc import contextlib import copy import errno import inspect +import json import logging import os import random @@ -25,31 +27,30 @@ import tarfile import tempfile import time -from functools import lru_cache -from typing import Union, Any, List, Optional, Dict -import json -import abc import uuid from datetime import datetime -from os.path import abspath, realpath, dirname, normpath, join as joinpath - +from functools import lru_cache from importlib import import_module +from os.path import abspath, dirname +from os.path import join as joinpath +from os.path import normpath, realpath +from typing import Any, Dict, List, Optional, Union import boto3 import botocore from botocore.utils import merge_dicts -from six.moves.urllib import parse from six import viewitems +from six.moves.urllib import parse from sagemaker import deprecations from sagemaker.config import validate_sagemaker_config from sagemaker.config.config_utils import ( - _log_sagemaker_config_single_substitution, _log_sagemaker_config_merge, + _log_sagemaker_config_single_substitution, ) from sagemaker.enums import RoutingStrategy from sagemaker.session_settings import SessionSettings -from sagemaker.workflow import is_pipeline_variable, is_pipeline_parameter_string +from sagemaker.workflow import is_pipeline_parameter_string, is_pipeline_variable from sagemaker.workflow.entities import PipelineVariable ALTERNATE_DOMAINS = { @@ -624,7 +625,24 @@ def _create_or_update_code_dir( if os.path.exists(os.path.join(code_dir, inference_script)): pass else: - raise + raise FileNotFoundError( + f"Could not find '{inference_script}'. Common solutions:\n" + "1. Make sure inference.py exists in the code/ directory\n" + "2. Package your model correctly:\n" + " - ✅ DO: Navigate to the directory containing model files and run:\n" + " cd /path/to/model_files\n" + " tar czvf ../model.tar.gz *\n" + " - ❌ DON'T: Create from parent directory:\n" + " tar czvf model.tar.gz model/\n" + "\nExpected structure in model.tar.gz:\n" + " ├── model.pth (or your model file)\n" + " └── code/\n" + " ├── inference.py\n" + " └── requirements.txt\n" + "\nFor more details, see the documentation:\n" + + "https://sagemaker.readthedocs.io/en/stable/" + + "frameworks/pytorch/using_pytorch.html#bring-your-own-model" + ) for dependency in dependencies: lib_dir = os.path.join(code_dir, "lib") From c66a39ef7e876be1d949eeda698b1036b4b90628 Mon Sep 17 00:00:00 2001 From: Namrata Madan Date: Thu, 8 May 2025 13:26:53 -0700 Subject: [PATCH 078/164] fix: fix bad initialization script error message (#5152) Co-authored-by: Namrata Madan --- src/sagemaker/workflow/notebook_job_step.py | 12 +++++++----- .../workflow/test_notebook_job_step.py | 18 +++++++++--------- 2 files changed, 16 insertions(+), 14 deletions(-) diff --git a/src/sagemaker/workflow/notebook_job_step.py b/src/sagemaker/workflow/notebook_job_step.py index ca0ecac15b..8db95a2fae 100644 --- a/src/sagemaker/workflow/notebook_job_step.py +++ b/src/sagemaker/workflow/notebook_job_step.py @@ -243,25 +243,27 @@ def _validate_inputs(self): # input notebook is required if not self.input_notebook or not os.path.isfile(self.input_notebook): errors.append( - f"The required input notebook({self.input_notebook}) is not a valid " f"file." + f"The required input notebook ({self.input_notebook}) is not a valid file." ) # init script is optional if self.initialization_script and not os.path.isfile(self.initialization_script): - errors.append(f"The initialization script({self.input_notebook}) is not a valid file.") + errors.append( + f"The initialization script ({self.initialization_script}) is not a valid file." + ) if self.additional_dependencies: for path in self.additional_dependencies: if not os.path.exists(path): errors.append( - f"The path({path}) specified in additional dependencies does not exist." + f"The path ({path}) specified in additional dependencies does not exist." ) # image uri is required if not self.image_uri or self._region_from_session not in self.image_uri: errors.append( - f"The image uri(specified as {self.image_uri}) is required and " + f"The image uri (specified as {self.image_uri}) is required and " f"should be hosted in same region of the session" - f"({self._region_from_session})." + f" ({self._region_from_session})." ) if not self.kernel_name: diff --git a/tests/unit/sagemaker/workflow/test_notebook_job_step.py b/tests/unit/sagemaker/workflow/test_notebook_job_step.py index 6a5bb20daa..aad6767953 100644 --- a/tests/unit/sagemaker/workflow/test_notebook_job_step.py +++ b/tests/unit/sagemaker/workflow/test_notebook_job_step.py @@ -199,11 +199,11 @@ def test_invalid_inputs_required_fields_passed_as_none(self): in str(context.exception) ) self.assertTrue( - "The required input notebook(None) is not a valid file." in str(context.exception) + "The required input notebook (None) is not a valid file." in str(context.exception) ) self.assertTrue( - "The image uri(specified as None) is required and should be hosted in " - "same region of the session(us-west-2)." in str(context.exception) + "The image uri (specified as None) is required and should be hosted in " + "same region of the session (us-west-2)." in str(context.exception) ) self.assertTrue("The kernel name is required." in str(context.exception)) @@ -222,19 +222,19 @@ def test_invalid_paths_to_upload(self): ).arguments self.assertTrue( - "The required input notebook(path/non-existing-file) is not a valid file." + "The required input notebook (path/non-existing-file) is not a valid file." in str(context.exception) ) self.assertTrue( - "The initialization script(path/non-existing-file) is not a valid file." + "The initialization script (non-existing-script) is not a valid file." in str(context.exception) ) self.assertTrue( - "The path(/tmp/non-existing-folder) specified in additional dependencies " + "The path (/tmp/non-existing-folder) specified in additional dependencies " "does not exist." in str(context.exception) ) self.assertTrue( - "The path(path2/non-existing-file) specified in additional dependencies " + "The path (path2/non-existing-file) specified in additional dependencies " "does not exist." in str(context.exception) ) @@ -251,9 +251,9 @@ def test_image_uri_is_not_in_the_expected_region(self): ).arguments self.assertTrue( - "The image uri(specified as 236514542706.dkr.ecr.us-east-9.amazonaws.com/" + "The image uri (specified as 236514542706.dkr.ecr.us-east-9.amazonaws.com/" "sagemaker-data-science) is required and should be hosted in " - "same region of the session(us-west-2)." in str(context.exception) + "same region of the session (us-west-2)." in str(context.exception) ) def test_invalid_notebook_job_name(self): From b50b6fc5c746b00073a215eaa0d801d0b1a03e32 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Thu, 8 May 2025 17:47:29 -0700 Subject: [PATCH 079/164] fix: pin test dependency (#5165) --- requirements/extras/test_requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 3e6200ee3e..9277c55ecd 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -16,6 +16,7 @@ stopit==1.1.2 # Update tox.ini to have correct version of airflow constraints file apache-airflow==2.10.4 apache-airflow-providers-amazon==7.2.1 +Flask-Limiter==3.12 attrs>=23.1.0,<24 fabric==3.2.2 requests==2.32.2 From 67a3e5a96edc8ea97b97a536a172c5f913c20a76 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Fri, 9 May 2025 10:50:52 -0700 Subject: [PATCH 080/164] fix: Map llama models to correct script (#5159) --- .../modules/train/sm_recipes/utils.py | 2 +- .../modules/train/sm_recipes/test_utils.py | 66 +++++++++---------- 2 files changed, 34 insertions(+), 34 deletions(-) diff --git a/src/sagemaker/modules/train/sm_recipes/utils.py b/src/sagemaker/modules/train/sm_recipes/utils.py index 549645cbe2..6b39add6cd 100644 --- a/src/sagemaker/modules/train/sm_recipes/utils.py +++ b/src/sagemaker/modules/train/sm_recipes/utils.py @@ -129,7 +129,7 @@ def _get_trainining_recipe_gpu_model_name_and_script(model_type: str): """Get the model base name and script for the training recipe.""" model_type_to_script = { - "llama_v3": ("llama", "llama_pretrain.py"), + "llama": ("llama", "llama_pretrain.py"), "mistral": ("mistral", "mistral_pretrain.py"), "mixtral": ("mixtral", "mixtral_pretrain.py"), "deepseek": ("deepseek", "deepseek_pretrain.py"), diff --git a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py index f5f7ceb083..585a4d2745 100644 --- a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py +++ b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py @@ -180,36 +180,36 @@ def test_get_args_from_recipe_compute( assert mock_trainium_args.call_count == 0 assert args is None - @pytest.mark.parametrize( - "test_case", - [ - { - "model_type": "llama_v3", - "script": "llama_pretrain.py", - "model_base_name": "llama_v3", - }, - { - "model_type": "mistral", - "script": "mistral_pretrain.py", - "model_base_name": "mistral", - }, - { - "model_type": "deepseek_llamav3", - "script": "deepseek_pretrain.py", - "model_base_name": "deepseek", - }, - { - "model_type": "deepseek_qwenv2", - "script": "deepseek_pretrain.py", - "model_base_name": "deepseek", - }, - ], - ) - def test_get_trainining_recipe_gpu_model_name_and_script(test_case): - model_type = test_case["model_type"] - script = test_case["script"] - model_base_name, script = _get_trainining_recipe_gpu_model_name_and_script( - model_type, script - ) - assert model_base_name == test_case["model_base_name"] - assert script == test_case["script"] + +@pytest.mark.parametrize( + "test_case", + [ + {"model_type": "llama_v4", "script": "llama_pretrain.py", "model_base_name": "llama"}, + { + "model_type": "llama_v3", + "script": "llama_pretrain.py", + "model_base_name": "llama", + }, + { + "model_type": "mistral", + "script": "mistral_pretrain.py", + "model_base_name": "mistral", + }, + { + "model_type": "deepseek_llamav3", + "script": "deepseek_pretrain.py", + "model_base_name": "deepseek", + }, + { + "model_type": "deepseek_qwenv2", + "script": "deepseek_pretrain.py", + "model_base_name": "deepseek", + }, + ], +) +def test_get_trainining_recipe_gpu_model_name_and_script(test_case): + model_type = test_case["model_type"] + script = test_case["script"] + model_base_name, script = _get_trainining_recipe_gpu_model_name_and_script(model_type) + assert model_base_name == test_case["model_base_name"] + assert script == test_case["script"] From 246d5606b9183f2e12d21b4a3d08e5a83ba32df6 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Fri, 9 May 2025 14:42:51 -0700 Subject: [PATCH 081/164] fix: honor json serialization of HPs (#5164) * fix: honor json serialization of HPs * test * fix --- .../modules/train/container_drivers/common/utils.py | 9 --------- .../modules/train/container_drivers/test_utils.py | 10 ++++++++-- 2 files changed, 8 insertions(+), 11 deletions(-) diff --git a/src/sagemaker/modules/train/container_drivers/common/utils.py b/src/sagemaker/modules/train/container_drivers/common/utils.py index c07aa1359a..a94416550d 100644 --- a/src/sagemaker/modules/train/container_drivers/common/utils.py +++ b/src/sagemaker/modules/train/container_drivers/common/utils.py @@ -124,8 +124,6 @@ def safe_deserialize(data: Any) -> Any: This function handles the following cases: 1. If `data` is not a string, it returns the input as-is. - 2. If `data` is a string and matches common boolean values ("true" or "false"), - it returns the corresponding boolean value (True or False). 3. If `data` is a JSON-encoded string, it attempts to deserialize it using `json.loads()`. 4. If `data` is a string but cannot be decoded as JSON, it returns the original string. @@ -134,13 +132,6 @@ def safe_deserialize(data: Any) -> Any: """ if not isinstance(data, str): return data - - lower_data = data.lower() - if lower_data in ["true"]: - return True - if lower_data in ["false"]: - return False - try: return json.loads(data) except json.JSONDecodeError: diff --git a/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py b/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py index beff06e8d8..c563e0607f 100644 --- a/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py +++ b/tests/unit/sagemaker/modules/train/container_drivers/test_utils.py @@ -59,8 +59,14 @@ def test_safe_deserialize_not_a_string(): def test_safe_deserialize_boolean_strings(): assert safe_deserialize("true") is True assert safe_deserialize("false") is False - assert safe_deserialize("True") is True - assert safe_deserialize("False") is False + + # The below are not valid JSON booleans + assert safe_deserialize("True") == "True" + assert safe_deserialize("False") == "False" + assert safe_deserialize("TRUE") == "TRUE" + assert safe_deserialize("FALSE") == "FALSE" + assert safe_deserialize("tRuE") == "tRuE" + assert safe_deserialize("fAlSe") == "fAlSe" def test_safe_deserialize_valid_json_string(): From c9b420aa91ae4f464226bc62f8ee798aae2c76d4 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Fri, 9 May 2025 14:55:56 -0700 Subject: [PATCH 082/164] chore: Allow omegaconf >=2.2,<3 (#5168) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index c5c9bf9874..c6508f54ad 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -40,7 +40,7 @@ dependencies = [ "importlib-metadata>=1.4.0,<7.0", "jsonschema", "numpy==1.26.4", - "omegaconf>=2.2,<=2.3", + "omegaconf>=2.2,<3", "packaging>=23.0,<25", "pandas", "pathos", From 14d7de1f3cda671831965793867d80eaf4142a99 Mon Sep 17 00:00:00 2001 From: Roman A <121314722+GameRoMan@users.noreply.github.com> Date: Fri, 9 May 2025 23:01:37 +0100 Subject: [PATCH 083/164] Fix type annotations (#5166) --- .../feature_store/feature_processor/_input_offset_parser.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/feature_store/feature_processor/_input_offset_parser.py b/src/sagemaker/feature_store/feature_processor/_input_offset_parser.py index 17e4139bc6..2b66553ab3 100644 --- a/src/sagemaker/feature_store/feature_processor/_input_offset_parser.py +++ b/src/sagemaker/feature_store/feature_processor/_input_offset_parser.py @@ -72,14 +72,16 @@ def get_offset_datetime(self, offset: Optional[str]) -> datetime: return self.now + offset_td - def get_offset_date_year_month_day_hour(self, offset: Optional[str]) -> Tuple[str]: + def get_offset_date_year_month_day_hour( + self, offset: Optional[str] + ) -> Tuple[str, str, str, str]: """Get the year, month, day and hour based on offset diff. Args: offset (Optional[str]): Offset that is used for target date calcluation. Returns: - Tuple[str]: A tuple that consists of extracted year, month, day, hour from offset date. + Tuple[str, str, str, str]: A tuple that consists of extracted year, month, day, hour from offset date. """ if offset is None: return (None, None, None, None) From 40432b3e8ecb419769d3514b53f2f0f01048f64f Mon Sep 17 00:00:00 2001 From: Molly He Date: Mon, 12 May 2025 10:02:47 -0700 Subject: [PATCH 084/164] remove --strip-component for untar source tar.gz (#5163) * remove --strip-component for untar source tar.gz * update code.tar.gz in test --------- Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> --- src/sagemaker/modules/train/model_trainer.py | 2 +- tests/data/modules/script_mode/code.tar.gz | Bin 37983 -> 37844 bytes 2 files changed, 1 insertion(+), 1 deletion(-) diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 4183fb87cd..96078d1aeb 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -865,7 +865,7 @@ def _prepare_train_script( working_dir = f"cd {SM_CODE_CONTAINER_PATH} \n" if source_code.source_dir.endswith(".tar.gz"): tarfile_name = os.path.basename(source_code.source_dir) - working_dir += f"tar --strip-components=1 -xzf {tarfile_name} \n" + working_dir += f"tar -xzf {tarfile_name} \n" if base_command: execute_driver = EXECUTE_BASE_COMMANDS.format(base_command=base_command) diff --git a/tests/data/modules/script_mode/code.tar.gz b/tests/data/modules/script_mode/code.tar.gz index 7c43f35f576640607e79a6f70ccaf84ce897feaa..e2ed9d4b184580bd8aebdc2a971747c1a1bea251 100644 GIT binary patch delta 36187 zcmV)JK)b)+r~=fd0)HQi2mtza9%ujq?7an8Rom7#PIv4ijV%@^(y8Da3Zi17*ntQe zK`99ZyF0MEyD+hJVq=4Xg&+-rA|+{jbM3`M&pPM4=e_U$p7Z^`_d3txvsi1*7<1%r zjJfu`7CwH_kx^kGK9PPALE%vr;jwc6_GV>eQSx!?ESo3fj?_n^i-`5({4 zeqkXNzTx4)Qh$r^h_ETrP~T8LshqrmTvkxbg=X13d;J?W`K$d|8|WL;OX}+{jj;Ut z{J>w@zqJ*|{vEBY9pxl3|2`7_y#0sUzpa%dBq}IG>T2z1XJ>8aY-8nY;Y6fkXJu<+ zuVL>f>D#+|w?S^bdJpYk5#t*b6=Cs5=IYwbt9LiMo`1o1Q8Cj32U$(fuyd9SCWHEp z_^$^2WaAqDxB2j&+W!9N|5x^JP3+&A8~?5Ct$xM-f17>@C*FSjYVjvY=KaXfQYb=#%IisNDF`8C|^lqUw86%-!LX%nM=H-p^;$` 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z5%LD|0PqBRKlYV69D3#_0zLs=us)1~_d;BM$K$U5_>rSDo(uC9_yy}iT>G?(8JSvB zA>Q59U&t7lQj0KcBv>BUMs{2cmy~D ze*k~rKitEyDLP@pZ+je=1?z06!QH>owCWYc?S|odA!4 z-@qTh2l#81X8p+}ubx0W;W_XV^cvzLjLYx5fO?QJ&f;|J-D2T;;4Rc;un+8l_uwDA z2ftt)@Mnp<=`7!OQW)Z%p!>5r$tz4a58`bcN*Vl`N#5GR6S?a ze;*d!G@Yg4$;vm@zN|Vyn=h*V@~v-Nd|7peZ@r-TMXOJ=I5$>DSp5Zyr!4$vcJi&K zEPZ)$V#Vr`-G##I_byFW>6hgr?v?wVJCF6Awl3>R+lTMIqK*^wePjKQ)O<CCvLpOjhDD~iOV-}^GecjkyL#C^uB*eSN~~TBvro}t5c1&UtAp&Rj(UcZ^f;X dtbP8||NmqE{{H>_`}@!R{tvJSyS)H30sw^1M5h1% From c87801e865744acbf69933fe9911d5969fdce4c3 Mon Sep 17 00:00:00 2001 From: David Tippett Date: Mon, 12 May 2025 17:36:34 -0400 Subject: [PATCH 085/164] fix: parameter mismatch in update_endpoint (#5135) --- src/sagemaker/model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/sagemaker/model.py b/src/sagemaker/model.py index b281d9f489..3bfac0c8da 100644 --- a/src/sagemaker/model.py +++ b/src/sagemaker/model.py @@ -1805,7 +1805,7 @@ def deploy( container_startup_health_check_timeout=container_startup_health_check_timeout, explainer_config_dict=explainer_config_dict, async_inference_config_dict=async_inference_config_dict, - serverless_inference_config=serverless_inference_config_dict, + serverless_inference_config_dict=serverless_inference_config_dict, routing_config=routing_config, inference_ami_version=inference_ami_version, ) From 23f490701a2c6b9888fc97a3a2998e76ef4bf64f Mon Sep 17 00:00:00 2001 From: Prateek M Desai Date: Mon, 12 May 2025 14:37:05 -0700 Subject: [PATCH 086/164] add AG v1.3 (#5171) Co-authored-by: Ubuntu --- src/sagemaker/image_uri_config/autogluon.json | 90 ++++++++++++++++++- 1 file changed, 88 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/autogluon.json b/src/sagemaker/image_uri_config/autogluon.json index f1edd9d287..8d2f169b31 100644 --- a/src/sagemaker/image_uri_config/autogluon.json +++ b/src/sagemaker/image_uri_config/autogluon.json @@ -13,7 +13,8 @@ "0.8": "0.8.2", "1.0": "1.0.0", "1.1": "1.1.1", - "1.2": "1.2.0" + "1.2": "1.2.0", + "1.3": "1.3.0" }, "versions": { "0.3.1": { @@ -605,6 +606,47 @@ "py_versions": [ "py311" ] + }, + "1.3.0": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ca-central-1": "763104351884", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "autogluon-training", + "processors": [ + "cpu", + "gpu" + ], + "py_versions": [ + "py311" + ] } } }, @@ -618,7 +660,8 @@ "0.8": "0.8.2", "1.0": "1.0.0", "1.1": "1.1.1", - "1.2": "1.2.0" + "1.2": "1.2.0", + "1.3": "1.3.0" }, "versions": { "0.3.1": { @@ -1243,6 +1286,49 @@ "py_versions": [ "py311" ] + }, + "1.3.0": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "autogluon-inference", + "processors": [ + "cpu", + "gpu" + ], + "py_versions": [ + "py311" + ] } } } From 6809486484cce7244cd023560c822f04500e7b09 Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Tue, 13 May 2025 10:50:32 -0700 Subject: [PATCH 087/164] Fix test_deploy_with_update_endpoint() (#5177) Co-authored-by: pintaoz --- tests/unit/sagemaker/model/test_deploy.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/unit/sagemaker/model/test_deploy.py b/tests/unit/sagemaker/model/test_deploy.py index 4167ca62c3..ef8b5e6af5 100644 --- a/tests/unit/sagemaker/model/test_deploy.py +++ b/tests/unit/sagemaker/model/test_deploy.py @@ -1090,7 +1090,7 @@ def test_deploy_with_update_endpoint(production_variant, name_from_base, sagemak container_startup_health_check_timeout=None, explainer_config_dict=None, async_inference_config_dict=None, - serverless_inference_config=None, + serverless_inference_config_dict=None, routing_config=None, inference_ami_version=None, ) @@ -1124,7 +1124,7 @@ def test_deploy_with_update_endpoint(production_variant, name_from_base, sagemak container_startup_health_check_timeout=None, explainer_config_dict=None, async_inference_config_dict=None, - serverless_inference_config=serverless_inference_config_dict, + serverless_inference_config_dict=serverless_inference_config_dict, routing_config=None, inference_ami_version=None, ) @@ -1164,7 +1164,7 @@ def test_deploy_with_update_endpoint(production_variant, name_from_base, sagemak container_startup_health_check_timeout=None, explainer_config_dict=None, async_inference_config_dict=async_inference_config_dict, - serverless_inference_config=None, + serverless_inference_config_dict=None, routing_config=None, inference_ami_version=None, ) From 0ae2457bd27121482c618125489d9c4dbe74e31f Mon Sep 17 00:00:00 2001 From: pagezyhf <165770107+pagezyhf@users.noreply.github.com> Date: Tue, 13 May 2025 19:56:29 +0200 Subject: [PATCH 088/164] huggingface-tei dlc image_uri (#5174) Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> --- .../image_uri_config/huggingface-tei-cpu.json | 50 ++++++++++++++++++- .../image_uri_config/huggingface-tei.json | 50 ++++++++++++++++++- 2 files changed, 98 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface-tei-cpu.json b/src/sagemaker/image_uri_config/huggingface-tei-cpu.json index 1e81df6de4..3af1ed5de6 100644 --- a/src/sagemaker/image_uri_config/huggingface-tei-cpu.json +++ b/src/sagemaker/image_uri_config/huggingface-tei-cpu.json @@ -6,7 +6,8 @@ "version_aliases": { "1.2": "1.2.3", "1.4": "1.4.0", - "1.6": "1.6.0" + "1.6": "1.6.0", + "1.7": "1.7.0" }, "versions": { "1.2.3": { @@ -149,6 +150,53 @@ "container_version": { "cpu": "ubuntu22.04" } + }, + "1.7.0":{ + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "510948584623", + "ap-east-1": "651117190479", + "ap-northeast-1": "354813040037", + "ap-northeast-2": "366743142698", + "ap-northeast-3": "867004704886", + "ap-south-1": "720646828776", + "ap-south-2": "628508329040", + "ap-southeast-1": "121021644041", + "ap-southeast-2": "783357654285", + "ap-southeast-3": "951798379941", + "ap-southeast-4": "106583098589", + "ca-central-1": "341280168497", + "ca-west-1": "190319476487", + "cn-north-1": "450853457545", + "cn-northwest-1": "451049120500", + "eu-central-1": "492215442770", + "eu-central-2": "680994064768", + "eu-north-1": "662702820516", + "eu-south-1": "978288397137", + "eu-south-2": "104374241257", + "eu-west-1": "141502667606", + "eu-west-2": "764974769150", + "eu-west-3": "659782779980", + "il-central-1": "898809789911", + "me-central-1": "272398656194", + "me-south-1": "801668240914", + "sa-east-1": "737474898029", + "us-east-1": "683313688378", + "us-east-2": "257758044811", + "us-gov-east-1": "237065988967", + "us-gov-west-1": "414596584902", + "us-iso-east-1": "833128469047", + "us-isob-east-1": "281123927165", + "us-west-1": "746614075791", + "us-west-2": "246618743249" + }, + "tag_prefix": "2.0.1-tei1.7.0", + "repository": "tei-cpu", + "container_version": { + "cpu": "ubuntu22.04" + } } } } diff --git a/src/sagemaker/image_uri_config/huggingface-tei.json b/src/sagemaker/image_uri_config/huggingface-tei.json index c2515daf12..eaf08230c7 100644 --- a/src/sagemaker/image_uri_config/huggingface-tei.json +++ b/src/sagemaker/image_uri_config/huggingface-tei.json @@ -6,7 +6,8 @@ "version_aliases": { "1.2": "1.2.3", "1.4": "1.4.0", - "1.6": "1.6.0" + "1.6": "1.6.0", + "1.7": "1.7.0" }, "versions": { "1.2.3": { @@ -149,6 +150,53 @@ "container_version": { "gpu": "cu122-ubuntu22.04" } + }, + "1.7.0": { + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "510948584623", + "ap-east-1": "651117190479", + "ap-northeast-1": "354813040037", + "ap-northeast-2": "366743142698", + "ap-northeast-3": "867004704886", + "ap-south-1": "720646828776", + "ap-south-2": "628508329040", + "ap-southeast-1": "121021644041", + "ap-southeast-2": "783357654285", + "ap-southeast-3": "951798379941", + "ap-southeast-4": "106583098589", + "ca-central-1": "341280168497", + "ca-west-1": "190319476487", + "cn-north-1": "450853457545", + "cn-northwest-1": "451049120500", + "eu-central-1": "492215442770", + "eu-central-2": "680994064768", + "eu-north-1": "662702820516", + "eu-south-1": "978288397137", + "eu-south-2": "104374241257", + "eu-west-1": "141502667606", + "eu-west-2": "764974769150", + "eu-west-3": "659782779980", + "il-central-1": "898809789911", + "me-central-1": "272398656194", + "me-south-1": "801668240914", + "sa-east-1": "737474898029", + "us-east-1": "683313688378", + "us-east-2": "257758044811", + "us-gov-east-1": "237065988967", + "us-gov-west-1": "414596584902", + "us-iso-east-1": "833128469047", + "us-isob-east-1": "281123927165", + "us-west-1": "746614075791", + "us-west-2": "246618743249" + }, + "tag_prefix": "2.0.1-tei1.7.0", + "repository": "tei", + "container_version": { + "gpu": "cu122-ubuntu22.04" + } } } } From e2ea4ffb81009601d37f727147feea3b4381829a Mon Sep 17 00:00:00 2001 From: pagezyhf <165770107+pagezyhf@users.noreply.github.com> Date: Tue, 13 May 2025 19:56:44 +0200 Subject: [PATCH 089/164] huggingface-neuronx dlc image_uri (#5172) * huggingface-neuronx dlc image_uri * huggingface-neuronx inference dlc --------- Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> --- .../image_uri_config/huggingface-neuronx.json | 136 +++++++++++++++++- 1 file changed, 134 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface-neuronx.json b/src/sagemaker/image_uri_config/huggingface-neuronx.json index a3426d5e0c..0ae1a5987d 100644 --- a/src/sagemaker/image_uri_config/huggingface-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-neuronx.json @@ -6,7 +6,9 @@ "version_aliases": { "4.28": "4.28.1", "4.34": "4.34.1", - "4.36": "4.36.2" + "4.36": "4.36.2", + "4.43": "4.43.2", + "4.48": "4.48.1" }, "versions": { "4.28.1": { @@ -137,6 +139,92 @@ "sdk2.18.0" ] } + }, + "4.43.2": { + "version_aliases": { + "pytorch2.1": "pytorch2.1.2" + }, + "pytorch2.1.2": { + "py_versions": [ + "py310" + ], + "repository": "huggingface-pytorch-inference-neuronx", + "registries": { + "ap-northeast-1": "763104351884", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "mx-central-1":"637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "container_version": { + "inf": "ubuntu20.04" + }, + "sdk_versions": [ + "sdk2.20.0" + ] + } + }, + "4.48.1": { + "version_aliases": { + "pytorch2.1": "pytorch2.1.2" + }, + "pytorch2.1.2": { + "py_versions": [ + "py310" + ], + "repository": "huggingface-pytorch-inference-neuronx", + "registries": { + "ap-northeast-1": "763104351884", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "mx-central-1":"637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "container_version": { + "inf": "ubuntu20.04" + }, + "sdk_versions": [ + "sdk2.20.0" + ] + } } } }, @@ -147,7 +235,8 @@ "version_aliases": { "4.28": "4.28.1", "4.34": "4.34.1", - "4.36": "4.36.2" + "4.36": "4.36.2", + "4.43": "4.43.2" }, "versions": { "4.28.1": { @@ -365,6 +454,49 @@ "sdk2.18.0" ] } + }, + "4.43.2": { + "version_aliases": { + "pytorch2.1": "pytorch2.1.2" + }, + "pytorch2.1.2": { + "py_versions": [ + "py310" + ], + "repository": "huggingface-pytorch-inference-neuronx", + "registries": { + "ap-northeast-1": "763104351884", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "mx-central-1":"637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "container_version": { + "inf": "ubuntu20.04" + }, + "sdk_versions": [ + "sdk2.20.0" + ] + } } } } From 84852dd2d73ae592a179ab5b038d4591700ef3cb Mon Sep 17 00:00:00 2001 From: pagezyhf <165770107+pagezyhf@users.noreply.github.com> Date: Tue, 13 May 2025 19:57:00 +0200 Subject: [PATCH 090/164] huggingface-llm-neuronx dlc (#5173) Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> --- .../huggingface-llm-neuronx.json | 55 ++++++++++++++++++- 1 file changed, 54 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index d79e7637ed..74647b107a 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -4,7 +4,7 @@ "inf2" ], "version_aliases": { - "0.0": "0.0.27" + "0.0": "0.0.28", }, "versions": { "0.0.16": { @@ -589,6 +589,59 @@ "container_version": { "inf2": "ubuntu22.04" } + }, + "0.0.28": { + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "tag_prefix": "2.1.2-optimum0.0.28", + "repository": "huggingface-pytorch-tgi-inference", + "container_version": { + "inf2": "ubuntu22.04" + } } } } From 7825dc928217be11e13ecb77d26e47f730e7726c Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Tue, 13 May 2025 13:55:47 -0700 Subject: [PATCH 091/164] Fix test_huggingface_tei_uris() (#5178) * Fix test_huggingface_tei_uris() * Fix json --------- Co-authored-by: pintaoz --- src/sagemaker/image_uri_config/huggingface-llm-neuronx.json | 2 +- tests/unit/sagemaker/image_uris/test_huggingface_llm.py | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index 74647b107a..9b7b18ee94 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -4,7 +4,7 @@ "inf2" ], "version_aliases": { - "0.0": "0.0.28", + "0.0": "0.0.28" }, "versions": { "0.0.16": { diff --git a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py index 6598117027..e693b9f8ce 100644 --- a/tests/unit/sagemaker/image_uris/test_huggingface_llm.py +++ b/tests/unit/sagemaker/image_uris/test_huggingface_llm.py @@ -24,11 +24,13 @@ "1.2.3": "2.0.1-tei1.2.3-gpu-py310-cu122-ubuntu22.04", "1.4.0": "2.0.1-tei1.4.0-gpu-py310-cu122-ubuntu22.04", "1.6.0": "2.0.1-tei1.6.0-gpu-py310-cu122-ubuntu22.04", + "1.7.0": "2.0.1-tei1.7.0-gpu-py310-cu122-ubuntu22.04", }, "cpu": { "1.2.3": "2.0.1-tei1.2.3-cpu-py310-ubuntu22.04", "1.4.0": "2.0.1-tei1.4.0-cpu-py310-ubuntu22.04", "1.6.0": "2.0.1-tei1.6.0-cpu-py310-ubuntu22.04", + "1.7.0": "2.0.1-tei1.7.0-cpu-py310-ubuntu22.04", }, } HF_VERSIONS_MAPPING = { From 3e419eed390caa021f2c4029f5434dc2be0384d6 Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Wed, 14 May 2025 10:55:00 -0700 Subject: [PATCH 092/164] Fix Flask-Limiter version (#5180) --- requirements/extras/test_requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 9277c55ecd..8bdd7c8ae3 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -16,7 +16,7 @@ stopit==1.1.2 # Update tox.ini to have correct version of airflow constraints file apache-airflow==2.10.4 apache-airflow-providers-amazon==7.2.1 -Flask-Limiter==3.12 +Flask-Limiter==3.11 attrs>=23.1.0,<24 fabric==3.2.2 requests==2.32.2 From d194050b2c7f896a903112e1b0917417bfbd58bd Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 15 May 2025 00:46:36 +0000 Subject: [PATCH 093/164] prepare release v2.244.1 --- CHANGELOG.md | 25 +++++++++++++++++++++++++ VERSION | 2 +- 2 files changed, 26 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index eb0278b42a..d86535c7b5 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,30 @@ # Changelog +## v2.244.1 (2025-05-15) + +### Bug Fixes and Other Changes + + * Fix Flask-Limiter version + * Fix test_huggingface_tei_uris() + * huggingface-llm-neuronx dlc + * huggingface-neuronx dlc image_uri + * huggingface-tei dlc image_uri + * Fix test_deploy_with_update_endpoint() + * add AG v1.3 + * parameter mismatch in update_endpoint + * remove --strip-component for untar source tar.gz + * Fix type annotations + * chore: Allow omegaconf >=2.2,<3 + * honor json serialization of HPs + * Map llama models to correct script + * pin test dependency + * fix bad initialization script error message + * Improve error logging and documentation for issue 4007 + * build(deps): bump scikit-learn + * build(deps): bump mlflow + * build(deps): bump mlflow in /tests/data/serve_resources/mlflow/pytorch + * chore: Add tei 1.6.0 image + ## v2.244.0 (2025-05-02) ### Features diff --git a/VERSION b/VERSION index d372855290..fd867561cb 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.1.dev0 +2.244.1 From 8adb660c7de763da28e6174bf9cc647a8dc758a3 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 15 May 2025 00:46:41 +0000 Subject: [PATCH 094/164] update development version to v2.244.2.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index fd867561cb..7c4fab2fd9 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.1 +2.244.2.dev0 From c849eae7a289afc954ca7731d6715066a2d2bf4d Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 14 May 2025 21:27:13 -0700 Subject: [PATCH 095/164] change: Improve defaults handling in ModelTrainer (#5170) * Improve default handling * format * add tests & update docs * fix docstyle * fix input_data_config * fix use input_data_config parameter in train as authoritative source * fix tests * format * update checkpoint config * docstyle * make config creation backwards compatible * format * fix condition * fix Compute and Networking config when attributes are None * format * fix * format --- pyproject.toml | 3 +- src/sagemaker/modules/configs.py | 80 +++++- src/sagemaker/modules/train/model_trainer.py | 262 ++++++++++++++---- .../modules/train/test_model_trainer.py | 48 +++- 4 files changed, 328 insertions(+), 65 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index c6508f54ad..17dfab3571 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,7 +55,8 @@ dependencies = [ "tblib>=1.7.0,<4", "tqdm", "urllib3>=1.26.8,<3.0.0", - "uvicorn" + "uvicorn", + "graphene>=3,<4" ] [project.scripts] diff --git a/src/sagemaker/modules/configs.py b/src/sagemaker/modules/configs.py index ac54e2ad0b..3739c73c5d 100644 --- a/src/sagemaker/modules/configs.py +++ b/src/sagemaker/modules/configs.py @@ -30,7 +30,6 @@ from sagemaker_core.shapes import ( StoppingCondition, RetryStrategy, - OutputDataConfig, Channel, ShuffleConfig, DataSource, @@ -43,8 +42,6 @@ RemoteDebugConfig, SessionChainingConfig, InstanceGroup, - TensorBoardOutputConfig, - CheckpointConfig, ) from sagemaker.modules.utils import convert_unassigned_to_none @@ -131,6 +128,8 @@ class Compute(shapes.ResourceConfig): subsequent training jobs. instance_groups (Optional[List[InstanceGroup]]): A list of instance groups for heterogeneous clusters to be used in the training job. + training_plan_arn (Optional[str]): + The Amazon Resource Name (ARN) of the training plan to use for this resource configuration. enable_managed_spot_training (Optional[bool]): To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning @@ -151,8 +150,12 @@ def _to_resource_config(self) -> shapes.ResourceConfig: compute_config_dict = self.model_dump() resource_config_fields = set(shapes.ResourceConfig.__annotations__.keys()) filtered_dict = { - k: v for k, v in compute_config_dict.items() if k in resource_config_fields + k: v + for k, v in compute_config_dict.items() + if k in resource_config_fields and v is not None } + if not filtered_dict: + return None return shapes.ResourceConfig(**filtered_dict) @@ -194,10 +197,12 @@ def _model_validator(self) -> "Networking": def _to_vpc_config(self) -> shapes.VpcConfig: """Convert to a sagemaker_core.shapes.VpcConfig object.""" compute_config_dict = self.model_dump() - resource_config_fields = set(shapes.VpcConfig.__annotations__.keys()) + vpc_config_fields = set(shapes.VpcConfig.__annotations__.keys()) filtered_dict = { - k: v for k, v in compute_config_dict.items() if k in resource_config_fields + k: v for k, v in compute_config_dict.items() if k in vpc_config_fields and v is not None } + if not filtered_dict: + return None return shapes.VpcConfig(**filtered_dict) @@ -224,3 +229,66 @@ class InputData(BaseConfig): channel_name: str = None data_source: Union[str, FileSystemDataSource, S3DataSource] = None + + +class OutputDataConfig(shapes.OutputDataConfig): + """OutputDataConfig. + + The OutputDataConfig class is a subclass of ``sagemaker_core.shapes.OutputDataConfig`` + and allows the user to specify the output data configuration for the training job. + + Parameters: + s3_output_path (Optional[str]): + The S3 URI where the output data will be stored. This is the location where the + training job will save its output data, such as model artifacts and logs. + kms_key_id (Optional[str]): + The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that + SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side + encryption. + compression_type (Optional[str]): + The model output compression type. Select `NONE` to output an uncompressed model, + recommended for large model outputs. Defaults to `GZIP`. + """ + + s3_output_path: Optional[str] = None + kms_key_id: Optional[str] = None + compression_type: Optional[str] = None + + +class TensorBoardOutputConfig(shapes.TensorBoardOutputConfig): + """TensorBoardOutputConfig. + + The TensorBoardOutputConfig class is a subclass of ``sagemaker_core.shapes.TensorBoardOutputConfig`` + and allows the user to specify the storage locations for the Amazon SageMaker + Debugger TensorBoard. + + Parameters: + s3_output_path (Optional[str]): + Path to Amazon S3 storage location for TensorBoard output. If not specified, will + default to + ``s3://////tensorboard-output`` + local_path (Optional[str]): + Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard. + """ + + s3_output_path: Optional[str] = None + local_path: Optional[str] = "/opt/ml/output/tensorboard" + + +class CheckpointConfig(shapes.CheckpointConfig): + """CheckpointConfig. + + The CheckpointConfig class is a subclass of ``sagemaker_core.shapes.CheckpointConfig`` + and allows the user to specify the checkpoint configuration for the training job. + + Parameters: + s3_uri (Optional[str]): + Path to Amazon S3 storage location for the Checkpoint data. If not specified, will + default to + ``s3://////checkpoints`` + local_path (Optional[str]): + The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints. + """ + + s3_uri: Optional[str] = None + local_path: Optional[str] = "/opt/ml/checkpoints" diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 96078d1aeb..58ae724074 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -25,6 +25,7 @@ from sagemaker_core.main import resources from sagemaker_core.resources import TrainingJob +from sagemaker_core import shapes from sagemaker_core.shapes import AlgorithmSpecification from pydantic import BaseModel, ConfigDict, PrivateAttr, validate_call @@ -48,11 +49,11 @@ from sagemaker.utils import resolve_value_from_config from sagemaker.modules import Session, get_execution_role +from sagemaker.modules import configs from sagemaker.modules.configs import ( Compute, StoppingCondition, RetryStrategy, - OutputDataConfig, SourceCode, TrainingImageConfig, Channel, @@ -64,8 +65,6 @@ InfraCheckConfig, RemoteDebugConfig, SessionChainingConfig, - TensorBoardOutputConfig, - CheckpointConfig, InputData, ) @@ -221,9 +220,9 @@ class ModelTrainer(BaseModel): training_image: Optional[str] = None training_image_config: Optional[TrainingImageConfig] = None algorithm_name: Optional[str] = None - output_data_config: Optional[OutputDataConfig] = None + output_data_config: Optional[shapes.OutputDataConfig] = None input_data_config: Optional[List[Union[Channel, InputData]]] = None - checkpoint_config: Optional[CheckpointConfig] = None + checkpoint_config: Optional[shapes.CheckpointConfig] = None training_input_mode: Optional[str] = "File" environment: Optional[Dict[str, str]] = {} hyperparameters: Optional[Union[Dict[str, Any], str]] = {} @@ -234,7 +233,7 @@ class ModelTrainer(BaseModel): _latest_training_job: Optional[resources.TrainingJob] = PrivateAttr(default=None) # Private TrainingJob Parameters - _tensorboard_output_config: Optional[TensorBoardOutputConfig] = PrivateAttr(default=None) + _tensorboard_output_config: Optional[shapes.TensorBoardOutputConfig] = PrivateAttr(default=None) _retry_strategy: Optional[RetryStrategy] = PrivateAttr(default=None) _infra_check_config: Optional[InfraCheckConfig] = PrivateAttr(default=None) _session_chaining_config: Optional[SessionChainingConfig] = PrivateAttr(default=None) @@ -265,8 +264,8 @@ class ModelTrainer(BaseModel): "networking": Networking, "stopping_condition": StoppingCondition, "training_image_config": TrainingImageConfig, - "output_data_config": OutputDataConfig, - "checkpoint_config": CheckpointConfig, + "output_data_config": configs.OutputDataConfig, + "checkpoint_config": configs.CheckpointConfig, } def _populate_intelligent_defaults(self): @@ -318,7 +317,7 @@ def _populate_intelligent_defaults_from_training_job_space(self): config_path=TRAINING_JOB_OUTPUT_DATA_CONFIG_PATH ) if default_output_data_config: - self.output_data_config = OutputDataConfig( + self.output_data_config = configs.OutputDataConfig( **self._convert_keys_to_snake(default_output_data_config) ) @@ -477,6 +476,20 @@ def model_post_init(self, __context: Any): ) logger.warning(f"Compute not provided. Using default:\n{self.compute}") + if self.compute.instance_type is None: + self.compute.instance_type = DEFAULT_INSTANCE_TYPE + logger.warning(f"Instance type not provided. Using default:\n{DEFAULT_INSTANCE_TYPE}") + if self.compute.instance_count is None: + self.compute.instance_count = 1 + logger.warning( + f"Instance count not provided. Using default:\n{self.compute.instance_count}" + ) + if self.compute.volume_size_in_gb is None: + self.compute.volume_size_in_gb = 30 + logger.warning( + f"Volume size not provided. Using default:\n{self.compute.volume_size_in_gb}" + ) + if self.stopping_condition is None: self.stopping_condition = StoppingCondition( max_runtime_in_seconds=3600, @@ -486,6 +499,12 @@ def model_post_init(self, __context: Any): logger.warning( f"StoppingCondition not provided. Using default:\n{self.stopping_condition}" ) + if self.stopping_condition.max_runtime_in_seconds is None: + self.stopping_condition.max_runtime_in_seconds = 3600 + logger.info( + "Max runtime not provided. Using default:\n" + f"{self.stopping_condition.max_runtime_in_seconds}" + ) if self.hyperparameters and isinstance(self.hyperparameters, str): if not os.path.exists(self.hyperparameters): @@ -510,24 +529,41 @@ def model_post_init(self, __context: Any): "Must be a valid JSON or YAML file." ) - if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB and self.output_data_config is None: - session = self.sagemaker_session - base_job_name = self.base_job_name - self.output_data_config = OutputDataConfig( - s3_output_path=f"s3://{self._fetch_bucket_name_and_prefix(session)}" - f"/{base_job_name}", - compression_type="GZIP", - kms_key_id=None, - ) - logger.warning( - f"OutputDataConfig not provided. Using default:\n{self.output_data_config}" - ) + if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB: + if self.output_data_config is None: + session = self.sagemaker_session + base_job_name = self.base_job_name + self.output_data_config = configs.OutputDataConfig( + s3_output_path=f"s3://{self._fetch_bucket_name_and_prefix(session)}" + f"/{base_job_name}", + compression_type="GZIP", + kms_key_id=None, + ) + logger.warning( + f"OutputDataConfig not provided. Using default:\n{self.output_data_config}" + ) + if self.output_data_config.s3_output_path is None: + session = self.sagemaker_session + base_job_name = self.base_job_name + self.output_data_config.s3_output_path = ( + f"s3://{self._fetch_bucket_name_and_prefix(session)}/{base_job_name}" + ) + logger.warning( + f"OutputDataConfig s3_output_path not provided. Using default:\n" + f"{self.output_data_config.s3_output_path}" + ) + if self.output_data_config.compression_type is None: + self.output_data_config.compression_type = "GZIP" + logger.warning( + f"OutputDataConfig compression type not provided. Using default:\n" + f"{self.output_data_config.compression_type}" + ) - # TODO: Autodetect which image to use if source_code is provided if self.training_image: logger.info(f"Training image URI: {self.training_image}") - def _fetch_bucket_name_and_prefix(self, session: Session) -> str: + @staticmethod + def _fetch_bucket_name_and_prefix(session: Session) -> str: """Helper function to get the bucket name with the corresponding prefix if applicable""" if session.default_bucket_prefix is not None: return f"{session.default_bucket()}/{session.default_bucket_prefix}" @@ -559,15 +595,25 @@ def train( self._populate_intelligent_defaults() current_training_job_name = _get_unique_name(self.base_job_name) input_data_key_prefix = f"{self.base_job_name}/{current_training_job_name}/input" - if input_data_config: - self.input_data_config = input_data_config - input_data_config = [] + self.input_data_config = input_data_config or self.input_data_config or [] + if self.input_data_config: - input_data_config = self._get_input_data_config( + self.input_data_config = self._get_input_data_config( self.input_data_config, input_data_key_prefix ) + if self.checkpoint_config and not self.checkpoint_config.s3_uri: + self.checkpoint_config.s3_uri = ( + f"s3://{self._fetch_bucket_name_and_prefix(self.sagemaker_session)}/" + f"{self.base_job_name}/{current_training_job_name}/checkpoints" + ) + if self._tensorboard_output_config and not self._tensorboard_output_config.s3_output_path: + self._tensorboard_output_config.s3_output_path = ( + f"s3://{self._fetch_bucket_name_and_prefix(self.sagemaker_session)}/" + f"{self.base_job_name}" + ) + string_hyper_parameters = {} if self.hyperparameters: for hyper_parameter, value in self.hyperparameters.items(): @@ -597,7 +643,7 @@ def train( data_source=self.source_code.source_dir, key_prefix=input_data_key_prefix, ) - input_data_config.append(source_code_channel) + self.input_data_config.append(source_code_channel) self._prepare_train_script( tmp_dir=tmp_dir, @@ -618,7 +664,7 @@ def train( data_source=tmp_dir.name, key_prefix=input_data_key_prefix, ) - input_data_config.append(sm_drivers_channel) + self.input_data_config.append(sm_drivers_channel) # If source_code is provided, we will always use # the default container entrypoint and arguments @@ -645,7 +691,7 @@ def train( training_job_name=current_training_job_name, algorithm_specification=algorithm_specification, hyper_parameters=string_hyper_parameters, - input_data_config=input_data_config, + input_data_config=self.input_data_config, resource_config=resource_config, vpc_config=vpc_config, # Public Instance Attributes @@ -690,7 +736,7 @@ def train( sagemaker_session=self.sagemaker_session, container_entrypoint=algorithm_specification.container_entrypoint, container_arguments=algorithm_specification.container_arguments, - input_data_config=input_data_config, + input_data_config=self.input_data_config, hyper_parameters=string_hyper_parameters, environment=self.environment, ) @@ -909,22 +955,55 @@ def from_recipe( requirements: Optional[str] = None, training_image: Optional[str] = None, training_image_config: Optional[TrainingImageConfig] = None, - output_data_config: Optional[OutputDataConfig] = None, + output_data_config: Optional[shapes.OutputDataConfig] = None, input_data_config: Optional[List[Union[Channel, InputData]]] = None, - checkpoint_config: Optional[CheckpointConfig] = None, + checkpoint_config: Optional[shapes.CheckpointConfig] = None, training_input_mode: Optional[str] = "File", environment: Optional[Dict[str, str]] = None, tags: Optional[List[Tag]] = None, sagemaker_session: Optional[Session] = None, role: Optional[str] = None, base_job_name: Optional[str] = None, - ) -> "ModelTrainer": + ) -> "ModelTrainer": # noqa: D412 """Create a ModelTrainer from a training recipe. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + from sagemaker.modules.configs import Compute + + recipe_overrides = { + "run": { + "results_dir": "/opt/ml/model", + }, + "model": { + "data": { + "use_synthetic_data": True + } + } + } + + compute = Compute( + instance_type="ml.p5.48xlarge", + keep_alive_period_in_seconds=3600 + ) + + model_trainer = ModelTrainer.from_recipe( + training_recipe="fine-tuning/deepseek/hf_deepseek_r1_distilled_llama_8b_seq8k_gpu_fine_tuning", + recipe_overrides=recipe_overrides, + compute=compute, + ) + + model_trainer.train(wait=False) + + Args: training_recipe (str): The training recipe to use for training the model. This must be the name of a sagemaker training recipe or a path to a local training recipe .yaml file. + For available training recipes, see: https://github.com/aws/sagemaker-hyperpod-recipes/ compute (Compute): The compute configuration. This is used to specify the compute resources for the training job. If not specified, will default to 1 instance of ml.m5.xlarge. @@ -1032,55 +1111,140 @@ def from_recipe( return model_trainer def with_tensorboard_output_config( - self, tensorboard_output_config: TensorBoardOutputConfig - ) -> "ModelTrainer": + self, tensorboard_output_config: Optional[shapes.TensorBoardOutputConfig] = None + ) -> "ModelTrainer": # noqa: D412 """Set the TensorBoard output configuration. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + + model_trainer = ModelTrainer( + ... + ).with_tensorboard_output_config() + Args: tensorboard_output_config (sagemaker.modules.configs.TensorBoardOutputConfig): The TensorBoard output configuration. """ - self._tensorboard_output_config = tensorboard_output_config + self._tensorboard_output_config = ( + tensorboard_output_config or configs.TensorBoardOutputConfig() + ) return self - def with_retry_strategy(self, retry_strategy: RetryStrategy) -> "ModelTrainer": + def with_retry_strategy(self, retry_strategy: RetryStrategy) -> "ModelTrainer": # noqa: D412 """Set the retry strategy for the training job. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + from sagemaker.modules.configs import RetryStrategy + + retry_strategy = RetryStrategy(maximum_retry_attempts=3) + + model_trainer = ModelTrainer( + ... + ).with_retry_strategy(retry_strategy) + Args: - retry_strategy (RetryStrategy): + retry_strategy (sagemaker.modules.configs.RetryStrategy): The retry strategy for the training job. """ self._retry_strategy = retry_strategy return self - def with_infra_check_config(self, infra_check_config: InfraCheckConfig) -> "ModelTrainer": + def with_infra_check_config( + self, infra_check_config: Optional[InfraCheckConfig] = None + ) -> "ModelTrainer": # noqa: D412 """Set the infra check configuration for the training job. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + + model_trainer = ModelTrainer( + ... + ).with_infra_check_config() + Args: - infra_check_config (InfraCheckConfig): + infra_check_config (sagemaker.modules.configs.InfraCheckConfig): The infra check configuration for the training job. """ - self._infra_check_config = infra_check_config + self._infra_check_config = infra_check_config or InfraCheckConfig(enable_infra_check=True) return self def with_session_chaining_config( - self, session_chaining_config: SessionChainingConfig - ) -> "ModelTrainer": + self, session_chaining_config: Optional[SessionChainingConfig] = None + ) -> "ModelTrainer": # noqa: D412 """Set the session chaining configuration for the training job. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + + model_trainer = ModelTrainer( + ... + ).with_session_chaining_config() + Args: - session_chaining_config (SessionChainingConfig): + session_chaining_config (sagemaker.modules.configs.SessionChainingConfig): The session chaining configuration for the training job. """ - self._session_chaining_config = session_chaining_config + self._session_chaining_config = session_chaining_config or SessionChainingConfig( + enable_session_tag_chaining=True + ) return self - def with_remote_debug_config(self, remote_debug_config: RemoteDebugConfig) -> "ModelTrainer": + def with_remote_debug_config( + self, remote_debug_config: Optional[RemoteDebugConfig] = None + ) -> "ModelTrainer": # noqa: D412 """Set the remote debug configuration for the training job. + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + + model_trainer = ModelTrainer( + ... + ).with_remote_debug_config() + Args: - remote_debug_config (RemoteDebugConfig): + remote_debug_config (sagemaker.modules.configs.RemoteDebugConfig): The remote debug configuration for the training job. """ - self._remote_debug_config = remote_debug_config + self._remote_debug_config = remote_debug_config or RemoteDebugConfig( + enable_remote_debug=True + ) + return self + + def with_checkpoint_config( + self, checkpoint_config: Optional[shapes.CheckpointConfig] = None + ) -> "ModelTrainer": # noqa: D412 + """Set the checkpoint configuration for the training job. + + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + + model_trainer = ModelTrainer( + ... + ).with_checkpoint_config() + + Args: + checkpoint_config (sagemaker.modules.configs.CheckpointConfig): + The checkpoint configuration for the training job. + """ + self.checkpoint_config = checkpoint_config or configs.CheckpointConfig() return self diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 6001c5db36..b1348b5ac9 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -324,13 +324,7 @@ def test_train_with_intelligent_defaults_training_job_space( hyper_parameters={}, input_data_config=[], resource_config=ResourceConfig( - volume_size_in_gb=30, - instance_type="ml.m5.xlarge", - instance_count=1, - volume_kms_key_id=None, - keep_alive_period_in_seconds=None, - instance_groups=None, - training_plan_arn=None, + volume_size_in_gb=30, instance_type="ml.m5.xlarge", instance_count=1 ), vpc_config=None, session=ANY, @@ -870,8 +864,6 @@ def mock_upload_data(path, bucket, key_prefix): volume_size_in_gb=compute.volume_size_in_gb, volume_kms_key_id=compute.volume_kms_key_id, keep_alive_period_in_seconds=compute.keep_alive_period_in_seconds, - instance_groups=None, - training_plan_arn=None, ), vpc_config=VpcConfig( security_group_ids=networking.security_group_ids, @@ -1228,3 +1220,41 @@ def test_hyperparameters_invalid(mock_exists, modules_session): compute=DEFAULT_COMPUTE_CONFIG, hyperparameters="hyperparameters.yaml", ) + + +@patch("sagemaker.modules.train.model_trainer._get_unique_name") +@patch("sagemaker.modules.train.model_trainer.TrainingJob") +def test_model_trainer_default_paths(mock_training_job, mock_unique_name, modules_session): + def mock_upload_data(path, bucket, key_prefix): + return f"s3://{bucket}/{key_prefix}" + + unique_name = "base-job-0123456789" + base_name = "base-job" + + modules_session.upload_data.side_effect = mock_upload_data + mock_unique_name.return_value = unique_name + + model_trainer = ( + ModelTrainer( + training_image=DEFAULT_IMAGE, + sagemaker_session=modules_session, + base_job_name=base_name, + ) + .with_tensorboard_output_config() + .with_checkpoint_config() + ) + + model_trainer.train() + + _, kwargs = mock_training_job.create.call_args + + default_base_path = f"s3://{DEFAULT_BUCKET}/{DEFAULT_BUCKET_PREFIX}/{base_name}" + + assert kwargs["output_data_config"].s3_output_path == default_base_path + assert kwargs["output_data_config"].compression_type == "GZIP" + + assert kwargs["checkpoint_config"].s3_uri == f"{default_base_path}/{unique_name}/checkpoints" + assert kwargs["checkpoint_config"].local_path == "/opt/ml/checkpoints" + + assert kwargs["tensor_board_output_config"].s3_output_path == default_base_path + assert kwargs["tensor_board_output_config"].local_path == "/opt/ml/output/tensorboard" From 681d21172801a65d78d65e5665a1a1c2ae180842 Mon Sep 17 00:00:00 2001 From: IshaChid76 <49986634+IshaChid76@users.noreply.github.com> Date: Thu, 15 May 2025 00:27:27 -0400 Subject: [PATCH 096/164] change: Add image configs and region config for TPE (ap-east-2) (#5167) * add image configs and region config for TPE (ap-east-2) * remove TPE from djl-neuronx --------- Co-authored-by: isha chidrawar Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> --- src/sagemaker/image_uri_config/huggingface-neuron.json | 1 + src/sagemaker/image_uri_config/huggingface-neuronx.json | 7 +++++++ .../image_uri_config/huggingface-training-compiler.json | 3 +++ src/sagemaker/jumpstart/region_config.json | 4 ++++ 4 files changed, 15 insertions(+) diff --git a/src/sagemaker/image_uri_config/huggingface-neuron.json b/src/sagemaker/image_uri_config/huggingface-neuron.json index 4e950bdb70..2a68282327 100644 --- a/src/sagemaker/image_uri_config/huggingface-neuron.json +++ b/src/sagemaker/image_uri_config/huggingface-neuron.json @@ -17,6 +17,7 @@ ], "repository": "huggingface-pytorch-inference-neuron", "registries": { + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-south-1": "763104351884", "ap-south-2": "772153158452", diff --git a/src/sagemaker/image_uri_config/huggingface-neuronx.json b/src/sagemaker/image_uri_config/huggingface-neuronx.json index 0ae1a5987d..d39d58bb9e 100644 --- a/src/sagemaker/image_uri_config/huggingface-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-neuronx.json @@ -21,6 +21,7 @@ ], "repository": "huggingface-pytorch-training-neuronx", "registries": { + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-south-1": "763104351884", "ap-south-2": "772153158452", @@ -64,6 +65,7 @@ ], "repository": "huggingface-pytorch-inference-neuronx", "registries": { + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-south-1": "763104351884", "ap-south-2": "772153158452", @@ -107,6 +109,7 @@ ], "repository": "huggingface-pytorch-inference-neuronx", "registries": { + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-south-1": "763104351884", "ap-south-2": "772153158452", @@ -252,6 +255,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -307,6 +311,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -363,6 +368,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -413,6 +419,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", diff --git a/src/sagemaker/image_uri_config/huggingface-training-compiler.json b/src/sagemaker/image_uri_config/huggingface-training-compiler.json index fa3a4119ca..c84469acc2 100644 --- a/src/sagemaker/image_uri_config/huggingface-training-compiler.json +++ b/src/sagemaker/image_uri_config/huggingface-training-compiler.json @@ -60,6 +60,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -103,6 +104,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", @@ -151,6 +153,7 @@ "af-south-1": "626614931356", "il-central-1": "780543022126", "ap-east-1": "871362719292", + "ap-east-2": "975050140332", "ap-northeast-1": "763104351884", "ap-northeast-2": "763104351884", "ap-northeast-3": "364406365360", diff --git a/src/sagemaker/jumpstart/region_config.json b/src/sagemaker/jumpstart/region_config.json index 30bea6ee70..136bf8256c 100644 --- a/src/sagemaker/jumpstart/region_config.json +++ b/src/sagemaker/jumpstart/region_config.json @@ -7,6 +7,10 @@ "content_bucket": "jumpstart-cache-prod-ap-east-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-1" }, + "ap-east-2": { + "content_bucket": "jumpstart-cache-prod-ap-east-2", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-2" + }, "ap-northeast-1": { "content_bucket": "jumpstart-cache-prod-ap-northeast-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-1", From 3ed4c63fd162f605260de1b92635218b98077da4 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Wed, 14 May 2025 14:18:16 +0000 Subject: [PATCH 097/164] change: update image_uri_configs 05-14-2025 07:18:16 PST --- .../huggingface-llm-neuronx.json | 55 +------------------ 1 file changed, 1 insertion(+), 54 deletions(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index 9b7b18ee94..d79e7637ed 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -4,7 +4,7 @@ "inf2" ], "version_aliases": { - "0.0": "0.0.28" + "0.0": "0.0.27" }, "versions": { "0.0.16": { @@ -589,59 +589,6 @@ "container_version": { "inf2": "ubuntu22.04" } - }, - "0.0.28": { - "py_versions": [ - "py310" - ], - "registries": { - "af-south-1": "626614931356", - "ap-east-1": "871362719292", - "ap-east-2": "975050140332", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-south-2": "772153158452", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ap-southeast-4": "457447274322", - "ap-southeast-5": "550225433462", - "ap-southeast-7": "590183813437", - "ca-central-1": "763104351884", - "ca-west-1": "204538143572", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-central-2": "380420809688", - "eu-north-1": "763104351884", - "eu-south-1": "692866216735", - "eu-south-2": "503227376785", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "il-central-1": "780543022126", - "me-central-1": "914824155844", - "me-south-1": "217643126080", - "mx-central-1": "637423239942", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-gov-east-1": "446045086412", - "us-gov-west-1": "442386744353", - "us-iso-east-1": "886529160074", - "us-isob-east-1": "094389454867", - "us-isof-east-1": "303241398832", - "us-isof-south-1": "454834333376", - "us-west-1": "763104351884", - "us-west-2": "763104351884" - }, - "tag_prefix": "2.1.2-optimum0.0.28", - "repository": "huggingface-pytorch-tgi-inference", - "container_version": { - "inf2": "ubuntu22.04" - } } } } From f967ca9a4767d6a8cb9679c279bbf776f2b6bbd5 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Thu, 15 May 2025 14:18:15 +0000 Subject: [PATCH 098/164] change: update jumpstart region_config 05-15-2025 07:18:15 PST --- src/sagemaker/jumpstart/region_config.json | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/sagemaker/jumpstart/region_config.json b/src/sagemaker/jumpstart/region_config.json index 136bf8256c..30bea6ee70 100644 --- a/src/sagemaker/jumpstart/region_config.json +++ b/src/sagemaker/jumpstart/region_config.json @@ -7,10 +7,6 @@ "content_bucket": "jumpstart-cache-prod-ap-east-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-1" }, - "ap-east-2": { - "content_bucket": "jumpstart-cache-prod-ap-east-2", - "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-2" - }, "ap-northeast-1": { "content_bucket": "jumpstart-cache-prod-ap-northeast-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-1", From ddc54d2a6181a1f2fdaf20f06dd81b02680c9092 Mon Sep 17 00:00:00 2001 From: zicanl-amazon <115581573+zicanl-amazon@users.noreply.github.com> Date: Thu, 15 May 2025 10:26:09 -0700 Subject: [PATCH 099/164] fix: clarify model monitor one time schedule bug (#5169) --- .../model_monitor/clarify_model_monitoring.py | 2 + .../monitor/test_clarify_model_monitor.py | 61 +++++++++++++++++++ 2 files changed, 63 insertions(+) diff --git a/src/sagemaker/model_monitor/clarify_model_monitoring.py b/src/sagemaker/model_monitor/clarify_model_monitoring.py index 2d9a4a69e4..9dc915a2d7 100644 --- a/src/sagemaker/model_monitor/clarify_model_monitoring.py +++ b/src/sagemaker/model_monitor/clarify_model_monitoring.py @@ -1103,6 +1103,8 @@ def create_monitoring_schedule( monitor_schedule_name=monitor_schedule_name, job_definition_name=new_job_definition_name, schedule_cron_expression=schedule_cron_expression, + data_analysis_start_time=data_analysis_start_time, + data_analysis_end_time=data_analysis_end_time, ) self.job_definition_name = new_job_definition_name self.monitoring_schedule_name = monitor_schedule_name diff --git a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py index 026e1a2d54..bdbba955a4 100644 --- a/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py +++ b/tests/unit/sagemaker/monitor/test_clarify_model_monitor.py @@ -89,6 +89,7 @@ subnets=SUBNETS, ) CRON_HOURLY = CronExpressionGenerator.hourly() +CRON_NOW = CronExpressionGenerator.now() ENDPOINT_NAME = "endpoint" GROUND_TRUTH_S3_URI = "s3://bucket/monitoring_captured/actuals" ANALYSIS_CONFIG_S3_URI = "s3://bucket/analysis_config.json" @@ -1305,6 +1306,66 @@ def test_model_explainability_monitor(model_explainability_monitor, sagemaker_se ) +def test_model_explainability_create_one_time_schedule( + model_explainability_monitor, sagemaker_session +): + endpoint_input = EndpointInput( + endpoint_name=ENDPOINT_NAME, + destination=ENDPOINT_INPUT_LOCAL_PATH, + features_attribute=FEATURES_ATTRIBUTE, + inference_attribute=str(INFERENCE_ATTRIBUTE), + ) + + # Create one-time schedule + with patch( + "sagemaker.s3.S3Uploader.upload_string_as_file_body", return_value=ANALYSIS_CONFIG_S3_URI + ) as _: + model_explainability_monitor.create_monitoring_schedule( + endpoint_input=endpoint_input, + analysis_config=ANALYSIS_CONFIG_S3_URI, + output_s3_uri=OUTPUT_S3_URI, + monitor_schedule_name=SCHEDULE_NAME, + schedule_cron_expression=CRON_NOW, + data_analysis_start_time=START_TIME_OFFSET, + data_analysis_end_time=END_TIME_OFFSET, + ) + + # Validate job definition creation + sagemaker_session.sagemaker_client.create_model_explainability_job_definition.assert_called_once() + job_definition_args = ( + sagemaker_session.sagemaker_client.create_model_explainability_job_definition.call_args[1] + ) + assert ( + job_definition_args["JobDefinitionName"] == model_explainability_monitor.job_definition_name + ) + assert job_definition_args == { + "JobDefinitionName": model_explainability_monitor.job_definition_name, + **EXPLAINABILITY_JOB_DEFINITION, + "Tags": TAGS, + } + + # Validate monitoring schedule creation + sagemaker_session.sagemaker_client.create_monitoring_schedule.assert_called_once() + schedule_args = sagemaker_session.sagemaker_client.create_monitoring_schedule.call_args[1] + assert schedule_args == { + "MonitoringScheduleName": SCHEDULE_NAME, + "MonitoringScheduleConfig": { + "MonitoringJobDefinitionName": model_explainability_monitor.job_definition_name, + "MonitoringType": "ModelExplainability", + "ScheduleConfig": { + "ScheduleExpression": CRON_NOW, + "DataAnalysisStartTime": START_TIME_OFFSET, + "DataAnalysisEndTime": END_TIME_OFFSET, + }, + }, + "Tags": TAGS, + } + + # Check if the monitoring schedule is stored in the monitor object + assert model_explainability_monitor.monitoring_schedule_name == SCHEDULE_NAME + assert model_explainability_monitor.job_definition_name is not None + + def test_model_explainability_batch_transform_monitor( model_explainability_monitor, sagemaker_session ): From 7f5ad9dd63ba5fe86968f56893df51a61a1dbd5a Mon Sep 17 00:00:00 2001 From: evakravi <69981223+evakravi@users.noreply.github.com> Date: Fri, 16 May 2025 19:51:29 -0400 Subject: [PATCH 100/164] fix: include model channel for gated uncompressed models (#5181) --- src/sagemaker/jumpstart/cache.py | 16 +- src/sagemaker/jumpstart/factory/estimator.py | 8 +- src/sagemaker/jumpstart/types.py | 16 +- .../sagemaker/jumpstart/factory/__init__.py | 0 .../jumpstart/factory/test_estimator.py | 162 ++++++++++++++++++ tests/unit/sagemaker/jumpstart/test_cache.py | 75 ++++++++ tests/unit/sagemaker/jumpstart/test_types.py | 71 +++++++- 7 files changed, 328 insertions(+), 20 deletions(-) create mode 100644 tests/unit/sagemaker/jumpstart/factory/__init__.py create mode 100644 tests/unit/sagemaker/jumpstart/factory/test_estimator.py diff --git a/src/sagemaker/jumpstart/cache.py b/src/sagemaker/jumpstart/cache.py index 29a903e00b..5a4be3f53f 100644 --- a/src/sagemaker/jumpstart/cache.py +++ b/src/sagemaker/jumpstart/cache.py @@ -372,10 +372,18 @@ def _get_json_file( object and None when reading from the local file system. """ if self._is_local_metadata_mode(): - file_content, etag = self._get_json_file_from_local_override(key, filetype), None - else: - file_content, etag = self._get_json_file_and_etag_from_s3(key) - return file_content, etag + if filetype in { + JumpStartS3FileType.OPEN_WEIGHT_MANIFEST, + JumpStartS3FileType.OPEN_WEIGHT_SPECS, + }: + return self._get_json_file_from_local_override(key, filetype), None + else: + JUMPSTART_LOGGER.warning( + "Local metadata mode is enabled, but the file type %s is not supported " + "for local override. Falling back to s3.", + filetype, + ) + return self._get_json_file_and_etag_from_s3(key) def _get_json_md5_hash(self, key: str): """Retrieves md5 object hash for s3 objects, using `s3.head_object`. diff --git a/src/sagemaker/jumpstart/factory/estimator.py b/src/sagemaker/jumpstart/factory/estimator.py index 12eb30daaf..051cda0f4a 100644 --- a/src/sagemaker/jumpstart/factory/estimator.py +++ b/src/sagemaker/jumpstart/factory/estimator.py @@ -54,9 +54,9 @@ from sagemaker.jumpstart.constants import ( JUMPSTART_DEFAULT_REGION_NAME, JUMPSTART_LOGGER, + JUMPSTART_MODEL_HUB_NAME, TRAINING_ENTRY_POINT_SCRIPT_NAME, SAGEMAKER_GATED_MODEL_S3_URI_TRAINING_ENV_VAR_KEY, - JUMPSTART_MODEL_HUB_NAME, ) from sagemaker.jumpstart.enums import JumpStartScriptScope, JumpStartModelType from sagemaker.jumpstart.factory import model @@ -634,10 +634,10 @@ def _add_model_uri_to_kwargs(kwargs: JumpStartEstimatorInitKwargs) -> JumpStartE """Sets model uri in kwargs based on default or override, returns full kwargs.""" # hub_arn is by default None unless the user specifies the hub_name # If no hub_name is specified, it is assumed the public hub + # Training platform enforces that private hub models must use model channel is_private_hub = JUMPSTART_MODEL_HUB_NAME not in kwargs.hub_arn if kwargs.hub_arn else False - if ( - _model_supports_training_model_uri(**get_model_info_default_kwargs(kwargs)) - or is_private_hub + if is_private_hub or _model_supports_training_model_uri( + **get_model_info_default_kwargs(kwargs) ): default_model_uri = model_uris.retrieve( model_scope=JumpStartScriptScope.TRAINING, diff --git a/src/sagemaker/jumpstart/types.py b/src/sagemaker/jumpstart/types.py index 0cd4bcc902..5b45b21bd8 100644 --- a/src/sagemaker/jumpstart/types.py +++ b/src/sagemaker/jumpstart/types.py @@ -1940,12 +1940,20 @@ def use_inference_script_uri(self) -> bool: def use_training_model_artifact(self) -> bool: """Returns True if the model should use a model uri when kicking off training job.""" - # gated model never use training model artifact - if self.gated_bucket: + # old models with this environment variable present don't use model channel + if any( + self.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value( + instance_type + ) + for instance_type in self.supported_training_instance_types + ): + return False + + # even older models with training model package artifact uris present also don't use model channel + if len(self.training_model_package_artifact_uris or {}) > 0: return False - # otherwise, return true is a training model package is not set - return len(self.training_model_package_artifact_uris or {}) == 0 + return getattr(self, "training_artifact_key", None) is not None def is_gated_model(self) -> bool: """Returns True if the model has a EULA key or the model bucket is gated.""" diff --git a/tests/unit/sagemaker/jumpstart/factory/__init__.py b/tests/unit/sagemaker/jumpstart/factory/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/unit/sagemaker/jumpstart/factory/test_estimator.py b/tests/unit/sagemaker/jumpstart/factory/test_estimator.py new file mode 100644 index 0000000000..fd59961f09 --- /dev/null +++ b/tests/unit/sagemaker/jumpstart/factory/test_estimator.py @@ -0,0 +1,162 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import +import pytest +from unittest.mock import patch +from sagemaker.jumpstart.constants import JUMPSTART_MODEL_HUB_NAME +from sagemaker.jumpstart.factory.estimator import ( + _add_model_uri_to_kwargs, + get_model_info_default_kwargs, +) +from sagemaker.jumpstart.types import JumpStartEstimatorInitKwargs +from sagemaker.jumpstart.enums import JumpStartScriptScope + + +class TestAddModelUriToKwargs: + @pytest.fixture + def mock_kwargs(self): + return JumpStartEstimatorInitKwargs( + model_id="test-model", + model_version="1.0.0", + instance_type="ml.m5.large", + model_uri=None, + ) + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=True, + ) + @patch("sagemaker.jumpstart.factory.estimator.model_uris.retrieve") + def test_add_model_uri_to_kwargs_default_uri( + self, mock_retrieve, mock_supports_training, mock_kwargs + ): + """Test adding default model URI when none is provided.""" + default_uri = "s3://jumpstart-models/training/test-model/1.0.0" + mock_retrieve.return_value = default_uri + + result = _add_model_uri_to_kwargs(mock_kwargs) + + mock_supports_training.assert_called_once() + mock_retrieve.assert_called_once_with( + model_scope=JumpStartScriptScope.TRAINING, + instance_type=mock_kwargs.instance_type, + **get_model_info_default_kwargs(mock_kwargs), + ) + assert result.model_uri == default_uri + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=True, + ) + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_incremental_training", + return_value=True, + ) + @patch("sagemaker.jumpstart.factory.estimator.model_uris.retrieve") + def test_add_model_uri_to_kwargs_custom_uri_with_incremental( + self, mock_retrieve, mock_supports_incremental, mock_supports_training, mock_kwargs + ): + """Test using custom model URI with incremental training support.""" + default_uri = "s3://jumpstart-models/training/test-model/1.0.0" + custom_uri = "s3://custom-bucket/my-model" + mock_retrieve.return_value = default_uri + mock_kwargs.model_uri = custom_uri + + result = _add_model_uri_to_kwargs(mock_kwargs) + + mock_supports_training.assert_called_once() + mock_supports_incremental.assert_called_once() + assert result.model_uri == custom_uri + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=True, + ) + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_incremental_training", + return_value=False, + ) + @patch("sagemaker.jumpstart.factory.estimator.model_uris.retrieve") + @patch("sagemaker.jumpstart.factory.estimator.JUMPSTART_LOGGER.warning") + def test_add_model_uri_to_kwargs_custom_uri_without_incremental( + self, + mock_warning, + mock_retrieve, + mock_supports_incremental, + mock_supports_training, + mock_kwargs, + ): + """Test using custom model URI without incremental training support logs warning.""" + default_uri = "s3://jumpstart-models/training/test-model/1.0.0" + custom_uri = "s3://custom-bucket/my-model" + mock_retrieve.return_value = default_uri + mock_kwargs.model_uri = custom_uri + + result = _add_model_uri_to_kwargs(mock_kwargs) + + mock_supports_training.assert_called_once() + mock_supports_incremental.assert_called_once() + mock_warning.assert_called_once() + assert "does not support incremental training" in mock_warning.call_args[0][0] + assert result.model_uri == custom_uri + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=False, + ) + def test_add_model_uri_to_kwargs_no_training_support(self, mock_supports_training, mock_kwargs): + """Test when model doesn't support training model URI.""" + result = _add_model_uri_to_kwargs(mock_kwargs) + + mock_supports_training.assert_called_once() + assert result.model_uri is None + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=False, + ) + @patch("sagemaker.jumpstart.factory.estimator.model_uris.retrieve") + def test_add_model_uri_to_kwargs_private_hub( + self, mock_retrieve, mock_supports_training, mock_kwargs + ): + """Test when model is from a private hub.""" + default_uri = "s3://jumpstart-models/training/test-model/1.0.0" + mock_retrieve.return_value = default_uri + mock_kwargs.hub_arn = "arn:aws:sagemaker:us-west-2:123456789012:hub/private-hub" + + result = _add_model_uri_to_kwargs(mock_kwargs) + + # Should not check if model supports training model URI for private hub + mock_supports_training.assert_not_called() + mock_retrieve.assert_called_once() + assert result.model_uri == default_uri + + @patch( + "sagemaker.jumpstart.factory.estimator._model_supports_training_model_uri", + return_value=False, + ) + @patch("sagemaker.jumpstart.factory.estimator.model_uris.retrieve") + def test_add_model_uri_to_kwargs_public_hub( + self, mock_retrieve, mock_supports_training, mock_kwargs + ): + """Test when model is from the public hub.""" + mock_kwargs.hub_arn = ( + f"arn:aws:sagemaker:us-west-2:123456789012:hub/{JUMPSTART_MODEL_HUB_NAME}" + ) + + result = _add_model_uri_to_kwargs(mock_kwargs) + + # Should check if model supports training model URI for public hub + mock_supports_training.assert_called_once() + mock_retrieve.assert_not_called() + assert result.model_uri is None diff --git a/tests/unit/sagemaker/jumpstart/test_cache.py b/tests/unit/sagemaker/jumpstart/test_cache.py index 17996f4f15..a652a11f4e 100644 --- a/tests/unit/sagemaker/jumpstart/test_cache.py +++ b/tests/unit/sagemaker/jumpstart/test_cache.py @@ -1288,3 +1288,78 @@ def test_jumpstart_cache_handles_versioning_correctly_non_sem_ver(retrieval_func assert_key = JumpStartVersionedModelId("test-model", "abc") assert result == assert_key + + +@patch("sagemaker.jumpstart.utils.get_region_fallback", lambda *args, **kwargs: "dummy-region") +@patch( + "sagemaker.jumpstart.utils.get_jumpstart_content_bucket", lambda *args, **kwargs: "dummy-bucket" +) +def test_get_json_file_from_s3(): + """Test _get_json_file retrieves from S3 in normal mode.""" + cache = JumpStartModelsCache() + test_key = "test/file/path.json" + test_json_data = {"key": "value"} + test_etag = "test-etag-123" + + with patch.object( + JumpStartModelsCache, + "_get_json_file_and_etag_from_s3", + return_value=(test_json_data, test_etag), + ) as mock_s3_get: + result, etag = cache._get_json_file(test_key, JumpStartS3FileType.OPEN_WEIGHT_MANIFEST) + + mock_s3_get.assert_called_once_with(test_key) + assert result == test_json_data + assert etag == test_etag + + +@patch("sagemaker.jumpstart.utils.get_region_fallback", lambda *args, **kwargs: "dummy-region") +@patch( + "sagemaker.jumpstart.utils.get_jumpstart_content_bucket", lambda *args, **kwargs: "dummy-bucket" +) +def test_get_json_file_from_local_supported_type(): + """Test _get_json_file retrieves from local override for supported file types.""" + cache = JumpStartModelsCache() + test_key = "test/file/path.json" + test_json_data = {"key": "value"} + + with ( + patch.object(JumpStartModelsCache, "_is_local_metadata_mode", return_value=True), + patch.object( + JumpStartModelsCache, "_get_json_file_from_local_override", return_value=test_json_data + ) as mock_local_get, + ): + result, etag = cache._get_json_file(test_key, JumpStartS3FileType.OPEN_WEIGHT_MANIFEST) + + mock_local_get.assert_called_once_with(test_key, JumpStartS3FileType.OPEN_WEIGHT_MANIFEST) + assert result == test_json_data + assert etag is None + + +@patch("sagemaker.jumpstart.utils.get_region_fallback", lambda *args, **kwargs: "dummy-region") +@patch( + "sagemaker.jumpstart.utils.get_jumpstart_content_bucket", lambda *args, **kwargs: "dummy-bucket" +) +def test_get_json_file_local_mode_unsupported_type(): + """Test _get_json_file falls back to S3 for unsupported file types in local mode.""" + cache = JumpStartModelsCache() + test_key = "test/file/path.json" + test_json_data = {"key": "value"} + test_etag = "test-etag-123" + + with ( + patch.object(JumpStartModelsCache, "_is_local_metadata_mode", return_value=True), + patch.object( + JumpStartModelsCache, + "_get_json_file_and_etag_from_s3", + return_value=(test_json_data, test_etag), + ) as mock_s3_get, + patch("sagemaker.jumpstart.cache.JUMPSTART_LOGGER.warning") as mock_warning, + ): + result, etag = cache._get_json_file(test_key, JumpStartS3FileType.PROPRIETARY_MANIFEST) + + mock_s3_get.assert_called_once_with(test_key) + mock_warning.assert_called_once() + assert "not supported for local override" in mock_warning.call_args[0][0] + assert result == test_json_data + assert etag == test_etag diff --git a/tests/unit/sagemaker/jumpstart/test_types.py b/tests/unit/sagemaker/jumpstart/test_types.py index 0b5ef63947..03a85fee44 100644 --- a/tests/unit/sagemaker/jumpstart/test_types.py +++ b/tests/unit/sagemaker/jumpstart/test_types.py @@ -39,6 +39,8 @@ INIT_KWARGS, ) +from unittest.mock import Mock + INSTANCE_TYPE_VARIANT = JumpStartInstanceTypeVariants( { "regional_aliases": { @@ -329,14 +331,67 @@ def test_jumpstart_model_header(): assert header1 == header3 -def test_use_training_model_artifact(): - specs1 = JumpStartModelSpecs(BASE_SPEC) - assert specs1.use_training_model_artifact() - specs1.gated_bucket = True - assert not specs1.use_training_model_artifact() - specs1.gated_bucket = False - specs1.training_model_package_artifact_uris = {"region1": "blah", "region2": "blah2"} - assert not specs1.use_training_model_artifact() +class TestUseTrainingModelArtifact: + @pytest.fixture + def mock_specs(self): + specs = Mock(spec=JumpStartModelSpecs) + specs.training_instance_type_variants = Mock() + specs.supported_training_instance_types = ["ml.p3.2xlarge", "ml.g4dn.xlarge"] + specs.training_model_package_artifact_uris = {} + specs.training_artifact_key = None + return specs + + def test_use_training_model_artifact_with_env_var(self, mock_specs): + """Test when instance type variants have env var values.""" + mock_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value.side_effect = [ + "some-value", + None, + ] + + result = JumpStartModelSpecs.use_training_model_artifact(mock_specs) + + assert result is False + mock_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value.assert_any_call( + "ml.p3.2xlarge" + ) + + def test_use_training_model_artifact_with_package_uris(self, mock_specs): + """Test when model has training package artifact URIs.""" + mock_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value.return_value = ( + None + ) + mock_specs.training_model_package_artifact_uris = { + "ml.p3.2xlarge": "arn:aws:sagemaker:ap-southeast-1:192199979996:model-package/" + "llama2-13b-e155a2e0347b323fb882f1875851c5d3" + } + + result = JumpStartModelSpecs.use_training_model_artifact(mock_specs) + + assert result is False + + def test_use_training_model_artifact_with_artifact_key(self, mock_specs): + """Test when model has training artifact key.""" + mock_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value.return_value = ( + None + ) + mock_specs.training_model_package_artifact_uris = {} + mock_specs.training_artifact_key = "some-key" + + result = JumpStartModelSpecs.use_training_model_artifact(mock_specs) + + assert result is True + + def test_use_training_model_artifact_without_artifact_key(self, mock_specs): + """Test when model has no training artifact key.""" + mock_specs.training_instance_type_variants.get_instance_specific_gated_model_key_env_var_value.return_value = ( + None + ) + mock_specs.training_model_package_artifact_uris = {} + mock_specs.training_artifact_key = None + + result = JumpStartModelSpecs.use_training_model_artifact(mock_specs) + + assert result is False def test_jumpstart_model_specs(): From 8ec4d8900a2df5483e5e2e729e54836634049788 Mon Sep 17 00:00:00 2001 From: ci Date: Mon, 19 May 2025 20:51:55 +0000 Subject: [PATCH 101/164] prepare release v2.244.2 --- CHANGELOG.md | 11 +++++++++++ VERSION | 2 +- 2 files changed, 12 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index d86535c7b5..580adc3356 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,16 @@ # Changelog +## v2.244.2 (2025-05-19) + +### Bug Fixes and Other Changes + + * include model channel for gated uncompressed models + * clarify model monitor one time schedule bug + * update jumpstart region_config 05-15-2025 07:18:15 PST + * update image_uri_configs 05-14-2025 07:18:16 PST + * Add image configs and region config for TPE (ap-east-2) + * Improve defaults handling in ModelTrainer + ## v2.244.1 (2025-05-15) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index 7c4fab2fd9..505bfa4996 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.2.dev0 +2.244.2 From 4cfc43e105fa54f87568c43031f79dce8d2fc879 Mon Sep 17 00:00:00 2001 From: ci Date: Mon, 19 May 2025 20:52:01 +0000 Subject: [PATCH 102/164] update development version to v2.244.3.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 505bfa4996..f16f344be5 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.2 +2.244.3.dev0 From e69761923766e4946f0a52959fe3cdf9506144dd Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 20 May 2025 14:18:17 +0000 Subject: [PATCH 103/164] change: update image_uri_configs 05-20-2025 07:18:17 PST --- .../huggingface-llm-neuronx.json | 55 ++++++++++++++++++- 1 file changed, 54 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index d79e7637ed..9b7b18ee94 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -4,7 +4,7 @@ "inf2" ], "version_aliases": { - "0.0": "0.0.27" + "0.0": "0.0.28" }, "versions": { "0.0.16": { @@ -589,6 +589,59 @@ "container_version": { "inf2": "ubuntu22.04" } + }, + "0.0.28": { + "py_versions": [ + "py310" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-iso-east-1": "886529160074", + "us-isob-east-1": "094389454867", + "us-isof-east-1": "303241398832", + "us-isof-south-1": "454834333376", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "tag_prefix": "2.1.2-optimum0.0.28", + "repository": "huggingface-pytorch-tgi-inference", + "container_version": { + "inf2": "ubuntu22.04" + } } } } From 5ce7249ee6c11033bbe4ab9e6f8879198245762e Mon Sep 17 00:00:00 2001 From: DemyCode Date: Wed, 21 May 2025 22:59:34 +0000 Subject: [PATCH 104/164] feat: Correct mypy type checking through PEP 561 (#5027) Co-authored-by: parknate@ Co-authored-by: Molly He --- setup.py | 2 +- src/sagemaker/py.typed | 0 2 files changed, 1 insertion(+), 1 deletion(-) create mode 100644 src/sagemaker/py.typed diff --git a/setup.py b/setup.py index 3deaed54e0..f651c27898 100644 --- a/setup.py +++ b/setup.py @@ -58,7 +58,7 @@ def get_optional_dependencies(): version=HERE.joinpath("VERSION").read_text().strip(), packages=find_packages("src"), package_dir={"": "src"}, - package_data={"": ["*.whl"]}, + package_data={"": ["*.whl", "py.typed"]}, py_modules=[os.path.splitext(os.path.basename(path))[0] for path in glob("src/*.py")], include_package_data=True, install_requires=get_dependencies(), diff --git a/src/sagemaker/py.typed b/src/sagemaker/py.typed new file mode 100644 index 0000000000..e69de29bb2 From 3f484d7a0e9b3e1ab7682cc399ee57d763334756 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 21 May 2025 18:02:48 -0700 Subject: [PATCH 105/164] change: merge method inputs with class inputs (#5183) --- src/sagemaker/modules/train/model_trainer.py | 30 ++++++++++---- .../modules/train/test_model_trainer.py | 41 +++++++++++++++++++ 2 files changed, 62 insertions(+), 9 deletions(-) diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 58ae724074..2143da4e5c 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -580,7 +580,7 @@ def train( """Train a model using AWS SageMaker. Args: - input_data_config (Optional[Union[List[Channel], Dict[str, DataSourceType]]]): + input_data_config (Optional[List[Union[Channel, InputData]]]): The input data config for the training job. Takes a list of Channel objects or a dictionary of channel names to DataSourceType. DataSourceType can be an S3 URI string, local file path string, @@ -596,11 +596,23 @@ def train( current_training_job_name = _get_unique_name(self.base_job_name) input_data_key_prefix = f"{self.base_job_name}/{current_training_job_name}/input" - self.input_data_config = input_data_config or self.input_data_config or [] + final_input_data_config = self.input_data_config.copy() if self.input_data_config else [] + + if input_data_config: + # merge the inputs with method parameter taking precedence + existing_channels = {input.channel_name: input for input in final_input_data_config} + new_channels = [] + for new_input in input_data_config: + if new_input.channel_name in existing_channels: + existing_channels[new_input.channel_name] = new_input + else: + new_channels.append(new_input) + + final_input_data_config = list(existing_channels.values()) + new_channels - if self.input_data_config: - self.input_data_config = self._get_input_data_config( - self.input_data_config, input_data_key_prefix + if final_input_data_config: + final_input_data_config = self._get_input_data_config( + final_input_data_config, input_data_key_prefix ) if self.checkpoint_config and not self.checkpoint_config.s3_uri: @@ -643,7 +655,7 @@ def train( data_source=self.source_code.source_dir, key_prefix=input_data_key_prefix, ) - self.input_data_config.append(source_code_channel) + final_input_data_config.append(source_code_channel) self._prepare_train_script( tmp_dir=tmp_dir, @@ -664,7 +676,7 @@ def train( data_source=tmp_dir.name, key_prefix=input_data_key_prefix, ) - self.input_data_config.append(sm_drivers_channel) + final_input_data_config.append(sm_drivers_channel) # If source_code is provided, we will always use # the default container entrypoint and arguments @@ -691,7 +703,7 @@ def train( training_job_name=current_training_job_name, algorithm_specification=algorithm_specification, hyper_parameters=string_hyper_parameters, - input_data_config=self.input_data_config, + input_data_config=final_input_data_config, resource_config=resource_config, vpc_config=vpc_config, # Public Instance Attributes @@ -736,7 +748,7 @@ def train( sagemaker_session=self.sagemaker_session, container_entrypoint=algorithm_specification.container_entrypoint, container_arguments=algorithm_specification.container_arguments, - input_data_config=self.input_data_config, + input_data_config=final_input_data_config, hyper_parameters=string_hyper_parameters, environment=self.environment, ) diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index b1348b5ac9..5d4722b8aa 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -1258,3 +1258,44 @@ def mock_upload_data(path, bucket, key_prefix): assert kwargs["tensor_board_output_config"].s3_output_path == default_base_path assert kwargs["tensor_board_output_config"].local_path == "/opt/ml/output/tensorboard" + + +@patch("sagemaker.modules.train.model_trainer.TrainingJob") +def test_input_merge(mock_training_job, modules_session): + model_input = InputData(channel_name="model", data_source="s3://bucket/model/model.tar.gz") + model_trainer = ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + input_data_config=[model_input], + ) + + train_input = InputData(channel_name="train", data_source="s3://bucket/data/train") + model_trainer.train(input_data_config=[train_input]) + + mock_training_job.create.assert_called_once() + assert mock_training_job.create.call_args.kwargs["input_data_config"] == [ + Channel( + channel_name="model", + data_source=DataSource( + s3_data_source=S3DataSource( + s3_data_type="S3Prefix", + s3_uri="s3://bucket/model/model.tar.gz", + s3_data_distribution_type="FullyReplicated", + ) + ), + input_mode="File", + ), + Channel( + channel_name="train", + data_source=DataSource( + s3_data_source=S3DataSource( + s3_data_type="S3Prefix", + s3_uri="s3://bucket/data/train", + s3_data_distribution_type="FullyReplicated", + ) + ), + input_mode="File", + ), + ] From 6fb3b813d487d65b2114d129370ea012e9e37f07 Mon Sep 17 00:00:00 2001 From: haozhx23 <121946073+haozhx23@users.noreply.github.com> Date: Fri, 23 May 2025 00:03:36 +0800 Subject: [PATCH 106/164] fix: addWaiterTimeoutHandling (#4951) * addWaiterTimeoutHandling * codeStyleUpdate * updateCodeStyle * updateCodeStyle * updateCodeStyle * updateCodeStyle * updateCodeStyle * updateCodeStyle --------- Co-authored-by: Ubuntu Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Co-authored-by: Ubuntu --- src/sagemaker/predictor_async.py | 29 ++++++++++++++++------------- 1 file changed, 16 insertions(+), 13 deletions(-) diff --git a/src/sagemaker/predictor_async.py b/src/sagemaker/predictor_async.py index ef70b93599..783d034011 100644 --- a/src/sagemaker/predictor_async.py +++ b/src/sagemaker/predictor_async.py @@ -271,6 +271,7 @@ def _check_output_and_failure_paths(self, output_path, failure_path, waiter_conf output_file_found = threading.Event() failure_file_found = threading.Event() + waiter_error_catched = threading.Event() def check_output_file(): try: @@ -282,7 +283,7 @@ def check_output_file(): ) output_file_found.set() except WaiterError: - pass + waiter_error_catched.set() def check_failure_file(): try: @@ -294,7 +295,7 @@ def check_failure_file(): ) failure_file_found.set() except WaiterError: - pass + waiter_error_catched.set() output_thread = threading.Thread(target=check_output_file) failure_thread = threading.Thread(target=check_failure_file) @@ -302,7 +303,11 @@ def check_failure_file(): output_thread.start() failure_thread.start() - while not output_file_found.is_set() and not failure_file_found.is_set(): + while ( + not output_file_found.is_set() + and not failure_file_found.is_set() + and not waiter_error_catched.is_set() + ): time.sleep(1) if output_file_found.is_set(): @@ -310,17 +315,15 @@ def check_failure_file(): result = self.predictor._handle_response(response=s3_object) return result - failure_object = self.s3_client.get_object(Bucket=failure_bucket, Key=failure_key) - failure_response = self.predictor._handle_response(response=failure_object) + if failure_file_found.is_set(): + failure_object = self.s3_client.get_object(Bucket=failure_bucket, Key=failure_key) + failure_response = self.predictor._handle_response(response=failure_object) + raise AsyncInferenceModelError(message=failure_response) - raise ( - AsyncInferenceModelError(message=failure_response) - if failure_file_found.is_set() - else PollingTimeoutError( - message="Inference could still be running", - output_path=output_path, - seconds=waiter_config.delay * waiter_config.max_attempts, - ) + raise PollingTimeoutError( + message="Inference could still be running", + output_path=output_path, + seconds=waiter_config.delay * waiter_config.max_attempts, ) def update_endpoint( From a897b4306c07329d7df528c3ef47e26597146f1c Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Wed, 28 May 2025 10:19:21 -0700 Subject: [PATCH 107/164] MLFLow update for dependabot (#5187) * MLFLow update for dependabot * Update lower bound * Unit test fixes --- requirements/extras/test_requirements.txt | 2 +- .../mlflow/test_forward_sagemaker_metrics.py | 11 +++++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 8bdd7c8ae3..92273f2c9a 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -44,7 +44,7 @@ nbformat>=5.9,<6 accelerate>=0.24.1,<=0.27.0 schema==0.7.5 tensorflow>=2.16.2,<=2.18.0 -mlflow>=2.12.2,<2.13 +mlflow>=2.14.2,<3 huggingface_hub==0.26.2 uvicorn>=0.30.1 fastapi==0.115.4 diff --git a/tests/unit/sagemaker/mlflow/test_forward_sagemaker_metrics.py b/tests/unit/sagemaker/mlflow/test_forward_sagemaker_metrics.py index 4b53c93ad4..14502880c3 100644 --- a/tests/unit/sagemaker/mlflow/test_forward_sagemaker_metrics.py +++ b/tests/unit/sagemaker/mlflow/test_forward_sagemaker_metrics.py @@ -48,7 +48,7 @@ def mock_mlflow_client(): def test_encode(): existing_names = set() assert encode("test-name", existing_names) == "test-name" - assert encode("test:name", existing_names) == "test_3a_name" + assert encode("test:name", existing_names) == "test:name" assert encode("test-name", existing_names) == "test-name_1" @@ -183,6 +183,7 @@ def getenv_side_effect(arg, default=None): spec=requests.Response ), "https://test.sagemaker.aws/api/2.0/mlflow/runs/create": Mock(spec=requests.Response), + "https://test.sagemaker.aws/api/2.0/mlflow/runs/update": Mock(spec=requests.Response), "https://test.sagemaker.aws/api/2.0/mlflow/runs/log-batch": [ Mock(spec=requests.Response), Mock(spec=requests.Response), @@ -211,6 +212,11 @@ def getenv_side_effect(arg, default=None): {"run_id": "test_run_id"} ) + mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/update"].status_code = 200 + mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/update"].text = json.dumps( + {"run_id": "test_run_id"} + ) + for mock_response in mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/log-batch"]: mock_response.status_code = 200 mock_response.text = json.dumps({}) @@ -221,6 +227,7 @@ def getenv_side_effect(arg, default=None): mock_request.side_effect = [ mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/experiments/get-by-name"], mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/create"], + mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/update"], *mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/log-batch"], mock_responses["https://test.sagemaker.aws/api/2.0/mlflow/runs/terminate"], ] @@ -231,7 +238,7 @@ def getenv_side_effect(arg, default=None): log_to_mlflow(metrics, params, tags) - assert mock_request.call_count == 6 # Total number of API calls + assert mock_request.call_count == 7 # Total number of API calls @patch("sagemaker.mlflow.forward_sagemaker_metrics.get_training_job_details") From 629c652abaf6a0e8ef3e08645c0d5d1efbc6e48a Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 28 May 2025 23:37:09 +0000 Subject: [PATCH 108/164] prepare release v2.245.0 --- CHANGELOG.md | 13 +++++++++++++ VERSION | 2 +- 2 files changed, 14 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 580adc3356..859bc2413b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,18 @@ # Changelog +## v2.245.0 (2025-05-28) + +### Features + + * Correct mypy type checking through PEP 561 + +### Bug Fixes and Other Changes + + * MLFLow update for dependabot + * addWaiterTimeoutHandling + * merge method inputs with class inputs + * update image_uri_configs 05-20-2025 07:18:17 PST + ## v2.244.2 (2025-05-19) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index f16f344be5..89dc298c15 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.244.3.dev0 +2.245.0 From 3dffff051c9ecbb91cd66431f9afa20a0c80a038 Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 28 May 2025 23:37:14 +0000 Subject: [PATCH 109/164] update development version to v2.245.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 89dc298c15..aca3af02c1 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.245.0 +2.245.1.dev0 From e1b6a7f2bd6af03006651c15ad8dc529c0f68939 Mon Sep 17 00:00:00 2001 From: Mohan Kishore Date: Fri, 30 May 2025 08:50:08 -0700 Subject: [PATCH 110/164] feature: Triton v25.04 DLC (#5188) Co-authored-by: Mohan Kishore --- .../sagemaker-tritonserver.json | 379 ++++++++++-------- 1 file changed, 210 insertions(+), 169 deletions(-) diff --git a/src/sagemaker/image_uri_config/sagemaker-tritonserver.json b/src/sagemaker/image_uri_config/sagemaker-tritonserver.json index 8f29a65e4e..91842ae713 100644 --- a/src/sagemaker/image_uri_config/sagemaker-tritonserver.json +++ b/src/sagemaker/image_uri_config/sagemaker-tritonserver.json @@ -1,171 +1,212 @@ { - "processors": [ - "cpu", - "gpu" - ], - "scope": [ - "inference" - ], - "versions": { - "24.09": { - "registries": { - "af-south-1": "626614931356", - "il-central-1": "780543022126", - "ap-east-1": "871362719292", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ca-central-1": "763104351884", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "me-south-1": "217643126080", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" - }, - "repository": "sagemaker-tritonserver", - "tag_prefix": "24.09-py3" - }, - "24.05": { - "registries": { - "af-south-1": "626614931356", - "il-central-1": "780543022126", - "ap-east-1": "871362719292", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ca-central-1": "763104351884", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "me-south-1": "217643126080", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" - }, - "repository": "sagemaker-tritonserver", - "tag_prefix": "24.05-py3" - }, - "24.03": { - "registries": { - "af-south-1": "626614931356", - "il-central-1": "780543022126", - "ap-east-1": "871362719292", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ca-central-1": "763104351884", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "me-south-1": "217643126080", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" - }, - "repository": "sagemaker-tritonserver", - "tag_prefix": "24.03-py3" - }, - "24.01": { - "registries": { - "af-south-1": "626614931356", - "il-central-1": "780543022126", - "ap-east-1": "871362719292", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ca-central-1": "763104351884", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "me-south-1": "217643126080", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" - }, - "repository": "sagemaker-tritonserver", - "tag_prefix": "24.01-py3" - }, - "23.12": { - "registries": { - "af-south-1": "626614931356", - "il-central-1": "780543022126", - "ap-east-1": "871362719292", - "ap-northeast-1": "763104351884", - "ap-northeast-2": "763104351884", - "ap-northeast-3": "364406365360", - "ap-south-1": "763104351884", - "ap-southeast-1": "763104351884", - "ap-southeast-2": "763104351884", - "ap-southeast-3": "907027046896", - "ca-central-1": "763104351884", - "cn-north-1": "727897471807", - "cn-northwest-1": "727897471807", - "eu-central-1": "763104351884", - "eu-north-1": "763104351884", - "eu-west-1": "763104351884", - "eu-west-2": "763104351884", - "eu-west-3": "763104351884", - "eu-south-1": "692866216735", - "me-south-1": "217643126080", - "sa-east-1": "763104351884", - "us-east-1": "763104351884", - "us-east-2": "763104351884", - "us-west-1": "763104351884", - "us-west-2": "763104351884", - "ca-west-1": "204538143572" - }, - "repository": "sagemaker-tritonserver", - "tag_prefix": "23.12-py3" - } - } + "processors": [ + "cpu", + "gpu" + ], + "scope": [ + "inference" + ], + "versions": { + "25.04": { + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "25.04-py3" + }, + "24.09": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "24.09-py3" + }, + "24.05": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "24.05-py3" + }, + "24.03": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "24.03-py3" + }, + "24.01": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "24.01-py3" + }, + "23.12": { + "registries": { + "af-south-1": "626614931356", + "il-central-1": "780543022126", + "ap-east-1": "871362719292", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ca-central-1": "763104351884", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-north-1": "763104351884", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "eu-south-1": "692866216735", + "me-south-1": "217643126080", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-west-1": "763104351884", + "us-west-2": "763104351884", + "ca-west-1": "204538143572" + }, + "repository": "sagemaker-tritonserver", + "tag_prefix": "23.12-py3" + } + } } From f6a5050547fdf2d60d56d93722f7c51ba6ec30ae Mon Sep 17 00:00:00 2001 From: Molly He Date: Tue, 3 Jun 2025 10:03:16 -0700 Subject: [PATCH 111/164] update estimator documentation regarding hyperparameters for source_dir (#5190) --- src/sagemaker/estimator.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py index fa40719c9f..16e6ac1cd0 100644 --- a/src/sagemaker/estimator.py +++ b/src/sagemaker/estimator.py @@ -456,6 +456,9 @@ def __init__( A dictionary containing the hyperparameters to initialize this estimator with. (Default: None). + If a source directory is specified, the set_hyperparameters method escapes + the dict argument as JSON, and updates the private hyperparameter attribute. + .. caution:: You must not include any security-sensitive information, such as account access IDs, secrets, and tokens, in the dictionary for configuring From baf16015f73b0e6d5a3f0269e32433cb2bf72a91 Mon Sep 17 00:00:00 2001 From: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> Date: Tue, 3 Jun 2025 10:57:34 -0700 Subject: [PATCH 112/164] Update Attrs version to widen support (#5185) * Update Attrs version to widen support **Description** https://github.com/aws/sagemaker-python-sdk/issues/5075 **Testing Done** Running unit and integ tests Unit and integ tests passing indicate that this version upgrade does not break anything * Update version in conda_in_process.yml * Update test requirements * MLFlow update version --- Tested by : Running unit and integ tests --- pyproject.toml | 2 +- requirements/extras/test_requirements.txt | 2 +- src/sagemaker/serve/utils/conda_in_process.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 17dfab3571..918e874b57 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -31,7 +31,7 @@ classifiers = [ "Programming Language :: Python :: 3.12", ] dependencies = [ - "attrs>=23.1.0,<24", + "attrs>=24,<26", "boto3>=1.35.75,<2.0", "cloudpickle>=2.2.1", "docker", diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 92273f2c9a..04d6c0522a 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -17,7 +17,7 @@ stopit==1.1.2 apache-airflow==2.10.4 apache-airflow-providers-amazon==7.2.1 Flask-Limiter==3.11 -attrs>=23.1.0,<24 +attrs>=24,<26 fabric==3.2.2 requests==2.32.2 sagemaker-experiments==0.1.35 diff --git a/src/sagemaker/serve/utils/conda_in_process.yml b/src/sagemaker/serve/utils/conda_in_process.yml index 1f3fe322ef..d51754ec5a 100644 --- a/src/sagemaker/serve/utils/conda_in_process.yml +++ b/src/sagemaker/serve/utils/conda_in_process.yml @@ -8,7 +8,7 @@ dependencies: - fastapi>=0.111.0 - nest-asyncio - pip>=23.0.1 - - attrs>=23.1.0,<24 + - attrs>=24,<26 - boto3>=1.34.142,<2.0 - cloudpickle==2.2.1 - google-pasta From 91684ee49b30bf9aa6c5c03dcba04dfc55d09890 Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 4 Jun 2025 23:10:19 +0000 Subject: [PATCH 113/164] prepare release v2.246.0 --- CHANGELOG.md | 11 +++++++++++ VERSION | 2 +- 2 files changed, 12 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 859bc2413b..2349827551 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,16 @@ # Changelog +## v2.246.0 (2025-06-04) + +### Features + + * Triton v25.04 DLC + +### Bug Fixes and Other Changes + + * Update Attrs version to widen support + * update estimator documentation regarding hyperparameters for source_dir + ## v2.245.0 (2025-05-28) ### Features diff --git a/VERSION b/VERSION index aca3af02c1..43e557e27e 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.245.1.dev0 +2.246.0 From aba802c7f2711a8d5593894c6d22c51f0215d5a1 Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 4 Jun 2025 23:10:24 +0000 Subject: [PATCH 114/164] update development version to v2.246.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 43e557e27e..657c15330d 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.246.0 +2.246.1.dev0 From 5198f284b217980e568229e360244795fa2b664e Mon Sep 17 00:00:00 2001 From: Will Childs-Klein Date: Fri, 6 Jun 2025 16:44:48 -0400 Subject: [PATCH 115/164] fix: Allow import failure for internal _hashlib module (#5192) * fix: Allow import failure for _hashlib module * Fix formatting * Appease flake8 --- src/sagemaker/workflow/utilities.py | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/workflow/utilities.py b/src/sagemaker/workflow/utilities.py index 4fc98eb29a..961972da4d 100644 --- a/src/sagemaker/workflow/utilities.py +++ b/src/sagemaker/workflow/utilities.py @@ -21,7 +21,15 @@ import hashlib from urllib.parse import unquote, urlparse from contextlib import contextmanager -from _hashlib import HASH as Hash + +try: + # _hashlib is an internal python module, and is not present in + # statically linked interpreters. + from _hashlib import HASH as Hash +except ImportError: + import typing + + Hash = typing.Any from sagemaker.utils import base_from_name from sagemaker.workflow.parameters import Parameter From 829030aaa8ff84ba2e5a2bbf594f6f890001c28a Mon Sep 17 00:00:00 2001 From: Molly He Date: Tue, 10 Jun 2025 10:02:21 -0700 Subject: [PATCH 116/164] Add ignore_patterns in ModelTrainer to ignore specific files/folders (#5194) * Add ignore_patterns in ModelTrainer to ignore specific files/folders * fix black format * add unit test * add default ignore_patterns, fix minor path issue when uploaded to s3 * minor change to fix unit test failure * add new variables in default ignore_patterns * fix indentation error in docstring for readthedocs --- src/sagemaker/modules/configs.py | 13 +++++- src/sagemaker/modules/train/model_trainer.py | 46 +++++++++++++++---- .../modules/train/test_model_trainer.py | 12 +++++ 3 files changed, 62 insertions(+), 9 deletions(-) diff --git a/src/sagemaker/modules/configs.py b/src/sagemaker/modules/configs.py index 3739c73c5d..1ada10dff3 100644 --- a/src/sagemaker/modules/configs.py +++ b/src/sagemaker/modules/configs.py @@ -21,7 +21,7 @@ from __future__ import absolute_import -from typing import Optional, Union +from typing import Optional, Union, List from pydantic import BaseModel, model_validator, ConfigDict import sagemaker_core.shapes as shapes @@ -96,12 +96,23 @@ class SourceCode(BaseConfig): command (Optional[str]): The command(s) to execute in the training job container. Example: "python my_script.py". If not specified, entry_script must be provided. + ignore_patterns: (Optional[List[str]]) : + The ignore patterns to ignore specific files/folders when uploading to S3. If not specified, + default to: ['.env', '.git', '__pycache__', '.DS_Store', '.cache', '.ipynb_checkpoints']. """ source_dir: Optional[str] = None requirements: Optional[str] = None entry_script: Optional[str] = None command: Optional[str] = None + ignore_patterns: Optional[List[str]] = [ + ".env", + ".git", + "__pycache__", + ".DS_Store", + ".cache", + ".ipynb_checkpoints", + ] class Compute(shapes.ResourceConfig): diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 2143da4e5c..7d83766c9f 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -119,7 +119,8 @@ class ModelTrainer(BaseModel): from sagemaker.modules.train import ModelTrainer from sagemaker.modules.configs import SourceCode, Compute, InputData - source_code = SourceCode(source_dir="source", entry_script="train.py") + ignore_patterns = ['.env', '.git', '__pycache__', '.DS_Store', 'data'] + source_code = SourceCode(source_dir="source", entry_script="train.py", ignore_patterns=ignore_patterns) training_image = "123456789012.dkr.ecr.us-west-2.amazonaws.com/my-training-image" model_trainer = ModelTrainer( training_image=training_image, @@ -654,6 +655,7 @@ def train( channel_name=SM_CODE, data_source=self.source_code.source_dir, key_prefix=input_data_key_prefix, + ignore_patterns=self.source_code.ignore_patterns, ) final_input_data_config.append(source_code_channel) @@ -675,6 +677,7 @@ def train( channel_name=SM_DRIVERS, data_source=tmp_dir.name, key_prefix=input_data_key_prefix, + ignore_patterns=self.source_code.ignore_patterns, ) final_input_data_config.append(sm_drivers_channel) @@ -755,7 +758,11 @@ def train( local_container.train(wait) def create_input_data_channel( - self, channel_name: str, data_source: DataSourceType, key_prefix: Optional[str] = None + self, + channel_name: str, + data_source: DataSourceType, + key_prefix: Optional[str] = None, + ignore_patterns: Optional[List[str]] = None, ) -> Channel: """Create an input data channel for the training job. @@ -771,6 +778,10 @@ def create_input_data_channel( If specified, local data will be uploaded to: ``s3://///`` + ignore_patterns: (Optional[List[str]]) : + The ignore patterns to ignore specific files/folders when uploading to S3. + If not specified, default to: ['.env', '.git', '__pycache__', '.DS_Store', + '.cache', '.ipynb_checkpoints']. """ channel = None if isinstance(data_source, str): @@ -810,11 +821,28 @@ def create_input_data_channel( ) if self.sagemaker_session.default_bucket_prefix: key_prefix = f"{self.sagemaker_session.default_bucket_prefix}/{key_prefix}" - s3_uri = self.sagemaker_session.upload_data( - path=data_source, - bucket=self.sagemaker_session.default_bucket(), - key_prefix=key_prefix, - ) + if ignore_patterns and _is_valid_path(data_source, path_type="Directory"): + tmp_dir = TemporaryDirectory() + copied_path = os.path.join( + tmp_dir.name, os.path.basename(os.path.normpath(data_source)) + ) + shutil.copytree( + data_source, + copied_path, + dirs_exist_ok=True, + ignore=shutil.ignore_patterns(*ignore_patterns), + ) + s3_uri = self.sagemaker_session.upload_data( + path=copied_path, + bucket=self.sagemaker_session.default_bucket(), + key_prefix=key_prefix, + ) + else: + s3_uri = self.sagemaker_session.upload_data( + path=data_source, + bucket=self.sagemaker_session.default_bucket(), + key_prefix=key_prefix, + ) channel = Channel( channel_name=channel_name, data_source=DataSource( @@ -861,7 +889,9 @@ def _get_input_data_config( channels.append(input_data) elif isinstance(input_data, InputData): channel = self.create_input_data_channel( - input_data.channel_name, input_data.data_source, key_prefix=key_prefix + input_data.channel_name, + input_data.data_source, + key_prefix=key_prefix, ) channels.append(channel) else: diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 5d4722b8aa..cf38f26334 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -202,6 +202,17 @@ def model_trainer(): }, "should_throw": False, }, + { + "init_params": { + "training_image": DEFAULT_IMAGE, + "source_code": SourceCode( + source_dir=DEFAULT_SOURCE_DIR, + command="python custom_script.py", + ignore_patterns=["data"], + ), + }, + "should_throw": False, + }, ], ids=[ "no_params", @@ -213,6 +224,7 @@ def model_trainer(): "supported_source_code_local_tar_file", "supported_source_code_s3_dir", "supported_source_code_s3_tar_file", + "supported_source_code_ignore_patterns", ], ) def test_model_trainer_param_validation(test_case, modules_session): From 844b5588862b6f843cd6934edd00d58343a0182f Mon Sep 17 00:00:00 2001 From: Aditi Sharma <165942273+Aditi2424@users.noreply.github.com> Date: Tue, 10 Jun 2025 13:37:53 -0700 Subject: [PATCH 117/164] Fix: Object of type ModelLifeCycle is not JSON serializable (#5197) * Fix: Object of type ModelLifeCycle is not JSON serializable * Fix unit test * Fix integ tests * Revert "Fix integ tests" This reverts commit f6513fe430d7f7f13486239aaaf6983efde2e00f. * Fix integration tests --------- Co-authored-by: adishaa --- src/sagemaker/session.py | 2 +- .../workflow/test_model_create_and_registration.py | 11 ++++++----- tests/integ/test_model_package.py | 2 +- tests/unit/test_estimator.py | 3 +-- 4 files changed, 9 insertions(+), 9 deletions(-) diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py index 2cc18f6989..2ff561d784 100644 --- a/src/sagemaker/session.py +++ b/src/sagemaker/session.py @@ -7509,7 +7509,7 @@ def get_model_package_args( if source_uri is not None: model_package_args["source_uri"] = source_uri if model_life_cycle is not None: - model_package_args["model_life_cycle"] = model_life_cycle + model_package_args["model_life_cycle"] = model_life_cycle._to_request_dict() if model_card is not None: original_req = model_card._create_request_args() if original_req.get("ModelCardName") is not None: diff --git a/tests/integ/sagemaker/workflow/test_model_create_and_registration.py b/tests/integ/sagemaker/workflow/test_model_create_and_registration.py index 8f98cd076d..e84c1920f4 100644 --- a/tests/integ/sagemaker/workflow/test_model_create_and_registration.py +++ b/tests/integ/sagemaker/workflow/test_model_create_and_registration.py @@ -48,6 +48,7 @@ from sagemaker.s3 import S3Uploader from sagemaker.sklearn import SKLearnModel, SKLearnProcessor from sagemaker.mxnet.model import MXNetModel +from sagemaker.model_life_cycle import ModelLifeCycle from sagemaker.workflow.condition_step import ConditionStep from sagemaker.workflow.parameters import ParameterInteger, ParameterString from sagemaker.workflow.pipeline import Pipeline @@ -1005,11 +1006,11 @@ def test_model_registration_with_model_life_cycle_object( py_version="py3", role=role, ) - create_model_life_cycle = { - "Stage": "Development", - "StageStatus": "In-Progress", - "StageDescription": "Development In Progress", - } + create_model_life_cycle = ModelLifeCycle( + stage="Development", + stage_status="In-Progress", + stage_description="Development In Progress", + ) step_register = RegisterModel( name="MyRegisterModelStep", diff --git a/tests/integ/test_model_package.py b/tests/integ/test_model_package.py index bc8120bd07..1ac8e33fd8 100644 --- a/tests/integ/test_model_package.py +++ b/tests/integ/test_model_package.py @@ -103,7 +103,7 @@ def test_update_model_life_cycle_model_package(sagemaker_session): inference_instances=["ml.m5.large"], transform_instances=["ml.m5.large"], model_package_group_name=model_group_name, - model_life_cycle=create_model_life_cycle._to_request_dict(), + model_life_cycle=create_model_life_cycle, ) desc_model_package = sagemaker_session.sagemaker_client.describe_model_package( diff --git a/tests/unit/test_estimator.py b/tests/unit/test_estimator.py index 8294eb0039..11cc83a463 100644 --- a/tests/unit/test_estimator.py +++ b/tests/unit/test_estimator.py @@ -4369,7 +4369,6 @@ def test_register_default_image(sagemaker_session): stage_status="In-Progress", stage_description="Sending for Staging Verification", ) - update_model_life_cycle_req = update_model_life_cycle._to_request_dict() estimator.register( content_types=content_types, @@ -4384,7 +4383,7 @@ def test_register_default_image(sagemaker_session): nearest_model_name=nearest_model_name, data_input_configuration=data_input_config, model_card=model_card, - model_life_cycle=update_model_life_cycle_req, + model_life_cycle=update_model_life_cycle, ) sagemaker_session.create_model.assert_not_called() exp_model_card = { From 70b2f9a293014816bd801513b1e153fd3fe8cd17 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Thu, 12 Jun 2025 14:18:12 +0000 Subject: [PATCH 118/164] change: update jumpstart region_config, update image_uri_configs 06-12-2025 07:18:12 PST --- src/sagemaker/image_uri_config/pytorch.json | 48 ++++++++++++++++++++- src/sagemaker/jumpstart/region_config.json | 4 ++ 2 files changed, 51 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/image_uri_config/pytorch.json b/src/sagemaker/image_uri_config/pytorch.json index dbff976442..58b1fdfff7 100644 --- a/src/sagemaker/image_uri_config/pytorch.json +++ b/src/sagemaker/image_uri_config/pytorch.json @@ -1705,7 +1705,8 @@ "2.3": "2.3.0", "2.4": "2.4.0", "2.5": "2.5.1", - "2.6": "2.6.0" + "2.6": "2.6.0", + "2.7": "2.7.1" }, "versions": { "0.4.0": { @@ -2946,6 +2947,51 @@ "us-west-2": "763104351884" }, "repository": "pytorch-training" + }, + "2.7.1": { + "py_versions": [ + "py312" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "pytorch-training" } } } diff --git a/src/sagemaker/jumpstart/region_config.json b/src/sagemaker/jumpstart/region_config.json index 30bea6ee70..136bf8256c 100644 --- a/src/sagemaker/jumpstart/region_config.json +++ b/src/sagemaker/jumpstart/region_config.json @@ -7,6 +7,10 @@ "content_bucket": "jumpstart-cache-prod-ap-east-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-1" }, + "ap-east-2": { + "content_bucket": "jumpstart-cache-prod-ap-east-2", + "gated_content_bucket": "jumpstart-private-cache-prod-ap-east-2" + }, "ap-northeast-1": { "content_bucket": "jumpstart-cache-prod-ap-northeast-1", "gated_content_bucket": "jumpstart-private-cache-prod-ap-northeast-1", From 0215512600c4011d6f4c5ecf5e6975dae7da0adc Mon Sep 17 00:00:00 2001 From: Chad Chiang <42759281+chad119@users.noreply.github.com> Date: Thu, 12 Jun 2025 13:17:13 -0700 Subject: [PATCH 119/164] feat: Add support for MetricDefinitions in ModelTrainer (#5202) * feat: Add support for MetricDefinitions in ModelTrainer * style fix * Update model_trainer.py to generate the doc * resolve unit test failed * solve another unit test error --------- Co-authored-by: Chad Chiang --- src/sagemaker/modules/configs.py | 2 ++ src/sagemaker/modules/train/model_trainer.py | 33 +++++++++++++++++++ .../modules/train/test_model_trainer.py | 28 ++++++++++++++++ 3 files changed, 63 insertions(+) diff --git a/src/sagemaker/modules/configs.py b/src/sagemaker/modules/configs.py index 1ada10dff3..8fdf88e735 100644 --- a/src/sagemaker/modules/configs.py +++ b/src/sagemaker/modules/configs.py @@ -42,6 +42,7 @@ RemoteDebugConfig, SessionChainingConfig, InstanceGroup, + MetricDefinition, ) from sagemaker.modules.utils import convert_unassigned_to_none @@ -68,6 +69,7 @@ "Compute", "Networking", "InputData", + "MetricDefinition", ] diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 7d83766c9f..eaabe5972a 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -66,6 +66,7 @@ RemoteDebugConfig, SessionChainingConfig, InputData, + MetricDefinition, ) from sagemaker.modules.local_core.local_container import _LocalContainer @@ -239,6 +240,7 @@ class ModelTrainer(BaseModel): _infra_check_config: Optional[InfraCheckConfig] = PrivateAttr(default=None) _session_chaining_config: Optional[SessionChainingConfig] = PrivateAttr(default=None) _remote_debug_config: Optional[RemoteDebugConfig] = PrivateAttr(default=None) + _metric_definitions: Optional[List[MetricDefinition]] = PrivateAttr(default=None) _temp_recipe_train_dir: Optional[TemporaryDirectory] = PrivateAttr(default=None) @@ -696,6 +698,7 @@ def train( training_image_config=self.training_image_config, container_entrypoint=container_entrypoint, container_arguments=container_arguments, + metric_definitions=self._metric_definitions, ) resource_config = self.compute._to_resource_config() @@ -1290,3 +1293,33 @@ def with_checkpoint_config( """ self.checkpoint_config = checkpoint_config or configs.CheckpointConfig() return self + + def with_metric_definitions( + self, metric_definitions: List[MetricDefinition] + ) -> "ModelTrainer": # noqa: D412 + """Set the metric definitions for the training job. + + Example: + + .. code:: python + + from sagemaker.modules.train import ModelTrainer + from sagemaker.modules.configs import MetricDefinition + + metric_definitions = [ + MetricDefinition( + name="loss", + regex="Loss: (.*?)", + ) + ] + + model_trainer = ModelTrainer( + ... + ).with_metric_definitions(metric_definitions) + + Args: + metric_definitions (List[MetricDefinition]): + The metric definitions for the training job. + """ + self._metric_definitions = metric_definitions + return self diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index cf38f26334..23ea167ecf 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -64,6 +64,7 @@ FileSystemDataSource, Channel, DataSource, + MetricDefinition, ) from sagemaker.modules.distributed import Torchrun, SMP, MPI from sagemaker.modules.train.sm_recipes.utils import _load_recipes_cfg @@ -705,6 +706,32 @@ def test_remote_debug_config(mock_training_job, modules_session): ) +@patch("sagemaker.modules.train.model_trainer.TrainingJob") +def test_metric_definitions(mock_training_job, modules_session): + image_uri = DEFAULT_IMAGE + role = DEFAULT_ROLE + metric_definitions = [ + MetricDefinition( + name="loss", + regex="Loss: (.*?);", + ) + ] + + model_trainer = ModelTrainer( + training_image=image_uri, sagemaker_session=modules_session, role=role + ).with_metric_definitions(metric_definitions) + + with patch("sagemaker.modules.train.model_trainer.Session.upload_data") as mock_upload_data: + mock_upload_data.return_value = "s3://dummy-bucket/dummy-prefix" + model_trainer.train() + + mock_training_job.create.assert_called_once() + assert ( + mock_training_job.create.call_args.kwargs["algorithm_specification"].metric_definitions + == metric_definitions + ) + + @patch("sagemaker.modules.train.model_trainer._get_unique_name") @patch("sagemaker.modules.train.model_trainer.TrainingJob") def test_model_trainer_full_init(mock_training_job, mock_unique_name, modules_session): @@ -822,6 +849,7 @@ def mock_upload_data(path, bucket, key_prefix): training_input_mode=training_input_mode, training_image=training_image, algorithm_name=None, + metric_definitions=None, container_entrypoint=DEFAULT_ENTRYPOINT, container_arguments=DEFAULT_ARGUMENTS, training_image_config=training_image_config, From e22d254d1db3f1850bfaa25f8168fa8131211415 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 13 Jun 2025 22:27:02 +0000 Subject: [PATCH 120/164] prepare release v2.247.0 --- CHANGELOG.md | 12 ++++++++++++ VERSION | 2 +- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 2349827551..818de80d89 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,17 @@ # Changelog +## v2.247.0 (2025-06-13) + +### Features + + * Add support for MetricDefinitions in ModelTrainer + +### Bug Fixes and Other Changes + + * update jumpstart region_config, update image_uri_configs 06-12-2025 07:18:12 PST + * Add ignore_patterns in ModelTrainer to ignore specific files/folders + * Allow import failure for internal _hashlib module + ## v2.246.0 (2025-06-04) ### Features diff --git a/VERSION b/VERSION index 657c15330d..ca54e31f54 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.246.1.dev0 +2.247.0 From 23109671f6262269ab54cdd9aeb5ebe4ea640d25 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 13 Jun 2025 22:27:07 +0000 Subject: [PATCH 121/164] update development version to v2.247.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index ca54e31f54..4db8d6393a 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.247.0 +2.247.1.dev0 From 2680821a24bee64343190d99d0c28a15fbd773d0 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Thu, 19 Jun 2025 14:18:34 +0000 Subject: [PATCH 122/164] change: update image_uri_configs 06-19-2025 07:18:34 PST --- src/sagemaker/image_uri_config/spark.json | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/src/sagemaker/image_uri_config/spark.json b/src/sagemaker/image_uri_config/spark.json index bbb8c9b123..48c43fca15 100644 --- a/src/sagemaker/image_uri_config/spark.json +++ b/src/sagemaker/image_uri_config/spark.json @@ -11,6 +11,7 @@ "registries": { "af-south-1": "309385258863", "ap-east-1": "732049463269", + "ap-east-2": "533267296287", "ap-northeast-1": "411782140378", "ap-northeast-2": "860869212795", "ap-northeast-3": "102471314380", @@ -55,6 +56,7 @@ "registries": { "af-south-1": "309385258863", "ap-east-1": "732049463269", + "ap-east-2": "533267296287", "ap-northeast-1": "411782140378", "ap-northeast-2": "860869212795", "ap-northeast-3": "102471314380", @@ -99,6 +101,7 @@ "registries": { "af-south-1": "309385258863", "ap-east-1": "732049463269", + "ap-east-2": "533267296287", "ap-northeast-1": "411782140378", "ap-northeast-2": "860869212795", "ap-northeast-3": "102471314380", @@ -143,6 +146,7 @@ "registries": { "af-south-1": "309385258863", "ap-east-1": "732049463269", + "ap-east-2": "533267296287", "ap-northeast-1": "411782140378", "ap-northeast-2": "860869212795", "ap-northeast-3": "102471314380", @@ -187,6 +191,7 @@ "registries": { "af-south-1": "309385258863", "ap-east-1": "732049463269", + "ap-east-2": "533267296287", "ap-northeast-1": "411782140378", "ap-northeast-2": "860869212795", "ap-northeast-3": "102471314380", From 42066c4064bf904874aee0ed6c8fec80e19dddf9 Mon Sep 17 00:00:00 2001 From: ci Date: Mon, 23 Jun 2025 06:38:06 +0000 Subject: [PATCH 123/164] prepare release v2.247.1 --- CHANGELOG.md | 6 ++++++ VERSION | 2 +- 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 818de80d89..c43a7c91db 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,11 @@ # Changelog +## v2.247.1 (2025-06-23) + +### Bug Fixes and Other Changes + + * update image_uri_configs 06-19-2025 07:18:34 PST + ## v2.247.0 (2025-06-13) ### Features diff --git a/VERSION b/VERSION index 4db8d6393a..f01fb44831 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.247.1.dev0 +2.247.1 From a7b1368e2a3035c7a5c7657778b7f6cfcef9a161 Mon Sep 17 00:00:00 2001 From: ci Date: Mon, 23 Jun 2025 06:38:11 +0000 Subject: [PATCH 124/164] update development version to v2.247.2.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index f01fb44831..cdbe343ddb 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.247.1 +2.247.2.dev0 From e65b0d75e41d38cc33a1706b5ad25c09c60a587d Mon Sep 17 00:00:00 2001 From: "parknate@" Date: Mon, 23 Jun 2025 09:09:38 -0700 Subject: [PATCH 125/164] change: relax protobuf to <6.32 (#5211) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 918e874b57..87bc0a4d3c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -45,7 +45,7 @@ dependencies = [ "pandas", "pathos", "platformdirs", - "protobuf>=3.12,<6.0", + "protobuf>=3.12,<6.32", "psutil", "PyYAML>=6.0.1", "requests", From 31f34ddfcca3d98d044bf3ebd46ef3ed0faf7591 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Thu, 26 Jun 2025 14:18:35 +0000 Subject: [PATCH 126/164] change: update image_uri_configs 06-26-2025 07:18:35 PST --- src/sagemaker/image_uri_config/sagemaker-base-python.json | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/sagemaker/image_uri_config/sagemaker-base-python.json b/src/sagemaker/image_uri_config/sagemaker-base-python.json index 65b284d25e..cd64d73af1 100644 --- a/src/sagemaker/image_uri_config/sagemaker-base-python.json +++ b/src/sagemaker/image_uri_config/sagemaker-base-python.json @@ -4,6 +4,7 @@ "registries": { "af-south-1": "559312083959", "ap-east-1": "493642496378", + "ap-east-2": "938034419563", "ap-northeast-1": "102112518831", "ap-northeast-2": "806072073708", "ap-northeast-3": "792733760839", @@ -14,6 +15,7 @@ "ap-southeast-5": "148761635175", "ap-southeast-7": "528757812139", "ca-central-1": "310906938811", + "ca-west-1": "623308166672", "cn-north-1": "390048526115", "cn-northwest-1": "390780980154", "eu-central-1": "936697816551", From 51643165bd306cbd06a1679e26f2f037b6a5a93f Mon Sep 17 00:00:00 2001 From: uyoldas Date: Tue, 1 Jul 2025 19:26:35 +0200 Subject: [PATCH 127/164] feature: integrate amtviz for visualization of tuning jobs (#5044) * feature: integrate amtviz for visualization of tuning jobs * Move RecordSerializer and RecordDeserializer to sagemaker.serializers and sagemaker.deserialzers (#5037) * Move RecordSerializer and RecordDeserializer to sagemaker.serializers and sagemaker.deserializers * fix codestyle * fix test --------- Co-authored-by: pintaoz * Add framework_version to all TensorFlowModel examples (#5038) * Add framework_version to all TensorFlowModel examples * update framework_version to x.x.x --------- Co-authored-by: pintaoz * Fix hyperparameter strategy docs (#5045) * fix: pass in inference_ami_version to model_based endpoint type (#5043) * fix: pass in inference_ami_version to model_based endpoint type * documentation: update contributing.md w/ venv instructions and pip install fixes --------- Co-authored-by: Zhaoqi * Add warning about not supporting torch.nn.SyncBatchNorm (#5046) * Add warning about not supporting * update wording --------- Co-authored-by: pintaoz * prepare release v2.239.2 * update development version to v2.239.3.dev0 * change: update image_uri_configs 02-19-2025 06:18:15 PST * fix: codestyle, type hints, license, and docstrings * documentation: add docstring for amtviz module * fix: fix docstyle and flake8 errors * fix: code reformat using black --------- Co-authored-by: Uemit Yoldas Co-authored-by: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Co-authored-by: pintaoz Co-authored-by: parknate@ Co-authored-by: timkuo-amazon Co-authored-by: Zhaoqi Co-authored-by: ci Co-authored-by: sagemaker-bot --- src/sagemaker/amtviz/__init__.py | 27 + src/sagemaker/amtviz/job_metrics.py | 180 +++++ src/sagemaker/amtviz/visualization.py | 857 +++++++++++++++++++++++ src/sagemaker/tuner.py | 66 ++ tests/unit/test_tuner_visualize.py | 307 ++++++++ tests/unit/tuner_visualize_test_utils.py | 159 +++++ tox.ini | 1 + 7 files changed, 1597 insertions(+) create mode 100644 src/sagemaker/amtviz/__init__.py create mode 100644 src/sagemaker/amtviz/job_metrics.py create mode 100644 src/sagemaker/amtviz/visualization.py create mode 100644 tests/unit/test_tuner_visualize.py create mode 100644 tests/unit/tuner_visualize_test_utils.py diff --git a/src/sagemaker/amtviz/__init__.py b/src/sagemaker/amtviz/__init__.py new file mode 100644 index 0000000000..8554b32c4a --- /dev/null +++ b/src/sagemaker/amtviz/__init__.py @@ -0,0 +1,27 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Amazon SageMaker Automatic Model Tuning Visualization module. + +This module provides visualization capabilities for SageMaker hyperparameter tuning jobs. +It enables users to create interactive visualizations to analyze and understand the +performance of hyperparameter optimization experiments. + +Example: + >>> from sagemaker.amtviz import visualize_tuning_job + >>> visualize_tuning_job('my-tuning-job') +""" +from __future__ import absolute_import + +from sagemaker.amtviz.visualization import visualize_tuning_job + +__all__ = ["visualize_tuning_job"] diff --git a/src/sagemaker/amtviz/job_metrics.py b/src/sagemaker/amtviz/job_metrics.py new file mode 100644 index 0000000000..b99886941f --- /dev/null +++ b/src/sagemaker/amtviz/job_metrics.py @@ -0,0 +1,180 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Helper functions to retrieve job metrics from CloudWatch.""" +from __future__ import absolute_import + +from datetime import datetime, timedelta +from typing import Callable, List, Optional, Tuple, Dict, Any +import hashlib +import os +from pathlib import Path + +import logging +import pandas as pd +import numpy as np +import boto3 + +logger = logging.getLogger(__name__) + +cw = boto3.client("cloudwatch") +sm = boto3.client("sagemaker") + + +def disk_cache(outer: Callable) -> Callable: + """A decorator that implements disk-based caching for CloudWatch metrics data. + + This decorator caches the output of the wrapped function to disk in JSON Lines format. + It creates a cache key using MD5 hash of the function arguments and stores the data + in the user's home directory under .amtviz/cw_metrics_cache/. + + Args: + outer (Callable): The function to be wrapped. Must return a pandas DataFrame + containing CloudWatch metrics data. + + Returns: + Callable: A wrapper function that implements the caching logic. + """ + + def inner(*args: Any, **kwargs: Any) -> pd.DataFrame: + key_input = str(args) + str(kwargs) + # nosec b303 - Not used for cryptography, but to create lookup key + key = hashlib.md5(key_input.encode("utf-8")).hexdigest() + cache_dir = Path.home().joinpath(".amtviz/cw_metrics_cache") + fn = f"{cache_dir}/req_{key}.jsonl.gz" + if Path(fn).exists(): + try: + df = pd.read_json(fn, lines=True) + logger.debug("H", end="") + df["ts"] = pd.to_datetime(df["ts"]) + df["ts"] = df["ts"].dt.tz_localize(None) + # pyright: ignore [reportIndexIssue, reportOptionalSubscript] + df["rel_ts"] = pd.to_datetime(df["rel_ts"]) + df["rel_ts"] = df["rel_ts"].dt.tz_localize(None) + return df + except KeyError: + # Empty file leads to empty df, hence no df['ts'] possible + pass + # nosec b110 - doesn't matter why we could not load it. + except BaseException as e: + logger.error("\nException: %s - %s", type(e), e) + + logger.debug("M", end="") + df = outer(*args, **kwargs) + assert isinstance(df, pd.DataFrame), "Only caching Pandas DataFrames." + + os.makedirs(cache_dir, exist_ok=True) + df.to_json(fn, orient="records", date_format="iso", lines=True) + + return df + + return inner + + +def _metric_data_query_tpl(metric_name: str, dim_name: str, dim_value: str) -> Dict[str, Any]: + """Returns a CloudWatch metric data query template.""" + return { + "Id": metric_name.lower().replace(":", "_").replace("-", "_"), + "MetricStat": { + "Stat": "Average", + "Metric": { + "Namespace": "/aws/sagemaker/TrainingJobs", + "MetricName": metric_name, + "Dimensions": [ + {"Name": dim_name, "Value": dim_value}, + ], + }, + "Period": 60, + }, + "ReturnData": True, + } + + +def _get_metric_data( + queries: List[Dict[str, Any]], start_time: datetime, end_time: datetime +) -> pd.DataFrame: + """Fetches CloudWatch metrics between timestamps, returns a DataFrame with selected columns.""" + start_time = start_time - timedelta(hours=1) + end_time = end_time + timedelta(hours=1) + response = cw.get_metric_data(MetricDataQueries=queries, StartTime=start_time, EndTime=end_time) + + df = pd.DataFrame() + if "MetricDataResults" not in response: + return df + + for metric_data in response["MetricDataResults"]: + values = metric_data["Values"] + ts = np.array(metric_data["Timestamps"], dtype=np.datetime64) + labels = [metric_data["Label"]] * len(values) + + df = pd.concat([df, pd.DataFrame({"value": values, "ts": ts, "label": labels})]) + + # We now calculate the relative time based on the first actual observed + # time stamps, not the potentially start time that we used to scope our CW + # API call. The difference could be for example startup times or waiting + # for Spot. + if not df.empty: + df["rel_ts"] = datetime.fromtimestamp(1) + (df["ts"] - df["ts"].min()) # pyright: ignore + return df + + +@disk_cache +def _collect_metrics( + dimensions: List[Tuple[str, str]], start_time: datetime, end_time: Optional[datetime] +) -> pd.DataFrame: + """Collects SageMaker training job metrics from CloudWatch for dimensions and time range.""" + df = pd.DataFrame() + for dim_name, dim_value in dimensions: + response = cw.list_metrics( + Namespace="/aws/sagemaker/TrainingJobs", + Dimensions=[ + {"Name": dim_name, "Value": dim_value}, + ], + ) + if not response["Metrics"]: + continue + metric_names = [metric["MetricName"] for metric in response["Metrics"]] + if not metric_names: + # No metric data yet, or not any longer, because the data were aged out + continue + metric_data_queries = [ + _metric_data_query_tpl(metric_name, dim_name, dim_value) for metric_name in metric_names + ] + df = pd.concat([df, _get_metric_data(metric_data_queries, start_time, end_time)]) + + return df + + +def get_cw_job_metrics( + job_name: str, start_time: Optional[datetime] = None, end_time: Optional[datetime] = None +) -> pd.DataFrame: + """Retrieves CloudWatch metrics for a SageMaker training job. + + Args: + job_name (str): Name of the SageMaker training job. + start_time (datetime, optional): Start time for metrics collection. + Defaults to now - 4 hours. + end_time (datetime, optional): End time for metrics collection. + Defaults to start_time + 4 hours. + + Returns: + pd.DataFrame: Metrics data with columns for value, timestamp, and metric name. + Results are cached to disk for improved performance. + """ + dimensions = [ + ("TrainingJobName", job_name), + ("Host", job_name + "/algo-1"), + ] + # If not given, use reasonable defaults for start and end time + start_time = start_time or datetime.now() - timedelta(hours=4) + end_time = end_time or start_time + timedelta(hours=4) + return _collect_metrics(dimensions, start_time, end_time) diff --git a/src/sagemaker/amtviz/visualization.py b/src/sagemaker/amtviz/visualization.py new file mode 100644 index 0000000000..7f09117d1e --- /dev/null +++ b/src/sagemaker/amtviz/visualization.py @@ -0,0 +1,857 @@ +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""This module provides visualization capabilities for SageMaker hyperparameter tuning jobs. + +It contains utilities to create interactive visualizations of hyperparameter tuning results +using Altair charts. The module enables users to analyze and understand the performance +of their hyperparameter optimization experiments through various visual representations +including: +- Progress of objective metrics over time +- Distribution of results +- Relationship between hyperparameters and objective values +- Training job metrics and instance utilization +- Comparative analysis across multiple tuning jobs + +Main Features: + - Visualize single or multiple hyperparameter tuning jobs + - Display training job metrics from CloudWatch + - Support for both completed and in-progress tuning jobs + - Interactive filtering and highlighting of data points + - CPU, memory, and GPU utilization visualization + - Advanced visualization options for detailed analysis + +Primary Classes and Functions: + - visualize_tuning_job: Main function to create visualizations for tuning jobs + - create_charts: Core chart creation functionality + - get_job_analytics_data: Retrieves and processes tuning job data + +Dependencies: + - altair: For creating interactive visualizations + - pandas: For data manipulation and analysis + - boto3: For AWS service interaction + - sagemaker: For accessing SageMaker resources +""" +from __future__ import absolute_import + +from typing import Union, List, Optional, Tuple +import os +import warnings +import logging +import altair as alt +import pandas as pd +import numpy as np +import boto3 +import sagemaker +from sagemaker.amtviz.job_metrics import get_cw_job_metrics + +warnings.filterwarnings("ignore") +logger = logging.getLogger(__name__) + +pd.set_option("display.max_rows", 500) +pd.set_option("display.max_columns", 500) +pd.set_option("display.width", 1000) +pd.set_option("display.max_colwidth", None) # Don't truncate TrainingJobName + + +alt.data_transformers.disable_max_rows() +altair_renderer = os.getenv("ALTAIR_RENDERER", "default") +logger.info("Setting altair renderer to %s.", altair_renderer) +alt.renderers.enable(altair_renderer) + + +sm = boto3.client("sagemaker") + + +def _columnize(charts: List[alt.Chart], cols: int = 2) -> alt.VConcatChart: + """Arrange charts in columns.""" + return alt.vconcat(*[alt.hconcat(*charts[i : i + cols]) for i in range(0, len(charts), cols)]) + + +def visualize_tuning_job( + tuning_jobs: Union[str, List[str], "sagemaker.tuner.HyperparameterTuner"], + return_dfs: bool = False, + job_metrics: Optional[List[str]] = None, + trials_only: bool = False, + advanced: bool = False, +) -> Union[alt.Chart, Tuple[alt.Chart, pd.DataFrame, pd.DataFrame]]: + """Visualize SageMaker hyperparameter tuning jobs. + + Args: + tuning_jobs: Single tuning job or list of tuning jobs (name or HyperparameterTuner object) + return_dfs: Whether to return the underlying DataFrames + job_metrics: List of additional job metrics to include + trials_only: Whether to only show trials data + advanced: Whether to show advanced visualizations + + Returns: + If return_dfs is False, returns Altair chart + If return_dfs is True, returns tuple of (chart, trials_df, full_df) + """ + + trials_df, tuned_parameters, objective_name, is_minimize = get_job_analytics_data(tuning_jobs) + + try: + from IPython import get_ipython, display + + if get_ipython(): + # Running in a Jupyter Notebook + display(trials_df.head(10)) + else: + # Running in a non-Jupyter environment + logger.info(trials_df.head(10).to_string()) + except ImportError: + # Not running in a Jupyter Notebook + logger.info(trials_df.head(10).to_string()) + + full_df = _prepare_consolidated_df(trials_df) if not trials_only else pd.DataFrame() + + trials_df.columns = trials_df.columns.map(_clean_parameter_name) + full_df.columns = full_df.columns.map(_clean_parameter_name) + tuned_parameters = [_clean_parameter_name(tp) for tp in tuned_parameters] + objective_name = _clean_parameter_name(objective_name) + + charts = create_charts( + trials_df, + tuned_parameters, + full_df, + objective_name, + minimize_objective=is_minimize, + job_metrics=job_metrics, + advanced=advanced, + ) + + if return_dfs: + return charts, trials_df, full_df + return charts + + +def create_charts( + trials_df: pd.DataFrame, + tuning_parameters: List[str], + full_df: pd.DataFrame, + objective_name: str, + minimize_objective: bool, + job_metrics: Optional[List[str]] = None, + highlight_trials: bool = True, + color_trials: bool = False, + advanced: bool = False, +) -> alt.Chart: + """Create visualization charts for hyperparameter tuning results. + + Args: + trials_df: DataFrame containing trials data + tuning_parameters: List of hyperparameter names + full_df: DataFrame with consolidated data + objective_name: Name of the objective metric + minimize_objective: Whether objective should be minimized + job_metrics: Additional job metrics to include + highlight_trials: Whether to highlight selected trials + color_trials: Whether to color trials by job + advanced: Whether to show advanced visualizations + + Returns: + Altair chart visualization + """ + + if trials_df.empty: + logger.info("No results available yet.") + return pd.DataFrame() + + if job_metrics is None: + job_metrics = [] + + multiple_tuning_jobs = len(trials_df["TuningJobName"].unique()) > 1 + multiple_job_status = len(trials_df["TrainingJobStatus"].unique()) > 1 + + # Rows, n>1 + # Detail Charts + + brush = alt.selection_interval(encodings=["x"], resolve="intersect", empty=True) + + job_highlight_selection = alt.selection_point( + on="mouseover", + nearest=False, + empty=False, + fields=["TrainingJobName", "TrainingStartTime"], + ) + + # create tooltip + detail_tooltip = [] + for trp in [objective_name] + tuning_parameters: + if trials_df[trp].dtype == np.float64: + trp = alt.Tooltip(trp, format=".2e") + detail_tooltip.append(trp) + + detail_tooltip.append(alt.Tooltip("TrainingStartTime:T", format="%H:%M:%S")) + detail_tooltip.extend(["TrainingJobName", "TrainingJobStatus", "TrainingElapsedTimeSeconds"]) + + # create stroke/stroke-width for tuning_jobs + # and color for training jobs, if wanted + # add coloring of the stroke to highlight correlated + # data points + jobs_props = {"shape": alt.Shape("TrainingJobStatus:N", legend=None)} + + if multiple_tuning_jobs: + jobs_props["strokeWidth"] = alt.StrokeWidthValue(2.0) + jobs_props["stroke"] = alt.Stroke("TuningJobName:N", legend=None) + + if color_trials: + jobs_props["color"] = alt.Color("TrainingJobName:N") + + if highlight_trials: + jobs_props["strokeWidth"] = alt.condition( + job_highlight_selection, + alt.StrokeWidthValue(2.0), + alt.StrokeWidthValue(2.0), + ) + jobs_props["stroke"] = alt.condition( + job_highlight_selection, + alt.StrokeValue("gold"), + ( + alt.Stroke("TuningJobName:N", legend=None) + if multiple_tuning_jobs + else alt.StrokeValue("white") + ), + ) + + opacity = alt.condition(brush, alt.value(1.0), alt.value(0.35)) + charts = [] + + # Min and max of the objective. This is used in filtered + # charts, so that the filtering does not make the axis + # jump, which would make comparisons harder. + objective_scale = alt.Scale( + domain=( + trials_df[objective_name].min(), + trials_df[objective_name].max(), + ) + ) + + # If we have multiple tuning jobs, we also want to be able + # to discriminate based on the individual tuning job, so + # we just treat them as an additional tuning parameter + tuning_job_param = ["TuningJobName"] if multiple_tuning_jobs else [] + tuning_parameters = tuning_parameters.copy() + tuning_job_param + + # If we use early stopping and at least some jobs were + # stopped early, we want to be able to discriminate + # those jobs. + if multiple_job_status: + tuning_parameters.append("TrainingJobStatus") + + def render_detail_charts(): + # To force a tuning job to sample a combination more than once, we + # sometimes introduce a hyperparameter that has no effect. + # It's values are random and without impact, so we omit it from analysis. + ignored_parameters = {"dummy"} + for tuning_parameter in tuning_parameters: + if tuning_parameter in ignored_parameters: + continue + + # Map dataframe's dtype to altair's types and + # adjust scale if necessary + scale_type = "linear" + scale_log_base = 10 + + few_values = len(trials_df[tuning_parameter].unique()) < 8 + parameter_type = "N" # Nominal + dtype = str(trials_df.dtypes[tuning_parameter]) + if "float" in dtype: + parameter_type = "Q" # Quantitative + ratio = (trials_df[tuning_parameter].max() + 1e-10) / ( + trials_df[tuning_parameter].min() + 1e-10 + ) + not_likely_discrete = ( + len(trials_df[tuning_parameter].unique()) > trials_df[tuning_parameter].count() + ) # edge case when both are equal + if few_values and not_likely_discrete: + if ratio > 50: + scale_type = "log" + elif ratio > 10: + scale_type = "log" + scale_log_base = 2 + + elif "int" in dtype or "object" in dtype: + parameter_type = "O" # Ordinal + + x_encoding = alt.X( + f"{tuning_parameter}:{parameter_type}", + scale=alt.Scale( + zero=False, + padding=1, + type=scale_type, + base=scale_log_base, + ), + ) + + # Sync the coloring for categorical hyperparameters + discrete = parameter_type in ["O", "N"] and few_values + + # Detail Chart + charts.append( + alt.Chart(trials_df) + .add_params(brush) + .add_params(job_highlight_selection) + .mark_point(filled=True, size=50) + .encode( + x=x_encoding, + y=alt.Y( + f"{objective_name}:Q", + scale=alt.Scale(zero=False, padding=1), + axis=alt.Axis(title=objective_name), + ), + opacity=opacity, + tooltip=detail_tooltip, + **jobs_props, + ) + ) + + if discrete: + # Individually coloring the values only if we don't already + # use the colors to show the different tuning jobs + logger.info("%s, %s", parameter_type, tuning_parameter) + if not multiple_tuning_jobs: + charts[-1] = charts[-1].encode(color=f"{tuning_parameter}:N") + charts[-1] = ( + ( + charts[-1] + | alt.Chart(trials_df) + .transform_filter(brush) + .transform_density( + objective_name, + bandwidth=0.01, + groupby=[tuning_parameter], + # https://github.com/vega/altair/issues/3203#issuecomment-2141558911 + # Specifying extent no longer necessary (>5.1.2). + extent=[ + trials_df[objective_name].min(), + trials_df[objective_name].max(), + ], + ) + .mark_area(opacity=0.5) + .encode( + x=alt.X( + "value:Q", + title=objective_name, + scale=objective_scale, + ), + y="density:Q", + color=alt.Color( + f"{tuning_parameter}:N", + ), + tooltip=tuning_parameter, + ) + ).properties(title=tuning_parameter) + # .resolve_scale("independent") + # .resolve_legend(color="independent") + ) + + if advanced and parameter_type == "Q": + # Adding tick marks to the detail charts with quantitative hyperparameters + x_enc = x_encoding.copy() + charts[-1].encoding.x.title = None + charts[-1].encoding.x.axis = alt.Axis(labels=False) + + charts[-1] = charts[-1] & alt.Chart(trials_df).mark_tick(opacity=0.5).encode( + x=x_enc, + opacity=alt.condition(brush, alt.value(0.5), alt.value(0.1)), + ) + + return _columnize(charts) + + detail_charts = render_detail_charts() + + # First Row + # Progress Over Time Chart + + def render_progress_chart(): + # Sorting trials by training start time, so that we can track the \ + # progress of the best objective so far over time + trials_df_by_tst = trials_df.sort_values(["TuningJobName", "TrainingStartTime"]) + trials_df_by_tst["cum_objective"] = trials_df_by_tst.groupby(["TuningJobName"]).transform( + lambda x: x.cummin() if minimize_objective else x.cummax() + )[objective_name] + + progress_chart = ( + alt.Chart(trials_df_by_tst) + .add_params(brush) + .add_params(job_highlight_selection) + .mark_point(filled=True, size=50) + .encode( + x=alt.X("TrainingStartTime:T", scale=alt.Scale(nice=True)), + y=alt.Y( + f"{objective_name}:Q", + scale=alt.Scale(zero=False, padding=1), + axis=alt.Axis(title=objective_name), + ), + opacity=opacity, + tooltip=detail_tooltip, + **jobs_props, + ) + ) + + cum_obj_chart = ( + alt.Chart(trials_df_by_tst) + .mark_line( + interpolate="step-after", + opacity=1.0, + strokeDash=[3, 3], + strokeWidth=2.0, + ) + .encode( + x=alt.X("TrainingStartTime:T", scale=alt.Scale(nice=True)), + y=alt.Y("cum_objective:Q", scale=alt.Scale(zero=False, padding=1)), + stroke=alt.Stroke("TuningJobName:N", legend=None), + ) + ) + + if advanced: + return cum_obj_chart + progress_chart + return progress_chart + + progress_chart = render_progress_chart() + + # First Row + # KDE Training Objective + result_hist_chart = ( + alt.Chart(trials_df) + .transform_filter(brush) + .transform_density(objective_name, bandwidth=0.01) + .mark_area() + .encode( + x=alt.X("value:Q", scale=objective_scale, title=objective_name), + y="density:Q", + ) + ) + # Training Jobs + training_jobs_chart = ( + alt.Chart(trials_df.sort_values(objective_name), title="Training Jobs") + .mark_bar() + .add_params(brush) + .add_params(job_highlight_selection) + .encode( + y=alt.Y(f"{objective_name}:Q"), + x=alt.X("TrainingJobName:N", sort=None), + color=alt.Color("TrainingJobName:N"), + opacity=opacity, + **jobs_props, + ) + ) + + # Job Level Stats + + training_job_name_encodings = { + "color": alt.condition( + brush, + alt.Color("TrainingJobName:N", legend=None), + alt.value("grey"), + ), + "opacity": alt.condition(brush, alt.value(1.0), alt.value(0.3)), + "strokeWidth": alt.condition(brush, alt.value(2.5), alt.value(0.8)), + } + + duration_format = "%M:%S" + metrics_tooltip = [ + "TrainingJobName:N", + "value:Q", + "label:N", + alt.Tooltip("ts:T", format="%e:%H:%M"), + alt.Tooltip("rel_ts:T", format="%e:%H:%M"), + ] + + job_level_rows = alt.HConcatChart() + + # Use CW metrics + if not full_df.empty: + # Objective Progression + + objective_progression_chart = None + # Suppress diagram if we only have one, final, value + if ( + full_df.loc[full_df.label == objective_name] + .groupby(["TuningJobName", "TrainingJobName"])[objective_name] + .count() + .max() + > 1 + ): + objective_progression_chart = ( + alt.Chart(full_df, title=f"Progression {objective_name}", width=400) + .transform_filter(alt.FieldEqualPredicate(field="label", equal=objective_name)) + .mark_line(point=True) + .encode( + x=alt.X("rel_ts:T", axis=alt.Axis(format=duration_format)), + y=alt.Y("value:Q", scale=alt.Scale(zero=False)), + **training_job_name_encodings, + tooltip=metrics_tooltip, + ) + .interactive() + ) + + if multiple_job_status: + objective_progression_chart = objective_progression_chart.encode( + strokeDash=alt.StrokeDash("TrainingJobStatus:N", legend=None) + ) + + # Secondary chart showing the same contents, but by absolute time. + objective_progression_absolute_chart = objective_progression_chart.encode( + x=alt.X("ts:T", scale=alt.Scale(nice=True)) + ) + + objective_progression_chart = ( + objective_progression_chart | objective_progression_absolute_chart + ) + + ### + + job_metrics_charts = [] + for metric in job_metrics: + metric_chart = ( + alt.Chart(full_df, title=metric, width=400) + .transform_filter(alt.FieldEqualPredicate(field="label", equal=metric)) + .encode( + y=alt.Y("value:Q", scale=alt.Scale(zero=False)), + **training_job_name_encodings, + tooltip=metrics_tooltip, + ) + .interactive() + ) + + if ( + full_df.loc[full_df.label == metric] + .groupby(["TuningJobName", "TrainingJobName"]) + .count() + .value.max() + == 1 + ): + # single value, render as a bar over the training jobs on the x-axis + metric_chart = metric_chart.encode( + x=alt.X("TrainingJobName:N", sort=None) + ).mark_bar(interpolate="linear", point=True) + else: + # multiple values, render the values over time on the x-axis + metric_chart = metric_chart.encode( + x=alt.X("rel_ts:T", axis=alt.Axis(format=duration_format)) + ).mark_line(interpolate="linear", point=True) + + job_metrics_charts.append(metric_chart) + + job_metrics_chart = _columnize(job_metrics_charts, 3) + + # Job instance + # 'MemoryUtilization', 'CPUUtilization' + instance_metrics_chart = ( + alt.Chart(full_df, title="CPU and Memory") + .transform_filter( + alt.FieldOneOfPredicate( + field="label", + oneOf=[ + "MemoryUtilization", + "CPUUtilization", + ], + ) + ) + .mark_line() + .encode( + x=alt.X("rel_ts:T", axis=alt.Axis(format=duration_format)), + y="value:Q", + **training_job_name_encodings, + strokeDash=alt.StrokeDash("label:N", legend=alt.Legend(orient="bottom")), + tooltip=metrics_tooltip, + ) + .interactive() + ) + + if "GPUUtilization" in full_df.label.values: + instance_metrics_chart = ( + instance_metrics_chart + | alt.Chart(full_df, title="GPU and GPU Memory") + .transform_filter( + alt.FieldOneOfPredicate( + field="label", + oneOf=[ + "GPUMemoryUtilization", + "GPUUtilization", + ], + ) + ) + .mark_line() + .encode( + x=alt.X("rel_ts:T", axis=alt.Axis(format=duration_format)), + y=alt.Y("value:Q"), + **training_job_name_encodings, + strokeDash=alt.StrokeDash("label:N", legend=alt.Legend(orient="bottom")), + tooltip=metrics_tooltip, + ) + .interactive() + ) + + job_level_rows = job_metrics_chart & instance_metrics_chart + if objective_progression_chart: + job_level_rows = objective_progression_chart & job_level_rows + job_level_rows = job_level_rows.resolve_scale(strokeDash="independent").properties( + title="Job / Instance Level Metrics" + ) + + overview_row = (progress_chart | result_hist_chart).properties( + title="Hyper Parameter Tuning Job" + ) + detail_rows = detail_charts.properties(title="Hyper Parameter Details") + if job_level_rows: + job_level_rows = training_jobs_chart & job_level_rows + + return overview_row & detail_rows & job_level_rows + + +def _clean_parameter_name(s): + """Helper method to ensure proper parameter name characters for altair 5+""" + return s.replace(":", "_").replace(".", "_") + + +def _prepare_training_job_metrics(jobs): + """Fetches and combines CloudWatch metrics for multiple training jobs. + + Args: + jobs (list): List of (job_name, start_time, end_time) tuples. + + Returns: + pandas.DataFrame: Combined metrics DataFrame with 'TrainingJobName' column. + """ + df = pd.DataFrame() + for job_name, start_time, end_time in jobs: + job_df = get_cw_job_metrics( + job_name, + start_time=pd.Timestamp(start_time) - pd.DateOffset(hours=8), + end_time=pd.Timestamp(end_time) + pd.DateOffset(hours=8), + ) + if job_df is None: + logger.info("No CloudWatch metrics for %s. Skipping.", job_name) + continue + + job_df["TrainingJobName"] = job_name + df = pd.concat([df, job_df]) + return df + + +def _prepare_consolidated_df(trials_df): + """Merges training job metrics with trials data into a consolidated DataFrame.""" + if trials_df.empty: + return pd.DataFrame() + + logger.debug("Cache Hit/Miss: ", end="") + jobs_df = _prepare_training_job_metrics( + zip( + trials_df.TrainingJobName.values, + trials_df.TrainingStartTime.values, + trials_df.TrainingEndTime.values, + ) + ) + logger.info("") + + if jobs_df.empty: + return pd.DataFrame() + + merged_df = pd.merge(jobs_df, trials_df, on="TrainingJobName") + return merged_df + + +def _get_df(tuning_job_name, filter_out_stopped=False): + """Retrieves hyperparameter tuning job results and returns preprocessed DataFrame. + + Returns a DataFrame containing tuning metrics and parameters for the specified job. + """ + + tuner = sagemaker.HyperparameterTuningJobAnalytics(tuning_job_name) + + df = tuner.dataframe() + if df.empty: # HPO job just started; no results yet + return df + + df["TuningJobName"] = tuning_job_name + + # Filter out jobs without FinalObjectiveValue + df = df[df["FinalObjectiveValue"] > -float("inf")] + + # Jobs early stopped by AMT are reported with their last + # objective value, before they are stopped. + # However this value may not be a good representation + # of the eventual objective value we would have seen + # if run without stopping. Therefore it may be confusing + # to include those runs. + # For now, if included, we use a different mark to + # discriminate visually between a stopped and finished job + + if filter_out_stopped: + df = df[df["TrainingJobStatus"] != "Stopped"] + + # Preprocessing values for [32], [64] etc. + for tuning_range in tuner.tuning_ranges.values(): + parameter_name = tuning_range["Name"] + if df.dtypes[parameter_name] == "O": + try: + # Remove decorations, like [] + df[parameter_name] = df[parameter_name].apply( + lambda v: v.replace("[", "").replace("]", "").replace('"', "") + ) + + # Is it an int? 3 would work, 3.4 would fail. + try: + df[parameter_name] = df[parameter_name].astype(int) + except ValueError: + # A float then? + df[parameter_name] = df[parameter_name].astype(float) + + except (ValueError, TypeError, AttributeError): + # Catch exceptions that might occur during string manipulation or type conversion + # - ValueError: Could not convert string to float/int + # - TypeError: Object doesn't support the operation + # - AttributeError: Object doesn't have replace method + # Leaving the value untouched + pass + + return df + + +def _get_tuning_job_names_with_parents(tuning_job_names): + """Resolve dependent jobs, one level only""" + + all_tuning_job_names = [] + for tuning_job_name in tuning_job_names: + tuning_job_result = sm.describe_hyper_parameter_tuning_job( + HyperParameterTuningJobName=tuning_job_name + ) + + # find parent jobs and retrieve all tuner dataframes + parent_jobs = [] + if "WarmStartConfig" in tuning_job_result: + parent_jobs = [ + cfg["HyperParameterTuningJobName"] + for cfg in tuning_job_result["WarmStartConfig"]["ParentHyperParameterTuningJobs"] + ] + if parent_jobs: + logger.info("Tuning job %s's parents: %s", tuning_job_name, ", ".join(parent_jobs)) + all_tuning_job_names.extend([tuning_job_name, *parent_jobs]) + + # return de-duplicated tuning job names + return list(set(all_tuning_job_names)) + + +def get_job_analytics_data(tuning_job_names): + """Retrieves and processes analytics data from hyperparameter tuning jobs. + + Args: + tuning_job_names (str or list): Single tuning job name or list of names/tuner objects. + + Returns: + tuple: (DataFrame with training results, tuned params list, objective name, is_minimize). + + Raises: + ValueError: If tuning jobs have different objectives or optimization directions. + """ + if not isinstance(tuning_job_names, list): + tuning_job_names = [tuning_job_names] + + # Ensure to create a list of tuning job names (strings) + tuning_job_names = [ + ( + tuning_job.describe()["HyperParameterTuningJobName"] + if isinstance(tuning_job, sagemaker.tuner.HyperparameterTuner) + else tuning_job + ) + for tuning_job in tuning_job_names + ] + + # Maintain combined tuner dataframe from all tuning jobs + df = pd.DataFrame() + + # maintain objective, direction of optimization and tuned parameters + objective_name = None + is_minimize = None + tuned_parameters = None + + all_tuning_job_names = _get_tuning_job_names_with_parents(tuning_job_names) + + for tuning_job_name in all_tuning_job_names: + tuning_job_result = sm.describe_hyper_parameter_tuning_job( + HyperParameterTuningJobName=tuning_job_name + ) + status = tuning_job_result["HyperParameterTuningJobStatus"] + logger.info("Tuning job %-25s status: %s", tuning_job_name, status) + + df = pd.concat([df, _get_df(tuning_job_name)]) + + # maintain objective and assure that all tuning jobs use the same + job_is_minimize = ( + tuning_job_result["HyperParameterTuningJobConfig"]["HyperParameterTuningJobObjective"][ + "Type" + ] + != "Maximize" + ) + job_objective_name = tuning_job_result["HyperParameterTuningJobConfig"][ + "HyperParameterTuningJobObjective" + ]["MetricName"] + job_tuned_parameters = [ + v["Name"] + for v in sagemaker.HyperparameterTuningJobAnalytics( + tuning_job_name + ).tuning_ranges.values() + ] + + if not objective_name: + objective_name = job_objective_name + is_minimize = job_is_minimize + tuned_parameters = job_tuned_parameters + else: + if ( + objective_name != job_objective_name + or is_minimize != job_is_minimize + or set(tuned_parameters) != set(job_tuned_parameters) + ): + raise ValueError( + "All tuning jobs must use the same objective and optimization direction." + ) + + if not df.empty: + # Cleanup wrongly encoded floats, e.g. containing quotes. + for i, dtype in enumerate(df.dtypes): + column_name = str(df.columns[i]) + if column_name in [ + "TrainingJobName", + "TrainingJobStatus", + "TuningJobName", + ]: + continue + if dtype == "object": + val = df[column_name].iloc[0] + if isinstance(val, str) and val.startswith('"'): + try: + df[column_name] = df[column_name].apply(lambda x: int(x.replace('"', ""))) + except (ValueError, TypeError, AttributeError): + # noqa: E722 nosec b110 if we fail, we just continue with what we had + pass # Value is not an int, but a string + + df = df.sort_values("FinalObjectiveValue", ascending=is_minimize) + df[objective_name] = df.pop("FinalObjectiveValue") + + # Fix potential issue with dates represented as objects, instead of a timestamp + # This can in other cases lead to: + # https://www.markhneedham.com/blog/2020/01/10/altair-typeerror-object-type- + # date-not-json-serializable/ + # Seen this for TrainingEndTime, but will watch TrainingStartTime as well now. + df["TrainingEndTime"] = pd.to_datetime(df["TrainingEndTime"]) + df["TrainingStartTime"] = pd.to_datetime(df["TrainingStartTime"]) + + logger.info("") + logger.info("Number of training jobs with valid objective: %d", len(df)) + logger.info("Lowest: %s Highest %s", min(df[objective_name]), max(df[objective_name])) + + tuned_parameters = [_clean_parameter_name(tp) for tp in tuned_parameters] + + return df, tuned_parameters, objective_name, is_minimize diff --git a/src/sagemaker/tuner.py b/src/sagemaker/tuner.py index fa8f9b8555..d9b052770b 100644 --- a/src/sagemaker/tuner.py +++ b/src/sagemaker/tuner.py @@ -2117,6 +2117,72 @@ def _add_estimator( delete_endpoint = removed_function("delete_endpoint") + @staticmethod + def visualize_jobs( + tuning_jobs: Union[ + str, + "sagemaker.tuner.HyperparameterTuner", + List[Union[str, "sagemaker.tuner.HyperparameterTuner"]], + ], + return_dfs: bool = False, + job_metrics: Optional[List[str]] = None, + trials_only: bool = False, + advanced: bool = False, + ): + """Create interactive visualization via altair charts using the sagemaker.amtviz package. + + Args: + tuning_jobs (str or sagemaker.tuner.HyperparameterTuner or list[str, sagemaker.tuner.HyperparameterTuner]): + One or more tuning jobs to create + visualization for. + return_dfs: (bool): Option to return trials and full dataframe. + job_metrics: (list[str]): Metrics to be used in charts. + trials_only: (bool): Whether to show trials only or full dataframe. + advanced: (bool): Show a cumulative step line in the progress over time chart. + Returns: + A collection of charts (altair.VConcatChart); or charts, trials_df (pandas.DataFrame), + full_df (pandas.DataFrame) if ``return_dfs=True``. + """ + try: + # Check if altair is installed + importlib.import_module("altair") + + except ImportError: + print("Altair is not installed. Install Altair to use the visualization feature:") + print(" pip install altair") + print("After installing Altair, use the methods visualize_jobs or visualize_job.") + return None + + # If altair is installed, proceed with visualization + from sagemaker.amtviz import visualize_tuning_job + + return visualize_tuning_job( + tuning_jobs, + return_dfs=return_dfs, + job_metrics=job_metrics, + trials_only=trials_only, + advanced=advanced, + ) + + def visualize_job( + self, + return_dfs: bool = False, + job_metrics: Optional[List[str]] = None, + trials_only: bool = False, + advanced: bool = False, + ): + """Convenience method on instance level for visualize_jobs(). + + See static method visualize_jobs(). + """ + return HyperparameterTuner.visualize_jobs( + self, + return_dfs=return_dfs, + job_metrics=job_metrics, + trials_only=trials_only, + advanced=advanced, + ) + class _TuningJob(_Job): """Placeholder docstring""" diff --git a/tests/unit/test_tuner_visualize.py b/tests/unit/test_tuner_visualize.py new file mode 100644 index 0000000000..8397ae8e25 --- /dev/null +++ b/tests/unit/test_tuner_visualize.py @@ -0,0 +1,307 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Tests related to amtviz.visualization""" +from __future__ import absolute_import + +import pandas as pd +import pytest +from mock import Mock, patch, MagicMock +import sagemaker +from sagemaker.estimator import Estimator +from sagemaker.session_settings import SessionSettings +from sagemaker.tuner import HyperparameterTuner +from tests.unit.tuner_test_utils import ( + OBJECTIVE_METRIC_NAME, + HYPERPARAMETER_RANGES, + METRIC_DEFINITIONS, +) + +# Visualization specific imports +from sagemaker.amtviz.visualization import visualize_tuning_job, get_job_analytics_data +from tests.unit.tuner_visualize_test_utils import ( + TUNING_JOB_NAMES, + TUNED_PARAMETERS, + OBJECTIVE_NAME, + TRIALS_DF_DATA, + FULL_DF_DATA, + TUNING_JOB_NAME_1, + TUNING_JOB_NAME_2, + TUNING_JOB_RESULT, + TRIALS_DF_COLUMNS, + FULL_DF_COLUMNS, + TRIALS_DF_TRAINING_JOB_NAMES, + TRIALS_DF_TRAINING_JOB_STATUSES, + TRIALS_DF_VALID_F1_VALUES, + FILTERED_TUNING_JOB_DF_DATA, + TUNING_RANGES, +) +import altair as alt + + +def create_sagemaker_session(): + boto_mock = Mock(name="boto_session") + sms = Mock( + name="sagemaker_session", + boto_session=boto_mock, + config=None, + local_mode=False, + settings=SessionSettings(), + ) + sms.sagemaker_config = {} + return sms + + +@pytest.fixture() +def sagemaker_session(): + return create_sagemaker_session() + + +@pytest.fixture() +def estimator(sagemaker_session): + return Estimator( + "image", + "role", + 1, + "ml.c4.xlarge", + output_path="s3://bucket/prefix", + sagemaker_session=sagemaker_session, + ) + + +@pytest.fixture() +def tuner(estimator): + return HyperparameterTuner( + estimator, OBJECTIVE_METRIC_NAME, HYPERPARAMETER_RANGES, METRIC_DEFINITIONS + ) + + +@pytest.fixture() +def tuner2(estimator): + return HyperparameterTuner( + estimator, OBJECTIVE_METRIC_NAME, HYPERPARAMETER_RANGES, METRIC_DEFINITIONS + ) + + +@pytest.fixture +def mock_visualize_tuning_job(): + with patch("sagemaker.amtviz.visualize_tuning_job") as mock_visualize: + mock_visualize.return_value = "mock_chart" + yield mock_visualize + + +@pytest.fixture +def mock_get_job_analytics_data(): + with patch("sagemaker.amtviz.visualization.get_job_analytics_data") as mock: + mock.return_value = (pd.DataFrame(TRIALS_DF_DATA), TUNED_PARAMETERS, OBJECTIVE_NAME, True) + yield mock + + +@pytest.fixture +def mock_prepare_consolidated_df(): + with patch("sagemaker.amtviz.visualization._prepare_consolidated_df") as mock: + mock.return_value = pd.DataFrame(FULL_DF_DATA) + yield mock + + +# Test graceful handling if the required altair library is not installed +def test_visualize_jobs_altair_not_installed(capsys): + # Mock importlib.import_module to raise ImportError for 'altair' + with patch("importlib.import_module") as mock_import: + mock_import.side_effect = ImportError("No module named 'altair'") + result = HyperparameterTuner.visualize_jobs(TUNING_JOB_NAMES) + assert result is None + captured = capsys.readouterr() + assert "Altair is not installed." in captured.out + assert "pip install altair" in captured.out + + +# Test basic method call if altair is installed +def test_visualize_jobs_altair_installed(mock_visualize_tuning_job): + # Mock successful import of altair + with patch("importlib.import_module"): + result = HyperparameterTuner.visualize_jobs(TUNING_JOB_NAMES) + assert result == "mock_chart" + + +# Test for static method visualize_jobs() +def test_visualize_jobs(mock_visualize_tuning_job): + result = HyperparameterTuner.visualize_jobs(TUNING_JOB_NAMES) + assert result == "mock_chart" + mock_visualize_tuning_job.assert_called_once_with( + TUNING_JOB_NAMES, return_dfs=False, job_metrics=None, trials_only=False, advanced=False + ) + # Vary the parameters and check if they have been passed correctly + result = HyperparameterTuner.visualize_jobs( + [TUNING_JOB_NAME_1], + return_dfs=True, + job_metrics="job_metrics", + trials_only=True, + advanced=True, + ) + mock_visualize_tuning_job.assert_called_with( + [TUNING_JOB_NAME_1], + return_dfs=True, + job_metrics="job_metrics", + trials_only=True, + advanced=True, + ) + + +# Test the instance method visualize_job() on a stubbed tuner object +def test_visualize_job(tuner, mock_visualize_tuning_job): + # With default parameters + result = tuner.visualize_job() + assert result == "mock_chart" + mock_visualize_tuning_job.assert_called_once_with( + tuner, return_dfs=False, job_metrics=None, trials_only=False, advanced=False + ) + # With varying parameters + result = tuner.visualize_job( + return_dfs=True, job_metrics="job_metrics", trials_only=True, advanced=True + ) + assert result == "mock_chart" + mock_visualize_tuning_job.assert_called_with( + tuner, return_dfs=True, job_metrics="job_metrics", trials_only=True, advanced=True + ) + + +# Test the static method visualize_jobs() on multiple stubbed tuner objects +def test_visualize_multiple_jobs(tuner, tuner2, mock_visualize_tuning_job): + result = HyperparameterTuner.visualize_jobs([tuner, tuner2]) + assert result == "mock_chart" + mock_visualize_tuning_job.assert_called_once_with( + [tuner, tuner2], return_dfs=False, job_metrics=None, trials_only=False, advanced=False + ) + # Vary the parameters and check if they have been passed correctly + result = HyperparameterTuner.visualize_jobs( + [[tuner, tuner2]], + return_dfs=True, + job_metrics="job_metrics", + trials_only=True, + advanced=True, + ) + mock_visualize_tuning_job.assert_called_with( + [[tuner, tuner2]], + return_dfs=True, + job_metrics="job_metrics", + trials_only=True, + advanced=True, + ) + + +# Test direct method call for basic chart return type and default render settings +def test_visualize_tuning_job_analytics_data_results_in_altair_chart(mock_get_job_analytics_data): + result = visualize_tuning_job("mock_job") + assert alt.renderers.active == "default" + assert isinstance(result, alt.VConcatChart) + + +# Test the size and structure of the returned dataframes (trials_df and full_df) +def test_visualize_tuning_job_return_dfs(mock_get_job_analytics_data, mock_prepare_consolidated_df): + charts, trials_df, full_df = visualize_tuning_job("mock_job", return_dfs=True) + # Basic assertion for the charts + assert isinstance(charts, alt.VConcatChart) + + # Assertions for trials_df + assert isinstance(trials_df, pd.DataFrame) + assert trials_df.shape == (2, len(TRIALS_DF_COLUMNS)) + assert trials_df.columns.tolist() == TRIALS_DF_COLUMNS + assert trials_df["TrainingJobName"].tolist() == TRIALS_DF_TRAINING_JOB_NAMES + assert trials_df["TrainingJobStatus"].tolist() == TRIALS_DF_TRAINING_JOB_STATUSES + assert trials_df["TuningJobName"].tolist() == TUNING_JOB_NAMES + assert trials_df["valid-f1"].tolist() == TRIALS_DF_VALID_F1_VALUES + + # Assertions for full_df + assert isinstance(full_df, pd.DataFrame) + assert full_df.shape == (2, 16) + assert full_df.columns.tolist() == FULL_DF_COLUMNS + + +# Test the handling of an an empty trials dataframe +@patch("sagemaker.amtviz.visualization.get_job_analytics_data") +def test_visualize_tuning_job_empty_trials(mock_get_job_analytics_data): + mock_get_job_analytics_data.return_value = ( + pd.DataFrame(), # empty dataframe + TUNED_PARAMETERS, + OBJECTIVE_NAME, + True, + ) + charts = visualize_tuning_job("empty_job") + assert charts.empty + + +# Test handling of return_dfs and trials_only parameter +def test_visualize_tuning_job_trials_only(mock_get_job_analytics_data): + # If return_dfs is set to False, then only charts should be returned + result = visualize_tuning_job("mock_job", return_dfs=False, trials_only=True) + assert isinstance(result, alt.VConcatChart) + # Trials_only controls the content of the two returned dataframes (trials_df, full_df) + result, df1, df2 = visualize_tuning_job("mock_job", return_dfs=True, trials_only=True) + assert isinstance(df1, pd.DataFrame) + assert df1.shape == (2, len(TRIALS_DF_COLUMNS)) + assert isinstance(df2, pd.DataFrame) + assert df2.empty + # The combination of return_dfs and trials_only=False is covered in 'test_visualize_tuning_job_return_dfs' + + +# Check if all parameters are correctly passed to the (mocked) create_charts method +@patch("sagemaker.amtviz.visualization.create_charts") +def test_visualize_tuning_job_with_full_df( + mock_create_charts, mock_get_job_analytics_data, mock_prepare_consolidated_df +): + mock_create_charts.return_value = alt.Chart() + visualize_tuning_job("dummy_job") + + # Check the create_charts call arguments + call_args = mock_create_charts.call_args[0] + call_kwargs = mock_create_charts.call_args[1] + assert isinstance(call_args[0], pd.DataFrame) # trials_df + assert isinstance(call_args[1], list) # tuned_parameters + assert isinstance(call_args[2], pd.DataFrame) # full_df + assert isinstance(call_args[3], str) # objective_name + assert call_kwargs.get("minimize_objective") + + # Check the details of the passed arguments + trials_df = call_args[0] + assert trials_df.columns.tolist() == TRIALS_DF_COLUMNS + tuned_parameters = call_args[1] + assert tuned_parameters == TUNED_PARAMETERS + objective_name = call_args[3] + assert objective_name == OBJECTIVE_NAME + full_df = call_args[2] + assert full_df.columns.tolist() == FULL_DF_COLUMNS + + +# Test the dataframe produced by get_job_analytics_data() +@patch("sagemaker.HyperparameterTuningJobAnalytics") +def test_get_job_analytics_data(mock_hyperparameter_tuning_job_analytics): + # Mock sagemaker's describe_hyper_parameter_tuning_job and some internal methods + sagemaker.amtviz.visualization.sm.describe_hyper_parameter_tuning_job = Mock( + return_value=TUNING_JOB_RESULT + ) + sagemaker.amtviz.visualization._get_tuning_job_names_with_parents = Mock( + return_value=[TUNING_JOB_NAME_1, TUNING_JOB_NAME_2] + ) + sagemaker.amtviz.visualization._get_df = Mock( + return_value=pd.DataFrame(FILTERED_TUNING_JOB_DF_DATA) + ) + mock_tuning_job_instance = MagicMock() + mock_hyperparameter_tuning_job_analytics.return_value = mock_tuning_job_instance + mock_tuning_job_instance.tuning_ranges.values.return_value = TUNING_RANGES + + df, tuned_parameters, objective_name, is_minimize = get_job_analytics_data([TUNING_JOB_NAME_1]) + assert df.shape == (4, 12) + assert df.columns.tolist() == TRIALS_DF_COLUMNS + assert tuned_parameters == TUNED_PARAMETERS + assert objective_name == OBJECTIVE_NAME + assert is_minimize is False diff --git a/tests/unit/tuner_visualize_test_utils.py b/tests/unit/tuner_visualize_test_utils.py new file mode 100644 index 0000000000..d9524ff7e6 --- /dev/null +++ b/tests/unit/tuner_visualize_test_utils.py @@ -0,0 +1,159 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +TRIALS_DF_COLUMNS = [ + "criterion", + "max-depth", + "min-samples-leaf", + "min-weight-fraction-leaf", + "n-estimators", + "TrainingJobName", + "TrainingJobStatus", + "TrainingStartTime", + "TrainingEndTime", + "TrainingElapsedTimeSeconds", + "TuningJobName", + "valid-f1", +] + +FULL_DF_COLUMNS = [ + "value", + "ts", + "label", + "rel_ts", + "TrainingJobName", + "criterion", + "max-depth", + "min-samples-leaf", + "min-weight-fraction-leaf", + "n-estimators", + "TrainingJobStatus", + "TrainingStartTime", + "TrainingEndTime", + "TrainingElapsedTimeSeconds", + "TuningJobName", + "valid-f1", +] + + +TRIALS_DF_TRAINING_JOB_NAMES = [ + "random-240712-1545-019-4ac17a84", + "random-240712-1545-021-fcd64dc1", +] + +TRIALS_DF_TRAINING_JOB_STATUSES = ["Completed", "Completed"] + +TUNING_JOB_NAME_1 = "random-240712-1500" +TUNING_JOB_NAME_2 = "bayesian-240712-1600" +TUNING_JOB_NAMES = [TUNING_JOB_NAME_1, TUNING_JOB_NAME_2] +TRIALS_DF_VALID_F1_VALUES = [0.950, 0.896] + +FULL_DF_COLUMNS = [ + "value", + "ts", + "label", + "rel_ts", + "TrainingJobName", + "criterion", + "max-depth", + "min-samples-leaf", + "min-weight-fraction-leaf", + "n-estimators", + "TrainingJobStatus", + "TrainingStartTime", + "TrainingEndTime", + "TrainingElapsedTimeSeconds", + "TuningJobName", + "valid-f1", +] + +TUNED_PARAMETERS = [ + "n-estimators", + "max-depth", + "min-samples-leaf", + "min-weight-fraction-leaf", + "criterion", +] +OBJECTIVE_NAME = "valid-f1" + +TRIALS_DF_DATA = { + "criterion": ["gini", "log_loss"], + "max-depth": [18.0, 8.0], + "min-samples-leaf": [3.0, 10.0], + "min-weight-fraction-leaf": [0.011596, 0.062067], + "n-estimators": [110.0, 18.0], + "TrainingJobName": ["random-240712-1545-019-4ac17a84", "random-240712-1545-021-fcd64dc1"], + "TrainingJobStatus": ["Completed", "Completed"], + "TrainingStartTime": ["2024-07-12 17:55:59+02:00", "2024-07-12 17:56:50+02:00"], + "TrainingEndTime": ["2024-07-12 17:56:43+02:00", "2024-07-12 17:57:29+02:00"], + "TrainingElapsedTimeSeconds": [44.0, 39.0], + "TuningJobName": TUNING_JOB_NAMES, + "valid-f1": [0.950, 0.896], +} + +FULL_DF_DATA = { + "value": [0.951000, 0.950000], + "ts": ["2024-07-12 15:56:00", "2024-07-12 15:56:00"], + "label": ["valid-precision", "valid-recall"], + "rel_ts": ["1970-01-01 01:00:00", "1970-01-01 01:00:00"], + "TrainingJobName": ["random-240712-1545-019-4ac17a84", "random-240712-1545-019-4ac17a84"], + "criterion": ["gini", "gini"], + "max-depth": [18.0, 18.0], + "min-samples-leaf": [3.0, 3.0], + "min-weight-fraction-leaf": [0.011596, 0.011596], + "n-estimators": [110.0, 110.0], + "TrainingJobStatus": ["Completed", "Completed"], + "TrainingStartTime": ["2024-07-12 17:55:59+02:00", "2024-07-12 17:55:59+02:00"], + "TrainingEndTime": ["2024-07-12 17:56:43+02:00", "2024-07-12 17:56:43+02:00"], + "TrainingElapsedTimeSeconds": [44.0, 45.0], + "TuningJobName": ["random-240712-1545", "random-240712-1545"], + "valid-f1": [0.9500, 0.9500], +} + +FILTERED_TUNING_JOB_DF_DATA = { + "criterion": ["log_loss", "gini"], + "max-depth": [10.0, 16.0], + "min-samples-leaf": [7.0, 2.0], + "min-weight-fraction-leaf": [0.160910, 0.069803], + "n-estimators": [67.0, 79.0], + "TrainingJobName": ["random-240712-1545-050-c0b5c10a", "random-240712-1545-049-2db2ec05"], + "TrainingJobStatus": ["Completed", "Completed"], + "FinalObjectiveValue": [0.8190, 0.8910], + "TrainingStartTime": ["2024-07-12 18:09:48+02:00", "2024-07-12 18:09:45+02:00"], + "TrainingEndTime": ["2024-07-12 18:10:28+02:00", "2024-07-12 18:10:23+02:00"], + "TrainingElapsedTimeSeconds": [40.0, 38.0], + "TuningJobName": [TUNING_JOB_NAME_1, TUNING_JOB_NAME_2], +} + +TUNING_RANGES = [ + {"Name": "n-estimators", "MinValue": "1", "MaxValue": "200", "ScalingType": "Auto"}, + {"Name": "max-depth", "MinValue": "1", "MaxValue": "20", "ScalingType": "Auto"}, + {"Name": "min-samples-leaf", "MinValue": "1", "MaxValue": "10", "ScalingType": "Auto"}, + { + "Name": "min-weight-fraction-leaf", + "MinValue": "0.01", + "MaxValue": "0.5", + "ScalingType": "Auto", + }, + {"Name": "criterion", "Values": ['"gini"', '"entropy"', '"log_loss"']}, +] + +TUNING_JOB_RESULT = { + "HyperParameterTuningJobName": TUNING_JOB_NAME_1, + "HyperParameterTuningJobConfig": { + "Strategy": "Random", + "HyperParameterTuningJobObjective": {"Type": "Maximize", "MetricName": "valid-f1"}, + }, + "HyperParameterTuningJobStatus": "Completed", +} diff --git a/tox.ini b/tox.ini index c47d206380..566e46a9a7 100644 --- a/tox.ini +++ b/tox.ini @@ -86,6 +86,7 @@ commands = pip install 'torch==2.3.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' pip install 'torchvision==0.18.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' pip install 'dill>=0.3.9' + pip install 'altair>=5.3' # needed for amtviz pytest {posargs} deps = .[test] From 3ec937818e62cb96b61b542bb07e40f57b1b7556 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Fri, 4 Jul 2025 14:18:27 +0000 Subject: [PATCH 128/164] change: update image_uri_configs 07-04-2025 07:18:27 PST --- .../image_uri_config/tensorflow.json | 93 ++++++++++++++++++- 1 file changed, 91 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/image_uri_config/tensorflow.json b/src/sagemaker/image_uri_config/tensorflow.json index 097baafa9b..8450b2d22f 100644 --- a/src/sagemaker/image_uri_config/tensorflow.json +++ b/src/sagemaker/image_uri_config/tensorflow.json @@ -333,7 +333,8 @@ "2.13": "2.13.0", "2.14": "2.14.1", "2.16": "2.16.1", - "2.18": "2.18.0" + "2.18": "2.18.0", + "2.19": "2.19.0" }, "versions": { "1.4.1": { @@ -2430,6 +2431,48 @@ "us-west-2": "763104351884" }, "repository": "tensorflow-inference" + }, + "2.19.0": { + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "tensorflow-inference" } } }, @@ -2729,7 +2772,8 @@ "2.13": "2.13.0", "2.14": "2.14.1", "2.16": "2.16.2", - "2.18": "2.18.0" + "2.18": "2.18.0", + "2.19": "2.19.0" }, "versions": { "1.4.1": { @@ -4905,6 +4949,51 @@ "us-west-2": "763104351884" }, "repository": "tensorflow-training" + }, + "2.19.0": { + "py_versions": [ + "py312" + ], + "registries": { + "af-south-1": "626614931356", + "ap-east-1": "871362719292", + "ap-east-2": "975050140332", + "ap-northeast-1": "763104351884", + "ap-northeast-2": "763104351884", + "ap-northeast-3": "364406365360", + "ap-south-1": "763104351884", + "ap-south-2": "772153158452", + "ap-southeast-1": "763104351884", + "ap-southeast-2": "763104351884", + "ap-southeast-3": "907027046896", + "ap-southeast-4": "457447274322", + "ap-southeast-5": "550225433462", + "ap-southeast-7": "590183813437", + "ca-central-1": "763104351884", + "ca-west-1": "204538143572", + "cn-north-1": "727897471807", + "cn-northwest-1": "727897471807", + "eu-central-1": "763104351884", + "eu-central-2": "380420809688", + "eu-north-1": "763104351884", + "eu-south-1": "692866216735", + "eu-south-2": "503227376785", + "eu-west-1": "763104351884", + "eu-west-2": "763104351884", + "eu-west-3": "763104351884", + "il-central-1": "780543022126", + "me-central-1": "914824155844", + "me-south-1": "217643126080", + "mx-central-1": "637423239942", + "sa-east-1": "763104351884", + "us-east-1": "763104351884", + "us-east-2": "763104351884", + "us-gov-east-1": "446045086412", + "us-gov-west-1": "442386744353", + "us-west-1": "763104351884", + "us-west-2": "763104351884" + }, + "repository": "tensorflow-training" } } } From e9d663c76e985567b5c86d53fb5f7c8042f585f2 Mon Sep 17 00:00:00 2001 From: Sirut Buasai <73297481+sirutBuasai@users.noreply.github.com> Date: Mon, 7 Jul 2025 19:51:41 -0700 Subject: [PATCH 129/164] Update TF DLC python version to py312 (#5231) * Update TF DLC python version to py312 * catch integ version --- tests/conftest.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index 7557c87fbe..34f5c5306d 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -554,7 +554,9 @@ def _tf_py_version(tf_version, request): return "py38" if Version("2.8") <= version < Version("2.12"): return "py39" - return "py310" + if Version("2.12") <= version < Version("2.19"): + return "py310" + return "py312" @pytest.fixture(scope="module") @@ -597,7 +599,9 @@ def tf_full_py_version(tf_full_version): return "py38" if version < Version("2.12"): return "py39" - return "py310" + if version < Version("2.19"): + return "py310" + return "py312" @pytest.fixture(scope="module") From d408594494b68b532c1a852ebc4ce7343ecb4e70 Mon Sep 17 00:00:00 2001 From: cj-zhang <32367995+cj-zhang@users.noreply.github.com> Date: Tue, 8 Jul 2025 10:31:09 -0700 Subject: [PATCH 130/164] Bump SMD version to enable custom workflow deployment. (#5230) * Bump SMD version to enable custom workflow deployment. * Update SMD image uri UT. --------- Co-authored-by: Joseph Zhang --- src/sagemaker/image_uri_config/sagemaker-distribution.json | 4 ++-- .../unit/sagemaker/image_uris/test_sagemaker_distribution.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/sagemaker/image_uri_config/sagemaker-distribution.json b/src/sagemaker/image_uri_config/sagemaker-distribution.json index d9ffca5d7b..9853eb01ae 100644 --- a/src/sagemaker/image_uri_config/sagemaker-distribution.json +++ b/src/sagemaker/image_uri_config/sagemaker-distribution.json @@ -2,10 +2,10 @@ "processors": ["cpu", "gpu"], "scope": ["inference"], "version_aliases": { - "3.0": "3.0.0" + "3.2": "3.2.0" }, "versions": { - "3.0.0": { + "3.2.0": { "registries": { "us-east-1": "885854791233", "us-east-2": "137914896644", diff --git a/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py b/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py index d339a50b2e..adc51064f1 100644 --- a/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py +++ b/tests/unit/sagemaker/image_uris/test_sagemaker_distribution.py @@ -41,7 +41,7 @@ def test_sagemaker_distribution_ecr_uri(load_config): account=SAGEMAKER_DISTRIBUTION_ACCOUNTS[region], region=region, version=version, - tag="3.0.0", + tag="3.2.0", instance_type=INSTANCE_TYPES[processor], processor=processor, ) From d7ed025e9c337a4ff486899cd8cba31e64491441 Mon Sep 17 00:00:00 2001 From: Roja Reddy Sareddy Date: Fri, 11 Jul 2025 00:32:02 -0700 Subject: [PATCH 131/164] Adding Hyperpod feature to enable hyperpod telemetry --- src/sagemaker/telemetry/constants.py | 1 + src/sagemaker/telemetry/telemetry_logging.py | 1 + 2 files changed, 2 insertions(+) diff --git a/src/sagemaker/telemetry/constants.py b/src/sagemaker/telemetry/constants.py index cb83a78279..2c803f4aa2 100644 --- a/src/sagemaker/telemetry/constants.py +++ b/src/sagemaker/telemetry/constants.py @@ -27,6 +27,7 @@ class Feature(Enum): REMOTE_FUNCTION = 3 MODEL_TRAINER = 4 ESTIMATOR = 5 + HYPERPOD = 6 def __str__(self): # pylint: disable=E0307 """Return the feature name.""" diff --git a/src/sagemaker/telemetry/telemetry_logging.py b/src/sagemaker/telemetry/telemetry_logging.py index b0ecedee4c..8c431b3338 100644 --- a/src/sagemaker/telemetry/telemetry_logging.py +++ b/src/sagemaker/telemetry/telemetry_logging.py @@ -55,6 +55,7 @@ str(Feature.REMOTE_FUNCTION): 3, str(Feature.MODEL_TRAINER): 4, str(Feature.ESTIMATOR): 5, + str(Feature.HYPERPOD): 6, } STATUS_TO_CODE = { From 3641c2b9a14929853051f812c7d0955834563369 Mon Sep 17 00:00:00 2001 From: rsareddy0329 Date: Fri, 11 Jul 2025 10:13:44 -0700 Subject: [PATCH 132/164] Adding Hyperpod feature to enable hyperpod telemetry (#5235) * Adding Hyperpod feature to enable hyperpod telemetry * Adding Hyperpod feature to enable hyperpod telemetry --------- Co-authored-by: Roja Reddy Sareddy --- src/sagemaker/telemetry/constants.py | 2 +- src/sagemaker/telemetry/telemetry_logging.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/sagemaker/telemetry/constants.py b/src/sagemaker/telemetry/constants.py index 2c803f4aa2..6766d45b4e 100644 --- a/src/sagemaker/telemetry/constants.py +++ b/src/sagemaker/telemetry/constants.py @@ -27,7 +27,7 @@ class Feature(Enum): REMOTE_FUNCTION = 3 MODEL_TRAINER = 4 ESTIMATOR = 5 - HYPERPOD = 6 + HYPERPOD = 6 # Added to support telemetry in sagemaker-hyperpod-cli def __str__(self): # pylint: disable=E0307 """Return the feature name.""" diff --git a/src/sagemaker/telemetry/telemetry_logging.py b/src/sagemaker/telemetry/telemetry_logging.py index 8c431b3338..990e12124f 100644 --- a/src/sagemaker/telemetry/telemetry_logging.py +++ b/src/sagemaker/telemetry/telemetry_logging.py @@ -55,7 +55,7 @@ str(Feature.REMOTE_FUNCTION): 3, str(Feature.MODEL_TRAINER): 4, str(Feature.ESTIMATOR): 5, - str(Feature.HYPERPOD): 6, + str(Feature.HYPERPOD): 6, # Added to support telemetry in sagemaker-hyperpod-cli } STATUS_TO_CODE = { From ed143b77a884e7498fd93099fae67feb8500468d Mon Sep 17 00:00:00 2001 From: "parknate@" Date: Fri, 11 Jul 2025 10:50:55 -0700 Subject: [PATCH 133/164] fix: sanitize git clone repo input url (#5234) --- src/sagemaker/git_utils.py | 70 +++++++++++- tests/unit/test_estimator.py | 2 +- tests/unit/test_git_utils.py | 216 ++++++++++++++++++++++++++++++++++- 3 files changed, 283 insertions(+), 5 deletions(-) diff --git a/src/sagemaker/git_utils.py b/src/sagemaker/git_utils.py index 49d151a00b..25e745446a 100644 --- a/src/sagemaker/git_utils.py +++ b/src/sagemaker/git_utils.py @@ -14,14 +14,78 @@ from __future__ import absolute_import import os -from pathlib import Path +import re import subprocess import tempfile import warnings +from pathlib import Path +from urllib.parse import urlparse + import six from six.moves import urllib +def _sanitize_git_url(repo_url): + """Sanitize Git repository URL to prevent URL injection attacks. + + Args: + repo_url (str): The Git repository URL to sanitize + + Returns: + str: The sanitized URL + + Raises: + ValueError: If the URL contains suspicious patterns that could indicate injection + """ + at_count = repo_url.count("@") + + if repo_url.startswith("git@"): + # git@ format requires exactly one @ + if at_count != 1: + raise ValueError("Invalid SSH URL format: git@ URLs must have exactly one @ symbol") + elif repo_url.startswith("ssh://"): + # ssh:// format can have 0 or 1 @ symbols + if at_count > 1: + raise ValueError("Invalid SSH URL format: multiple @ symbols detected") + elif repo_url.startswith("https://") or repo_url.startswith("http://"): + # HTTPS format allows 0 or 1 @ symbols + if at_count > 1: + raise ValueError("Invalid HTTPS URL format: multiple @ symbols detected") + + # Check for invalid characters in the URL before parsing + # These characters should not appear in legitimate URLs + invalid_chars = ["<", ">", "[", "]", "{", "}", "\\", "^", "`", "|"] + for char in invalid_chars: + if char in repo_url: + raise ValueError("Invalid characters in hostname") + + try: + parsed = urlparse(repo_url) + + # Check for suspicious characters in hostname that could indicate injection + if parsed.hostname: + # Check for URL-encoded characters that might be used for obfuscation + suspicious_patterns = ["%25", "%40", "%2F", "%3A"] # encoded %, @, /, : + for pattern in suspicious_patterns: + if pattern in parsed.hostname.lower(): + raise ValueError(f"Suspicious URL encoding detected in hostname: {pattern}") + + # Validate that the hostname looks legitimate + if not re.match(r"^[a-zA-Z0-9.-]+$", parsed.hostname): + raise ValueError("Invalid characters in hostname") + + except Exception as e: + if isinstance(e, ValueError): + raise + raise ValueError(f"Failed to parse URL: {str(e)}") + else: + raise ValueError( + "Unsupported URL scheme: only https://, http://, git@, and ssh:// are allowed" + ) + + return repo_url + + def git_clone_repo(git_config, entry_point, source_dir=None, dependencies=None): """Git clone repo containing the training code and serving code. @@ -87,6 +151,10 @@ def git_clone_repo(git_config, entry_point, source_dir=None, dependencies=None): if entry_point is None: raise ValueError("Please provide an entry point.") _validate_git_config(git_config) + + # SECURITY: Sanitize the repository URL to prevent injection attacks + git_config["repo"] = _sanitize_git_url(git_config["repo"]) + dest_dir = tempfile.mkdtemp() _generate_and_run_clone_command(git_config, dest_dir) diff --git a/tests/unit/test_estimator.py b/tests/unit/test_estimator.py index 11cc83a463..cfb243b563 100644 --- a/tests/unit/test_estimator.py +++ b/tests/unit/test_estimator.py @@ -2794,7 +2794,7 @@ def test_git_support_bad_repo_url_format(sagemaker_session): ) with pytest.raises(ValueError) as error: fw.fit() - assert "Invalid Git url provided." in str(error) + assert "Unsupported URL scheme" in str(error) @patch( diff --git a/tests/unit/test_git_utils.py b/tests/unit/test_git_utils.py index 03bbc1ebcd..2d10ac7619 100644 --- a/tests/unit/test_git_utils.py +++ b/tests/unit/test_git_utils.py @@ -12,11 +12,12 @@ # language governing permissions and limitations under the License. from __future__ import absolute_import -import pytest import os -from pathlib import Path import subprocess -from mock import patch, ANY +from pathlib import Path + +import pytest +from mock import ANY, patch from sagemaker import git_utils @@ -494,3 +495,212 @@ def test_git_clone_repo_codecommit_https_creds_not_stored_locally(tempdir, mkdte with pytest.raises(subprocess.CalledProcessError) as error: git_utils.git_clone_repo(git_config, entry_point) assert "returned non-zero exit status" in str(error.value) + + +class TestGitUrlSanitization: + """Test cases for Git URL sanitization to prevent injection attacks.""" + + def test_sanitize_git_url_valid_https_urls(self): + """Test that valid HTTPS URLs pass sanitization.""" + valid_urls = [ + "https://github.com/user/repo.git", + "https://gitlab.com/user/repo.git", + "https://token@github.com/user/repo.git", + "https://user:pass@github.com/user/repo.git", + "http://internal-git.company.com/repo.git", + ] + + for url in valid_urls: + # Should not raise any exception + result = git_utils._sanitize_git_url(url) + assert result == url + + def test_sanitize_git_url_valid_ssh_urls(self): + """Test that valid SSH URLs pass sanitization.""" + valid_urls = [ + "git@github.com:user/repo.git", + "git@gitlab.com:user/repo.git", + "ssh://git@github.com/user/repo.git", + "ssh://git-codecommit.us-west-2.amazonaws.com/v1/repos/test-repo/", # 0 @ symbols - valid for ssh:// + "git@internal-git.company.com:repo.git", + ] + + for url in valid_urls: + # Should not raise any exception + result = git_utils._sanitize_git_url(url) + assert result == url + + def test_sanitize_git_url_blocks_multiple_at_https(self): + """Test that HTTPS URLs with multiple @ symbols are blocked.""" + malicious_urls = [ + "https://user@attacker.com@github.com/repo.git", + "https://token@evil.com@gitlab.com/user/repo.git", + "https://a@b@c@github.com/repo.git", + "https://user@malicious-host@github.com/legit/repo.git", + ] + + for url in malicious_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + assert "multiple @ symbols detected" in str(error.value) + + def test_sanitize_git_url_blocks_multiple_at_ssh(self): + """Test that SSH URLs with multiple @ symbols are blocked.""" + malicious_urls = [ + "git@attacker.com@github.com:repo.git", + "git@evil@gitlab.com:user/repo.git", + "ssh://git@malicious@github.com/repo.git", + "git@a@b@c:repo.git", + ] + + for url in malicious_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + # git@ URLs should give "exactly one @ symbol" error + # ssh:// URLs should give "multiple @ symbols detected" error + assert any( + phrase in str(error.value) + for phrase in ["multiple @ symbols detected", "exactly one @ symbol"] + ) + + def test_sanitize_git_url_blocks_invalid_schemes_and_git_at_format(self): + """Test that invalid schemes and git@ format violations are blocked.""" + # Test unsupported schemes + unsupported_scheme_urls = [ + "git-github.com:user/repo.git", # Doesn't start with git@, ssh://, http://, https:// + ] + + for url in unsupported_scheme_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + assert "Unsupported URL scheme" in str(error.value) + + # Test git@ URLs with wrong @ count + invalid_git_at_urls = [ + "git@github.com@evil.com:repo.git", # 2 @ symbols + ] + + for url in invalid_git_at_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + assert "exactly one @ symbol" in str(error.value) + + def test_sanitize_git_url_blocks_url_encoding_obfuscation(self): + """Test that URL-encoded obfuscation attempts are blocked.""" + obfuscated_urls = [ + "https://github.com%25evil.com/repo.git", + "https://user@github.com%40attacker.com/repo.git", + "https://github.com%2Fevil.com/repo.git", + "https://github.com%3Aevil.com/repo.git", + ] + + for url in obfuscated_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + # The error could be either suspicious encoding or invalid characters + assert any( + phrase in str(error.value) + for phrase in ["Suspicious URL encoding detected", "Invalid characters in hostname"] + ) + + def test_sanitize_git_url_blocks_invalid_hostname_chars(self): + """Test that hostnames with invalid characters are blocked.""" + invalid_urls = [ + "https://github", + ] + + for url in unsupported_urls: + with pytest.raises(ValueError) as error: + git_utils._sanitize_git_url(url) + assert "Unsupported URL scheme" in str(error.value) + + def test_git_clone_repo_blocks_malicious_https_url(self): + """Test that git_clone_repo blocks malicious HTTPS URLs.""" + malicious_git_config = { + "repo": "https://user@attacker.com@github.com/legit/repo.git", + "branch": "main", + } + entry_point = "train.py" + + with pytest.raises(ValueError) as error: + git_utils.git_clone_repo(malicious_git_config, entry_point) + assert "multiple @ symbols detected" in str(error.value) + + def test_git_clone_repo_blocks_malicious_ssh_url(self): + """Test that git_clone_repo blocks malicious SSH URLs.""" + malicious_git_config = { + "repo": "git@OBVIOUS@github.com:sage-maker/temp-sev2.git", + "branch": "main", + } + entry_point = "train.py" + + with pytest.raises(ValueError) as error: + git_utils.git_clone_repo(malicious_git_config, entry_point) + assert "exactly one @ symbol" in str(error.value) + + def test_git_clone_repo_blocks_url_encoded_attack(self): + """Test that git_clone_repo blocks URL-encoded attacks.""" + malicious_git_config = { + "repo": "https://github.com%40attacker.com/repo.git", + "branch": "main", + } + entry_point = "train.py" + + with pytest.raises(ValueError) as error: + git_utils.git_clone_repo(malicious_git_config, entry_point) + assert "Suspicious URL encoding detected" in str(error.value) + + def test_sanitize_git_url_comprehensive_attack_scenarios(self): + attack_scenarios = [ + # Original PoC attack + "https://USER@YOUR_NGROK_OR_LOCALHOST/malicious.git@github.com%25legit%25repo.git", + # Variations of the attack + "https://user@malicious-host@github.com/legit/repo.git", + "git@attacker.com@github.com:user/repo.git", + "ssh://git@evil.com@github.com/repo.git", + # URL encoding variations + "https://github.com%40evil.com/repo.git", + "https://user@github.com%2Fevil.com/repo.git", + ] + + entry_point = "train.py" + + for malicious_url in attack_scenarios: + git_config = {"repo": malicious_url} + with pytest.raises(ValueError) as error: + git_utils.git_clone_repo(git_config, entry_point) + # Should be blocked by sanitization + assert any( + phrase in str(error.value) + for phrase in [ + "multiple @ symbols detected", + "exactly one @ symbol", + "Suspicious URL encoding detected", + "Invalid characters in hostname", + ] + ) From fca7cc036b4b1b8663dfc65b994041d7167483a6 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 11 Jul 2025 12:12:01 -0700 Subject: [PATCH 134/164] build(deps): bump torch in /tests/data/modules/script_mode (#5189) Bumps [torch](https://github.com/pytorch/pytorch) from 2.0.1+cpu to 2.7.0. - [Release notes](https://github.com/pytorch/pytorch/releases) - [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md) - [Commits](https://github.com/pytorch/pytorch/commits/v2.7.0) --- updated-dependencies: - dependency-name: torch dependency-version: 2.7.0 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: parknate@ --- tests/data/modules/script_mode/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/modules/script_mode/requirements.txt b/tests/data/modules/script_mode/requirements.txt index da7441eee2..f7b8ccf0cc 100644 --- a/tests/data/modules/script_mode/requirements.txt +++ b/tests/data/modules/script_mode/requirements.txt @@ -1,3 +1,3 @@ numpy -f https://download.pytorch.org/whl/torch_stable.html -torch==2.0.1+cpu +torch==2.7.0 From 2ee8407ed2e3c4cc7f1024e320217f0a0c2e35e2 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 11 Jul 2025 18:42:06 -0700 Subject: [PATCH 135/164] build(deps): bump mlflow in /tests/data/serve_resources/mlflow/xgboost (#5218) Bumps [mlflow](https://github.com/mlflow/mlflow) from 2.13.2 to 3.1.0. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](https://github.com/mlflow/mlflow/compare/v2.13.2...v3.1.0) --- updated-dependencies: - dependency-name: mlflow dependency-version: 3.1.0 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: parknate@ --- tests/data/serve_resources/mlflow/xgboost/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/serve_resources/mlflow/xgboost/requirements.txt b/tests/data/serve_resources/mlflow/xgboost/requirements.txt index 30fc49cc97..78c7a1afda 100644 --- a/tests/data/serve_resources/mlflow/xgboost/requirements.txt +++ b/tests/data/serve_resources/mlflow/xgboost/requirements.txt @@ -1,4 +1,4 @@ -mlflow==2.13.2 +mlflow==3.1.0 lz4==4.3.2 numpy==1.26.4 pandas==2.0.3 From 757c700f81356d949b96dc5045d37a9229128c45 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 11 Jul 2025 18:49:33 -0700 Subject: [PATCH 136/164] build(deps): bump protobuf from 4.25.5 to 4.25.8 in /requirements/extras (#5209) Bumps [protobuf](https://github.com/protocolbuffers/protobuf) from 4.25.5 to 4.25.8. - [Release notes](https://github.com/protocolbuffers/protobuf/releases) - [Changelog](https://github.com/protocolbuffers/protobuf/blob/main/protobuf_release.bzl) - [Commits](https://github.com/protocolbuffers/protobuf/compare/v4.25.5...v4.25.8) --- updated-dependencies: - dependency-name: protobuf dependency-version: 4.25.8 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: parknate@ --- requirements/extras/test_requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 04d6c0522a..81bff89ddf 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -32,7 +32,7 @@ PyYAML>=6.0.1 xgboost>=1.6.2,<=1.7.6 pillow>=10.0.1,<=11 opentelemetry-proto==1.27.0 -protobuf==4.25.5 +protobuf==4.25.8 tensorboard>=2.16.2,<=2.18.0 transformers==4.48.0 sentencepiece==0.1.99 From 768ec1c8e9ba5e2d6275351638b092cc1b8c275a Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 11 Jul 2025 18:49:55 -0700 Subject: [PATCH 137/164] build(deps): bump requests in /tests/data/serve_resources/mlflow/pytorch (#5200) Bumps [requests](https://github.com/psf/requests) from 2.32.2 to 2.32.4. - [Release notes](https://github.com/psf/requests/releases) - [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md) - [Commits](https://github.com/psf/requests/compare/v2.32.2...v2.32.4) --- updated-dependencies: - dependency-name: requests dependency-version: 2.32.4 dependency-type: direct:production ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: parknate@ --- tests/data/serve_resources/mlflow/pytorch/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/serve_resources/mlflow/pytorch/requirements.txt b/tests/data/serve_resources/mlflow/pytorch/requirements.txt index a3eb04ed4f..eabe5e8e82 100644 --- a/tests/data/serve_resources/mlflow/pytorch/requirements.txt +++ b/tests/data/serve_resources/mlflow/pytorch/requirements.txt @@ -10,7 +10,7 @@ opt-einsum==3.3.0 packaging>=23.0,<25 pandas==2.2.1 pyyaml==6.0.1 -requests==2.32.2 +requests==2.32.4 torch>=2.6.0 torchvision>=0.17.0 tqdm==4.66.3 From 2f564e9ace8cbbdcd7fcd036e8bb6bb6d60f3899 Mon Sep 17 00:00:00 2001 From: ci Date: Tue, 15 Jul 2025 02:26:41 +0000 Subject: [PATCH 138/164] prepare release v2.248.0 --- CHANGELOG.md | 21 +++++++++++++++++++++ VERSION | 2 +- 2 files changed, 22 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index c43a7c91db..13a72a8f6a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,26 @@ # Changelog +## v2.248.0 (2025-07-15) + +### Features + + * integrate amtviz for visualization of tuning jobs + +### Bug Fixes and Other Changes + + * build(deps): bump requests in /tests/data/serve_resources/mlflow/pytorch + * build(deps): bump protobuf from 4.25.5 to 4.25.8 in /requirements/extras + * build(deps): bump mlflow in /tests/data/serve_resources/mlflow/xgboost + * build(deps): bump torch in /tests/data/modules/script_mode + * sanitize git clone repo input url + * Adding Hyperpod feature to enable hyperpod telemetry + * Adding Hyperpod feature to enable hyperpod telemetry + * Bump SMD version to enable custom workflow deployment. + * Update TF DLC python version to py312 + * update image_uri_configs 07-04-2025 07:18:27 PST + * update image_uri_configs 06-26-2025 07:18:35 PST + * relax protobuf to <6.32 + ## v2.247.1 (2025-06-23) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index cdbe343ddb..0c52ca6233 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.247.2.dev0 +2.248.0 From 61d043febabc1ce057512531a98df634190e01d3 Mon Sep 17 00:00:00 2001 From: ci Date: Tue, 15 Jul 2025 02:26:46 +0000 Subject: [PATCH 139/164] update development version to v2.248.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 0c52ca6233..c6caf264f5 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.0 +2.248.1.dev0 From f06ef6e50f2d0c2d60c7a12d8320e25c9ff524d8 Mon Sep 17 00:00:00 2001 From: Tritin Truong Date: Tue, 15 Jul 2025 14:25:31 -0700 Subject: [PATCH 140/164] Nova training support (#5238) * feature: Added Amazon Nova training support for ModelTrainer and Estimator Co-authored-by: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> --- .gitignore | 3 +- src/sagemaker/estimator.py | 47 +- src/sagemaker/fw_utils.py | 2 +- src/sagemaker/modules/constants.py | 4 + src/sagemaker/modules/train/model_trainer.py | 112 ++- .../modules/train/sm_recipes/utils.py | 129 ++- src/sagemaker/pytorch/estimator.py | 784 +++++++++++++++--- .../modules/train/sm_recipes/test_utils.py | 230 ++++- .../modules/train/test_model_trainer.py | 90 ++ tests/unit/test_pytorch_nova.py | 753 +++++++++++++++++ 10 files changed, 1985 insertions(+), 169 deletions(-) create mode 100644 tests/unit/test_pytorch_nova.py diff --git a/.gitignore b/.gitignore index fc07847fba..3d90b52e01 100644 --- a/.gitignore +++ b/.gitignore @@ -37,4 +37,5 @@ src/sagemaker/modules/train/container_drivers/sourcecode.json src/sagemaker/modules/train/container_drivers/distributed.json tests/data/**/_repack_model.py tests/data/experiment/sagemaker-dev-1.0.tar.gz -src/sagemaker/serve/tmp_workspace \ No newline at end of file +src/sagemaker/serve/tmp_workspace +test-examples \ No newline at end of file diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py index 16e6ac1cd0..9b4beae5c4 100644 --- a/src/sagemaker/estimator.py +++ b/src/sagemaker/estimator.py @@ -905,6 +905,30 @@ def _json_encode_hyperparameters(hyperparameters: Dict[str, Any]) -> Dict[str, A } return hyperparameters + @staticmethod + def _nova_encode_hyperparameters(hyperparameters: Dict[str, Any]) -> Dict[str, Any]: + """Applies JSON encoding for Nova job hyperparameters, preserving string values. + + For Nova jobs, string values should not be JSON-encoded. + + Args: + hyperparameters (dict): Dictionary of hyperparameters. + + Returns: + dict: Dictionary with encoded hyperparameters. + """ + current_hyperparameters = hyperparameters + if current_hyperparameters is not None: + hyperparameters = {} + for k, v in current_hyperparameters.items(): + if is_pipeline_variable(v): + hyperparameters[str(k)] = v.to_string() + elif isinstance(v, str): + hyperparameters[str(k)] = v + else: + hyperparameters[str(k)] = json.dumps(v) + return hyperparameters + def _prepare_for_training(self, job_name=None): """Set any values in the estimator that need to be set before training. @@ -938,7 +962,11 @@ def _prepare_for_training(self, job_name=None): self.source_dir = updated_paths["source_dir"] self.dependencies = updated_paths["dependencies"] - if self.source_dir or self.entry_point or self.dependencies: + if ( + self.source_dir + or self.entry_point + or (self.dependencies and len(self.dependencies) > 0) + ): # validate source dir will raise a ValueError if there is something wrong with # the source directory. We are intentionally not handling it because this is a # critical error. @@ -3579,7 +3607,11 @@ def __init__( git_config=git_config, enable_network_isolation=enable_network_isolation, ) - if not is_pipeline_variable(entry_point) and entry_point.startswith("s3://"): + if ( + not is_pipeline_variable(entry_point) + and entry_point is not None + and entry_point.startswith("s3://") + ): raise ValueError( "Invalid entry point script: {}. Must be a path to a local file.".format( entry_point @@ -3599,6 +3631,7 @@ def __init__( self.checkpoint_s3_uri = checkpoint_s3_uri self.checkpoint_local_path = checkpoint_local_path self.enable_sagemaker_metrics = enable_sagemaker_metrics + self.is_nova_job = kwargs.get("is_nova_job", False) def _prepare_for_training(self, job_name=None): """Set hyperparameters needed for training. This method will also validate ``source_dir``. @@ -3713,7 +3746,10 @@ def _model_entry_point(self): def set_hyperparameters(self, **kwargs): """Escapes the dict argument as JSON, updates the private hyperparameter attribute.""" - self._hyperparameters.update(EstimatorBase._json_encode_hyperparameters(kwargs)) + if self.is_nova_job: + self._hyperparameters.update(EstimatorBase._nova_encode_hyperparameters(kwargs)) + else: + self._hyperparameters.update(EstimatorBase._json_encode_hyperparameters(kwargs)) def hyperparameters(self): """Returns the hyperparameters as a dictionary to use for training. @@ -3724,7 +3760,10 @@ def hyperparameters(self): Returns: dict[str, str]: The hyperparameters. """ - return EstimatorBase._json_encode_hyperparameters(self._hyperparameters) + if self.is_nova_job: + return EstimatorBase._nova_encode_hyperparameters(self._hyperparameters) + else: + return EstimatorBase._json_encode_hyperparameters(self._hyperparameters) @classmethod def _prepare_init_params_from_job_description(cls, job_details, model_channel_name=None): diff --git a/src/sagemaker/fw_utils.py b/src/sagemaker/fw_utils.py index 234f0c61fa..4a00b2dbc1 100644 --- a/src/sagemaker/fw_utils.py +++ b/src/sagemaker/fw_utils.py @@ -1063,7 +1063,7 @@ def validate_torch_distributed_distribution( ) # Check entry point type - if not entry_point.endswith(".py"): + if entry_point is not None and not entry_point.endswith(".py"): err_msg += ( "Unsupported entry point type for the distribution torch_distributed.\n" "Only python programs (*.py) are supported." diff --git a/src/sagemaker/modules/constants.py b/src/sagemaker/modules/constants.py index e64d85367d..eaf9d131ef 100644 --- a/src/sagemaker/modules/constants.py +++ b/src/sagemaker/modules/constants.py @@ -25,6 +25,10 @@ os.path.dirname(os.path.abspath(__file__)), "train/container_drivers" ) +SM_RECIPE = "recipe" +SM_RECIPE_YAML = "recipe.yaml" +SM_RECIPE_CONTAINER_PATH = f"/opt/ml/input/data/recipe/{SM_RECIPE_YAML}" + SOURCE_CODE_JSON = "sourcecode.json" DISTRIBUTED_JSON = "distributed.json" TRAIN_SCRIPT = "sm_train.sh" diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index eaabe5972a..24b7922895 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -85,6 +85,9 @@ SM_CODE_CONTAINER_PATH, SM_DRIVERS, SM_DRIVERS_LOCAL_PATH, + SM_RECIPE, + SM_RECIPE_YAML, + SM_RECIPE_CONTAINER_PATH, TRAIN_SCRIPT, DEFAULT_CONTAINER_ENTRYPOINT, DEFAULT_CONTAINER_ARGUMENTS, @@ -100,7 +103,12 @@ from sagemaker.telemetry.telemetry_logging import _telemetry_emitter from sagemaker.telemetry.constants import Feature from sagemaker.modules import logger -from sagemaker.modules.train.sm_recipes.utils import _get_args_from_recipe, _determine_device_type +from sagemaker.modules.train.sm_recipes.utils import ( + _get_args_from_recipe, + _determine_device_type, + _is_nova_recipe, + _load_base_recipe, +) class Mode(Enum): @@ -242,6 +250,7 @@ class ModelTrainer(BaseModel): _remote_debug_config: Optional[RemoteDebugConfig] = PrivateAttr(default=None) _metric_definitions: Optional[List[MetricDefinition]] = PrivateAttr(default=None) + _is_nova_recipe: Optional[bool] = PrivateAttr(default=None) _temp_recipe_train_dir: Optional[TemporaryDirectory] = PrivateAttr(default=None) CONFIGURABLE_ATTRIBUTES: ClassVar[List[str]] = [ @@ -449,6 +458,33 @@ def _validate_source_code(self, source_code: Optional[SourceCode]): + "Must be a valid file within the 'source_dir'.", ) + @staticmethod + def _validate_and_load_hyperparameters_file(hyperparameters_file: str) -> Dict[str, Any]: + """Validate the hyperparameters file.""" + if not os.path.exists(hyperparameters_file): + raise ValueError(f"Hyperparameters file not found: {hyperparameters_file}") + logger.info(f"Loading hyperparameters from file: {hyperparameters_file}") + with open(hyperparameters_file, "r") as f: + contents = f.read() + try: + hyperparameters = json.loads(contents) + logger.debug("Hyperparameters loaded as JSON") + return hyperparameters + except json.JSONDecodeError: + try: + logger.info(f"contents: {contents}") + hyperparameters = yaml.safe_load(contents) + if not isinstance(hyperparameters, dict): + raise ValueError("YAML contents must be a valid mapping") + logger.info(f"hyperparameters: {hyperparameters}") + logger.debug("Hyperparameters loaded as YAML") + return hyperparameters + except (yaml.YAMLError, ValueError): + raise ValueError( + f"Invalid hyperparameters file: {hyperparameters_file}. " + "Must be a valid JSON or YAML file." + ) + def model_post_init(self, __context: Any): """Post init method to perform custom validation and set default values.""" self._validate_training_image_and_algorithm_name(self.training_image, self.algorithm_name) @@ -510,27 +546,9 @@ def model_post_init(self, __context: Any): ) if self.hyperparameters and isinstance(self.hyperparameters, str): - if not os.path.exists(self.hyperparameters): - raise ValueError(f"Hyperparameters file not found: {self.hyperparameters}") - logger.info(f"Loading hyperparameters from file: {self.hyperparameters}") - with open(self.hyperparameters, "r") as f: - contents = f.read() - try: - self.hyperparameters = json.loads(contents) - logger.debug("Hyperparameters loaded as JSON") - except json.JSONDecodeError: - try: - logger.info(f"contents: {contents}") - self.hyperparameters = yaml.safe_load(contents) - if not isinstance(self.hyperparameters, dict): - raise ValueError("YAML contents must be a valid mapping") - logger.info(f"hyperparameters: {self.hyperparameters}") - logger.debug("Hyperparameters loaded as YAML") - except (yaml.YAMLError, ValueError): - raise ValueError( - f"Invalid hyperparameters file: {self.hyperparameters}. " - "Must be a valid JSON or YAML file." - ) + self.hyperparameters = self._validate_and_load_hyperparameters_file( + self.hyperparameters + ) if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB: if self.output_data_config is None: @@ -613,6 +631,22 @@ def train( final_input_data_config = list(existing_channels.values()) + new_channels + if self._is_nova_recipe: + for input_data in final_input_data_config: + if input_data.channel_name == SM_RECIPE: + raise ValueError( + "Cannot use reserved channel name 'recipe' as an input channel name " + " for Nova Recipe" + ) + recipe_file_path = os.path.join(self._temp_recipe_train_dir.name, SM_RECIPE_YAML) + recipe_channel = self.create_input_data_channel( + channel_name=SM_RECIPE, + data_source=recipe_file_path, + key_prefix=input_data_key_prefix, + ) + final_input_data_config.append(recipe_channel) + self.hyperparameters.update({"sagemaker_recipe_local_path": SM_RECIPE_CONTAINER_PATH}) + if final_input_data_config: final_input_data_config = self._get_input_data_config( final_input_data_config, input_data_key_prefix @@ -1005,6 +1039,7 @@ def from_recipe( checkpoint_config: Optional[shapes.CheckpointConfig] = None, training_input_mode: Optional[str] = "File", environment: Optional[Dict[str, str]] = None, + hyperparameters: Optional[Union[Dict[str, Any], str]] = {}, tags: Optional[List[Tag]] = None, sagemaker_session: Optional[Session] = None, role: Optional[str] = None, @@ -1101,14 +1136,21 @@ def from_recipe( """ if compute.instance_type is None: raise ValueError( - "Must set ``instance_type`` in compute_config when using training recipes." + "Must set ``instance_type`` in ``compute`` input when using training recipes." ) device_type = _determine_device_type(compute.instance_type) - if device_type == "cpu": + recipe = _load_base_recipe( + training_recipe=training_recipe, recipe_overrides=recipe_overrides + ) + is_nova = _is_nova_recipe(recipe=recipe) + + if device_type == "cpu" and not is_nova: raise ValueError( - "Training recipes are not supported for CPU instances. " + "Training recipe is not supported for CPU instances. " + "Please provide a GPU or Tranium instance type." ) + if training_image is None and is_nova: + raise ValueError("training_image must be provided when using recipe for Nova.") if training_image_config and training_image is None: raise ValueError("training_image must be provided when using training_image_config.") @@ -1126,15 +1168,27 @@ def from_recipe( # - distributed # - compute # - hyperparameters - model_trainer_args, recipe_train_dir = _get_args_from_recipe( - training_recipe=training_recipe, + model_trainer_args, tmp_dir = _get_args_from_recipe( + training_recipe=recipe, recipe_overrides=recipe_overrides, requirements=requirements, compute=compute, region_name=sagemaker_session.boto_region_name, + role=role, ) if training_image is not None: model_trainer_args["training_image"] = training_image + if hyperparameters and not is_nova: + logger.warning( + "Hyperparameters are not supported for general training recipes. " + + "Ignoring hyperparameters input." + ) + if is_nova: + if hyperparameters and isinstance(hyperparameters, str): + hyperparameters = cls._validate_and_load_hyperparameters_file(hyperparameters) + model_trainer_args["hyperparameters"].update(hyperparameters) + elif hyperparameters and isinstance(hyperparameters, dict): + model_trainer_args["hyperparameters"].update(hyperparameters) model_trainer = cls( sagemaker_session=sagemaker_session, @@ -1151,8 +1205,8 @@ def from_recipe( tags=tags, **model_trainer_args, ) - - model_trainer._temp_recipe_train_dir = recipe_train_dir + model_trainer._is_nova_recipe = is_nova + model_trainer._temp_recipe_train_dir = tmp_dir return model_trainer def with_tensorboard_output_config( diff --git a/src/sagemaker/modules/train/sm_recipes/utils.py b/src/sagemaker/modules/train/sm_recipes/utils.py index 6b39add6cd..3b7659016e 100644 --- a/src/sagemaker/modules/train/sm_recipes/utils.py +++ b/src/sagemaker/modules/train/sm_recipes/utils.py @@ -19,20 +19,21 @@ import shutil import tempfile from urllib.request import urlretrieve -from typing import Dict, Any, Optional, Tuple +from typing import Dict, Any, Optional, Tuple, Union import omegaconf -from omegaconf import OmegaConf, dictconfig +from omegaconf import OmegaConf, dictconfig, DictConfig from sagemaker.image_uris import retrieve from sagemaker.modules import logger from sagemaker.modules.utils import _run_clone_command_silent +from sagemaker.modules.constants import SM_RECIPE_YAML from sagemaker.modules.configs import Compute, SourceCode from sagemaker.modules.distributed import Torchrun, SMP -def _try_resolve_recipe(recipe, key=None): +def _try_resolve_recipe(recipe: DictConfig, key=None) -> DictConfig: """Try to resolve recipe and return resolved recipe.""" if key is not None: recipe = dictconfig.DictConfig({key: recipe}) @@ -86,6 +87,8 @@ def _load_base_recipe( ) else: recipe_launcher_dir = tempfile.TemporaryDirectory(prefix="launcher_") + if training_recipes_cfg is None: + training_recipes_cfg = _load_recipes_cfg() launcher_repo = os.environ.get("TRAINING_LAUNCHER_GIT", None) or training_recipes_cfg.get( "launcher_repo" @@ -149,7 +152,7 @@ def _get_trainining_recipe_gpu_model_name_and_script(model_type: str): def _configure_gpu_args( training_recipes_cfg: Dict[str, Any], region_name: str, - recipe: OmegaConf, + recipe: DictConfig, recipe_train_dir: tempfile.TemporaryDirectory, ) -> Dict[str, Any]: """Configure arguments specific to GPU.""" @@ -231,12 +234,110 @@ def _configure_trainium_args( return args +def _is_nova_recipe( + recipe: DictConfig, +) -> bool: + """Check if the recipe is a Nova recipe. + + A recipe is considered a Nova recipe if it meets either of the following conditions: + + 1. It has a run section with: + - A model_type that includes "amazon.nova" + - A model_name_or_path field + + OR + + 2. It has a training_config section with: + - A distillation_data field + + Args: + recipe (DictConfig): The loaded recipe configuration + + Returns: + bool: True if the recipe is a Nova recipe, False otherwise + """ + run_config = recipe.get("run", {}) + model_type = run_config.get("model_type", "").lower() + has_nova_model = ( + model_type and "amazon.nova" in model_type and "model_name_or_path" in run_config + ) + + # Check for distillation data + training_config = recipe.get("training_config", {}) + has_distillation = training_config.get("distillation_data") is not None + return bool(has_nova_model) or bool(has_distillation) + + +def _get_args_from_nova_recipe( + recipe: DictConfig, + compute: Compute, + role: Optional[str] = None, +) -> Tuple[Dict[str, Any], tempfile.TemporaryDirectory]: + if not compute.instance_count and not recipe.get("run", {}).get("replicas", None): + raise ValueError("Must set ``instance_type`` in compute or ``replicas`` in recipe.") + compute.instance_count = compute.instance_count or recipe.get("run", {}).get("replicas") + + args = dict() + args.update({"hyperparameters": {}}) + + run_config = recipe.get("run", {}) + model_name_or_path = run_config.get("model_name_or_path") + if model_name_or_path: + if model_name_or_path.startswith("s3://"): + args["hyperparameters"]["base_model_location"] = model_name_or_path + else: + args["hyperparameters"]["base_model"] = model_name_or_path + + # Handle distillation configuration + training_config = recipe.get("training_config", {}) + distillation_data = training_config.get("distillation_data") + if bool(distillation_data): + args["hyperparameters"]["distillation_data"] = distillation_data + if not role: + raise ValueError("Must provide 'role' parameter when using Nova distillation") + args["hyperparameters"]["role_arn"] = role + + kms_key = training_config.get("kms_key") + if kms_key is None: + raise ValueError( + 'Nova distillation job recipe requires "kms_key" field in "training_config"' + ) + args["hyperparameters"]["kms_key"] = kms_key + + _register_custom_resolvers() + + # Resolve Final Recipe + final_recipe = _try_resolve_recipe(recipe) + if final_recipe is None: + final_recipe = _try_resolve_recipe(recipe, "recipes") + if final_recipe is None: + final_recipe = _try_resolve_recipe(recipe, "training") + if final_recipe is None: + raise RuntimeError("Could not resolve provided recipe.") + + # Save Final Recipe to tmp dir + recipe_local_dir = tempfile.TemporaryDirectory(prefix="recipe_") + final_recipe_path = os.path.join(recipe_local_dir.name, SM_RECIPE_YAML) + OmegaConf.save(config=final_recipe, f=final_recipe_path) + + args.update( + { + "compute": compute, + "training_image": None, + "source_code": None, + "distributed": None, + } + ) + return args, recipe_local_dir + + def _get_args_from_recipe( - training_recipe: str, + training_recipe: Union[str, DictConfig], compute: Compute, region_name: str, recipe_overrides: Optional[Dict[str, Any]], requirements: Optional[str], + role: Optional[str] = None, ) -> Tuple[Dict[str, Any], tempfile.TemporaryDirectory]: """Get arguments for ModelTrainer from a training recipe. @@ -252,8 +353,8 @@ def _get_args_from_recipe( ``` Args: - training_recipe (str): - Name of the training recipe or path to the recipe file. + training_recipe (Union[str, Dict[str, Any]]): + Name of the training recipe or path to the recipe file or loaded recipe Dict. compute (Compute): Compute configuration for training. region_name (str): @@ -267,7 +368,13 @@ def _get_args_from_recipe( raise ValueError("Must set `instance_type` in compute when using training recipes.") training_recipes_cfg = _load_recipes_cfg() - recipe = _load_base_recipe(training_recipe, recipe_overrides, training_recipes_cfg) + if isinstance(training_recipe, str): + recipe = _load_base_recipe(training_recipe, recipe_overrides, training_recipes_cfg) + else: + recipe = training_recipe + if _is_nova_recipe(recipe): + args, recipe_local_dir = _get_args_from_nova_recipe(recipe, compute, role=role) + return args, recipe_local_dir if "trainer" not in recipe: raise ValueError("Supplied recipe does not contain required field trainer.") @@ -281,7 +388,7 @@ def _get_args_from_recipe( if compute.instance_count is None: if "num_nodes" not in recipe["trainer"]: raise ValueError( - "Must provide Compute with instance_count or" " set trainer -> num_nodes in recipe." + "Must provide Compute with instance_count or set trainer -> num_nodes in recipe." ) compute.instance_count = recipe["trainer"]["num_nodes"] @@ -311,7 +418,7 @@ def _get_args_from_recipe( # Save Final Recipe to source_dir OmegaConf.save( - config=final_recipe, f=os.path.join(args["source_code"].source_dir, "recipe.yaml") + config=final_recipe, f=os.path.join(args["source_code"].source_dir, SM_RECIPE_YAML) ) # If recipe_requirements is provided, copy it to source_dir @@ -323,7 +430,7 @@ def _get_args_from_recipe( args.update( { "compute": compute, - "hyperparameters": {"config-path": ".", "config-name": "recipe.yaml"}, + "hyperparameters": {"config-path": ".", "config-name": SM_RECIPE_YAML}, } ) diff --git a/src/sagemaker/pytorch/estimator.py b/src/sagemaker/pytorch/estimator.py index d56c100546..633317927b 100644 --- a/src/sagemaker/pytorch/estimator.py +++ b/src/sagemaker/pytorch/estimator.py @@ -19,6 +19,8 @@ import os import shutil import tempfile +import time +from datetime import datetime from typing import Union, Optional, Dict from urllib.request import urlretrieve @@ -27,6 +29,7 @@ from packaging.version import Version from sagemaker.estimator import Framework, EstimatorBase +from sagemaker.inputs import TrainingInput, FileSystemInput from sagemaker.fw_utils import ( framework_name_from_image, framework_version_from_tag, @@ -126,6 +129,170 @@ def _get_training_recipe_trainium_script(code_dir, source_dir): return script +def _is_nova_recipe(recipe): + """Check if the recipe is a Nova recipe. + + A Nova recipe is identified by: + 1. Having a run section + 2. The model_type in run has a "amazon.nova" prefix + 3. The run contains model_name_or_path + + OR + + 1. Has a training_config section + 2. The training config_section has a distillation_data field + + Args: + recipe (OmegaConf): The loaded recipe configuration + + Returns: + bool: True if the recipe is a Nova recipe, False otherwise + """ + # Check for nova model + run_config = recipe.get("run", {}) + model_type = run_config.get("model_type", "").lower() + has_nova_model = ( + model_type and "amazon.nova" in model_type and "model_name_or_path" in run_config + ) + + # Check for distillation data + training_config = recipe.get("training_config", {}) + has_distillation = training_config.get("distillation_data") is not None + + return bool(has_nova_model) or bool(has_distillation) + + +def _recipe_initialize_args(source_dir): + """Initialize the arguments dictionary for recipe setup. + + Args: + source_dir (str): Path to the source directory. + + Returns: + dict: Initialized arguments dictionary. + + Raises: + ValueError: If source_dir is not a local directory. + """ + args = {"hyperparameters": {}} + + if source_dir is None: + args["source_dir"] = "." + else: + if not os.path.exists(source_dir): + raise ValueError("When using training_recipe, source_dir must be a local directory.") + args["source_dir"] = source_dir + + return args + + +def _recipe_get_region_name(kwargs): + """Get the AWS region name from session or create a new session. + + Args: + kwargs (dict): Dictionary of keyword arguments. + + Returns: + str: AWS region name. + """ + if kwargs.get("sagemaker_session") is not None: + return kwargs.get("sagemaker_session").boto_region_name + return Session().boto_region_name + + +def _recipe_load_config(): + """Load the training recipes configuration from JSON file. + + Returns: + dict: Training recipes configuration. + """ + training_recipes_cfg_filename = os.path.join(os.path.dirname(__file__), "training_recipes.json") + with open(training_recipes_cfg_filename) as training_recipes_cfg_file: + return json.load(training_recipes_cfg_file) + + +def _recipe_load_from_yaml(training_recipe, temp_local_recipe): + """Load recipe from a YAML file or URL. + + Args: + training_recipe (str): Path to the training recipe. + temp_local_recipe (str): Path to the temporary local recipe file. + + Raises: + ValueError: If the recipe cannot be fetched. + """ + if os.path.isfile(training_recipe): + shutil.copy(training_recipe, temp_local_recipe) + else: + try: + urlretrieve(training_recipe, temp_local_recipe) + except Exception as e: + raise ValueError( + f"Could not fetch the provided recipe {training_recipe}: exception {str(e)}" + ) + + +def _recipe_load_predefined( + training_recipe, recipe_launcher_dir, temp_local_recipe, training_recipes_cfg +): + """Load a predefined recipe from the recipe launcher. + + Args: + training_recipe (str): Name of the predefined recipe. + recipe_launcher_dir (str): Path to the recipe launcher directory. + temp_local_recipe (str): Path to the temporary local recipe file. + training_recipes_cfg (dict): Training recipes configuration. + + Raises: + ValueError: If the recipe cannot be found. + """ + launcher_repo = os.environ.get("TRAINING_LAUNCHER_GIT", None) or training_recipes_cfg.get( + "launcher_repo" + ) + _run_clone_command(launcher_repo, recipe_launcher_dir) + recipe_path = os.path.join( + recipe_launcher_dir, + "recipes_collection", + "recipes", + training_recipe + ".yaml", + ) + if os.path.isfile(recipe_path): + shutil.copy(recipe_path, temp_local_recipe) + else: + raise ValueError(f"Recipe {training_recipe} not found.") + + +def _device_get_distribution(device_type): + """Get the distribution configuration based on device type. + + Args: + device_type (str): Device type (gpu, trainium, or cpu). + + Returns: + dict: Distribution configuration. + + Raises: + ValueError: If the device type is not supported. + """ + if device_type == "gpu": + smp_options = { + "enabled": True, + "parameters": { + "placement_strategy": "cluster", + }, + } + return { + "smdistributed": {"modelparallel": smp_options}, + "torch_distributed": {"enabled": True}, + } + elif device_type == "trainium": + return { + "torch_distributed": {"enabled": True}, + } + else: + return {} + + class PyTorch(Framework): """Handle end-to-end training and deployment of custom PyTorch code.""" @@ -358,6 +525,7 @@ def __init__( :class:`~sagemaker.estimator.Framework` and :class:`~sagemaker.estimator.EstimatorBase`. """ + self.is_nova_recipe = False if training_recipe is not None: if entry_point is not None: logger.warning("Argument entry_point will be ignored with training_recipe.") @@ -368,6 +536,10 @@ def __init__( args = self._setup_for_training_recipe( training_recipe, recipe_overrides, source_dir, kwargs ) + + if self.is_nova_recipe and image_uri is None: + raise ValueError("Must supply image_uri for nova jobs.") + entry_point = args["entry_point"] source_dir = args["source_dir"] hyperparameters = args["hyperparameters"] @@ -392,7 +564,12 @@ def __init__( kwargs["enable_sagemaker_metrics"] = True super(PyTorch, self).__init__( - entry_point, source_dir, hyperparameters, image_uri=image_uri, **kwargs + entry_point, + source_dir, + hyperparameters, + image_uri=image_uri, + is_nova_job=self.is_nova_recipe, + **kwargs, ) if "entry_point" not in kwargs: @@ -499,6 +676,72 @@ def hyperparameters(self): return hyperparameters + def fit( + self, + inputs: Optional[Union[str, Dict, TrainingInput, FileSystemInput]] = None, + wait: bool = True, + logs: str = "All", + job_name: Optional[str] = None, + experiment_config: Optional[Dict[str, str]] = None, + ): + """Train a model using the input training dataset. + + Adds the recipe file to the inputs when a training recipe is used. + + Args: + inputs (str or dict or sagemaker.inputs.TrainingInput or + sagemaker.inputs.FileSystemInput): Information about the training data. + wait (bool): Whether the call should wait until the job completes (default: True). + logs ([str]): A list of strings specifying which logs to print. + job_name (str): Training job name. + experiment_config (dict[str, str]): Experiment management configuration. + + Returns: + None or pipeline step arguments + """ + # Handle recipe upload and input channel creation if we have a recipe + if ( + self.is_nova_recipe is not None + and self.is_nova_recipe + and hasattr(self, "training_recipe_file") + and self.training_recipe_file + ): + # Upload the recipe to S3 if it hasn't been uploaded yet + if not hasattr(self, "recipe_s3_uri") or not self.recipe_s3_uri: + self.recipe_s3_uri = self._upload_recipe_to_s3( + self.sagemaker_session, self.training_recipe_file.name + ) + + # Prepare inputs dictionary + from sagemaker.inputs import TrainingInput + + if inputs is None: + inputs = {} + elif not isinstance(inputs, dict): + inputs = {"training": inputs} + + # Add the recipe channel + recipe_channel_name = "recipe" + inputs[recipe_channel_name] = TrainingInput( + s3_data=os.path.dirname(self.recipe_s3_uri), input_mode="File" + ) + + # Update hyperparameters to reference the recipe location in the container + recipe_filename = os.path.basename(self.training_recipe_file.name) + + self._hyperparameters.update( + { + "sagemaker_recipe_local_path": f"/opt/ml/input/data/{recipe_channel_name}/{recipe_filename}", + } + ) + return super(PyTorch, self).fit( + inputs=inputs, + wait=wait, + logs=logs, + job_name=job_name, + experiment_config=experiment_config, + ) + def create_model( self, model_server_workers=None, @@ -604,155 +847,209 @@ def _prepare_init_params_from_job_description(cls, job_details, model_channel_na return init_params - @classmethod - def _setup_for_training_recipe(cls, training_recipe, recipe_overrides, source_dir, kwargs): - """Performs training recipe specific setup and returns recipe specific args. + # The old class methods have been replaced by static methods and module-level functions - Updates kwargs and returns a dictionary of args to use for estimator - initialization and setup when using a training recipe. Updates the paths in - the recipe for Sagemaker Jobs environment. + @staticmethod + def _recipe_load(training_recipe, recipe_launcher_dir, training_recipes_cfg): + """Load the recipe from file path, URL, or predefined recipe. Args: - training_recipe (str): A recipe which is a local file path, a url or a - sagemaker training recipe. - recipe_overrides (Dict): Dictionary specifying key values to override in the - source_dir (str): Path (absolute, or relative) to a directory where to copy - the scripts for training recipe. requirements.txt can also - go here. - kwargs (dict): Dictionary of args used for estimator initializaiton. + training_recipe (str): Path to the training recipe. + recipe_launcher_dir (str): Path to the recipe launcher directory. + training_recipes_cfg (dict): Training recipes configuration. + Returns: - dict containing arg values for estimator initialization and setup. + tuple: Recipe name and loaded recipe. + Raises: + ValueError: If the recipe cannot be fetched or found. """ - if kwargs.get("sagemaker_session") is not None: - region_name = kwargs.get("sagemaker_session").boto_region_name - else: - region_name = Session().boto_region_name - - training_recipes_cfg_filename = os.path.join( - os.path.dirname(__file__), "training_recipes.json" - ) - with open(training_recipes_cfg_filename) as training_recipes_cfg_file: - training_recipes_cfg = json.load(training_recipes_cfg_file) - - if recipe_overrides is None: - recipe_overrides = dict() - recipe_train_dir = tempfile.TemporaryDirectory(prefix="training_") - recipe_launcher_dir = tempfile.TemporaryDirectory(prefix="launcher_") - args = dict() - if source_dir is None: - args["source_dir"] = "." - else: - if not os.path.exists(source_dir): - raise ValueError( - "When using training_recipe, source_dir must be a local directory." - ) - args["source_dir"] = source_dir - recipe_name = os.path.splitext(os.path.basename(training_recipe))[0] temp_local_recipe = tempfile.NamedTemporaryFile(prefix=recipe_name, suffix=".yaml").name - if training_recipe.endswith(".yaml"): - if os.path.isfile(training_recipe): - shutil.copy(training_recipe, temp_local_recipe) + + try: + if training_recipe.endswith(".yaml"): + _recipe_load_from_yaml(training_recipe, temp_local_recipe) else: - try: - urlretrieve(training_recipe, temp_local_recipe) - except Exception as e: - raise ValueError( - f"Could not fetch the provided recipe {training_recipe}: exception {str(e)}" - ) + _recipe_load_predefined( + training_recipe, recipe_launcher_dir, temp_local_recipe, training_recipes_cfg + ) + + recipe = OmegaConf.load(temp_local_recipe) + os.unlink(temp_local_recipe) + return recipe_name, recipe + except Exception as e: + if os.path.exists(temp_local_recipe): + os.unlink(temp_local_recipe) + raise e + + @staticmethod + def _device_get_image_uri(args, device_type, recipe_config, region_name, recipe): + """Get the appropriate image URI based on device type. + + Args: + args (dict): Arguments dictionary. + device_type (str): Device type (gpu, trainium, or cpu). + recipe_config (dict): Training recipes configuration. + region_name (str): AWS region name. + recipe (OmegaConf): Recipe configuration. + + Returns: + str: Image URI or None if no image URI was found. + """ + if "default_image_uri" in args: + logger.debug("Image URI already exists") + return args["default_image_uri"] + elif device_type == "gpu": + logger.info("Using GPU training image") + return _get_training_recipe_image_uri(recipe_config.get("gpu_image"), region_name) + elif device_type == "trainium": + logger.info("Using Trainium training image") + return _get_training_recipe_image_uri(recipe_config.get("neuron_image"), region_name) else: - launcher_repo = os.environ.get( - "TRAINING_LAUNCHER_GIT", None - ) or training_recipes_cfg.get("launcher_repo") - _run_clone_command(launcher_repo, recipe_launcher_dir.name) - recipe = os.path.join( - recipe_launcher_dir.name, - "recipes_collection", - "recipes", - training_recipe + ".yaml", - ) - if os.path.isfile(recipe): - shutil.copy(recipe, temp_local_recipe) + return None + + @staticmethod + def _recipe_setup_nova(args, recipe): + """Set up configuration for Nova recipes. + + Args: + args (dict): Arguments dictionary. + recipe (OmegaConf): Recipe configuration. + kwargs (dict): Dictionary of keyword arguments. + """ + run_config = recipe.get("run", {}) + model_name_or_path = run_config.get("model_name_or_path") + + # Set hyperparameters based on model_name_or_path + if model_name_or_path: + if model_name_or_path.startswith("s3://"): + args["hyperparameters"]["base_model_location"] = model_name_or_path else: - raise ValueError(f"Recipe {training_recipe} not found.") + args["hyperparameters"]["base_model"] = model_name_or_path + + args["entry_point"] = None + args["source_dir"] = None - recipe = OmegaConf.load(temp_local_recipe) - os.unlink(temp_local_recipe) - recipe = OmegaConf.merge(recipe, recipe_overrides) + @staticmethod + def _device_validate_and_get_type(kwargs, recipe): + """Validate instance type and determine device type. + + Args: + kwargs (dict): Dictionary of keyword arguments. + recipe (OmegaConf): Recipe configuration. + Returns: + str: Device type (gpu, trainium, or cpu). + + Raises: + ValueError: If instance_type is not provided or recipe is invalid. + """ if "instance_type" not in kwargs: raise ValueError("Must pass instance type to estimator when using training recipes.") + + if not _is_nova_recipe(recipe) and "trainer" not in recipe: + raise ValueError("Supplied recipe does not contain required field trainer.") + instance_type = kwargs["instance_type"].split(".")[1] if instance_type.startswith(("p", "g")): - device_type = "gpu" + return "gpu" elif instance_type.startswith("trn"): - device_type = "trainium" + return "trainium" else: - device_type = "cpu" + return "cpu" - if "trainer" not in recipe: - raise ValueError("Supplied recipe does not contain required field trainer.") - if "instance_count" in kwargs and "num_nodes" in recipe["trainer"]: - logger.warning( - "Using instance_count argument to estimator to set number " - " of nodes. Ignoring trainer -> num_nodes in recipe." - ) - if "instance_count" not in kwargs: - if "num_nodes" not in recipe["trainer"]: - raise ValueError( - "Must set either instance_count argument for estimator or" - "set trainer -> num_nodes in recipe." + @staticmethod + def _device_handle_instance_count(kwargs, recipe): + """Handle instance count configuration. + + Args: + kwargs (dict): Dictionary of keyword arguments. + recipe (OmegaConf): Recipe configuration. + + Raises: + ValueError: If instance_count is not provided and cannot be found in the recipe. + """ + # Check if instance_count is already provided in kwargs + + is_nova = _is_nova_recipe(recipe) + if "instance_count" in kwargs: + # Warn if there are conflicting configurations in the recipe + if "num_nodes" in recipe.get("trainer", {}): + logger.warning( + "Using instance_count argument to estimator to set number " + "of nodes. Ignoring trainer -> num_nodes in recipe." ) + if is_nova and "replicas" in recipe.get("run", {}): + logger.warning( + "Using instance_count argument to estimator to set number " + "of nodes. Ignoring run -> replicas in recipe." + ) + return + + # Try to get instance_count from recipe + if "trainer" in recipe and "num_nodes" in recipe["trainer"]: kwargs["instance_count"] = recipe["trainer"]["num_nodes"] + return + + if is_nova and "run" in recipe and "replicas" in recipe["run"]: + kwargs["instance_count"] = recipe["run"]["replicas"] + return - # [TODO] Add image uris to image_uri_config/_.json and use image_uris.retrieve - # to retrieve the image uri below before we go GA. + # If we get here, we couldn't find instance_count anywhere + raise ValueError( + "Must set either instance_count argument for estimator or " + "set trainer -> num_nodes or run -> replicas in recipe for nova jobs." + ) + + @staticmethod + def _device_get_entry_point_script( + device_type, recipe_train_dir, recipe, source_dir, training_recipes_cfg + ): + """Get the entry point script based on device type. + + Args: + device_type (str): Device type (gpu, trainium, or cpu). + recipe_train_dir (str): Path to the recipe training directory. + recipe (OmegaConf): Recipe configuration. + source_dir (str): Path to the source directory. + training_recipes_cfg (dict): Training recipes configuration. + + Returns: + str: Path to the entry point script or None if not applicable. + """ if device_type == "gpu": adapter_repo = os.environ.get("TRAINING_ADAPTER_GIT", None) or training_recipes_cfg.get( "adapter_repo" ) - _run_clone_command(adapter_repo, recipe_train_dir.name) - script = _get_training_recipe_gpu_script( - recipe_train_dir.name, recipe, args["source_dir"] - ) - args["default_image_uri"] = _get_training_recipe_image_uri( - training_recipes_cfg.get("gpu_image"), region_name - ) - smp_options = { - "enabled": True, - "parameters": { - "placement_strategy": "cluster", - }, - } - args["distribution"] = { - "smdistributed": {"modelparallel": smp_options}, - "torch_distributed": {"enabled": True}, - } + _run_clone_command(adapter_repo, recipe_train_dir) + return _get_training_recipe_gpu_script(recipe_train_dir, recipe, source_dir) elif device_type == "trainium": - _run_clone_command(training_recipes_cfg.get("neuron_dist_repo"), recipe_train_dir.name) - script = _get_training_recipe_trainium_script(recipe_train_dir.name, args["source_dir"]) - args["default_image_uri"] = _get_training_recipe_image_uri( - training_recipes_cfg.get("neuron_image"), region_name - ) - args["distribution"] = { - "torch_distributed": {"enabled": True}, - } - else: + _run_clone_command(training_recipes_cfg.get("neuron_dist_repo"), recipe_train_dir) + return _get_training_recipe_trainium_script(recipe_train_dir, source_dir) + elif device_type == "cpu": raise ValueError( f"Devices of type {device_type} are not supported with training recipes." ) - args["entry_point"] = os.path.basename(script) + return None - recipe_train_dir.cleanup() - recipe_launcher_dir.cleanup() + def _recipe_resolve_and_save(self, recipe, recipe_name, source_dir): + """Resolve and save the final recipe configuration. - if "container" in recipe and not recipe["container"]: - logger.warning( - "Ignoring container from training_recipe. Use image_uri arg for estimator." - ) + Args: + recipe (OmegaConf): Recipe configuration. + recipe_name (str): Recipe name. + source_dir (str): Path to the source directory. + + Returns: + OmegaConf: Resolved recipe configuration. + Raises: + RuntimeError: If the recipe cannot be resolved. + """ _setup_omegaconf_resolvers() + + # Try different resolution strategies final_recipe = _try_resolve_recipe(recipe) if final_recipe is None: final_recipe = _try_resolve_recipe(recipe, "recipes") @@ -760,15 +1057,258 @@ def _setup_for_training_recipe(cls, training_recipe, recipe_overrides, source_di final_recipe = _try_resolve_recipe(recipe, "training") if final_recipe is None: raise RuntimeError("Could not resolve provided recipe.") - cls.training_recipe_file = tempfile.NamedTemporaryFile( - dir=args["source_dir"], + + # Save the resolved recipe - this sets an instance attribute + self.training_recipe_file = tempfile.NamedTemporaryFile( + dir=source_dir, prefix=recipe_name + "_", suffix=".yaml", ) - OmegaConf.save(config=final_recipe, f=cls.training_recipe_file.name) - args["hyperparameters"] = { - "config-path": ".", - "config-name": os.path.basename(cls.training_recipe_file.name), - } + OmegaConf.save(config=final_recipe, f=self.training_recipe_file.name) + + return final_recipe + + def _upload_recipe_to_s3(self, session, recipe_file_path): + """Upload the recipe file to S3. + + Args: + session (sagemaker.session.Session): SageMaker session. + recipe_file_path (str): Path to the recipe file. + + Returns: + str: S3 URI of the uploaded recipe file. + """ + bucket = session.default_bucket() + key_prefix = session.default_bucket_prefix + + recipe_filename = os.path.basename(recipe_file_path) + + readable_date = datetime.fromtimestamp(int(time.time())) + date_format = readable_date.strftime("%Y-%m-%d") + + if key_prefix != "None" and key_prefix is not None: + s3_key = f"{key_prefix}/recipes/{date_format}_{recipe_filename[:-5]}" + else: + s3_key = f"recipes/{date_format}_{recipe_filename[:-5]}" + + # Upload the recipe file to S3 + s3_uri = session.upload_data( + path=recipe_file_path, + bucket=bucket, + key_prefix=os.path.dirname(os.path.join(s3_key, recipe_filename)), + ) + + # Return the full S3 URI to the recipe file + return f"{s3_uri}" + + def _setup_for_training_recipe(self, training_recipe, recipe_overrides, source_dir, kwargs): + """Performs training recipe specific setup and returns recipe specific args. + + Updates kwargs and returns a dictionary of args to use for estimator + initialization and setup when using a training recipe. + + Args: + training_recipe (str): A recipe which is a local file path, a url or a + sagemaker training recipe. + recipe_overrides (Dict): Dictionary specifying key values to override in the + training recipe. + source_dir (str): Path (absolute, or relative) to a directory where to copy + the scripts for training recipe. + kwargs (dict): Dictionary of args used for estimator initialization. + + Returns: + dict containing arg values for estimator initialization and setup. + """ + region_name = _recipe_get_region_name(kwargs) + training_recipes_cfg = _recipe_load_config() + recipe_overrides = recipe_overrides or {} + + # Create temporary directories for recipe processing + with ( + tempfile.TemporaryDirectory(prefix="training_") as recipe_train_dir, + tempfile.TemporaryDirectory(prefix="launcher_") as recipe_launcher_dir, + ): + # Load and process the recipe + recipe_name, recipe = PyTorch._recipe_load( + training_recipe, recipe_launcher_dir, training_recipes_cfg + ) + + # Merge with overrides + recipe = OmegaConf.merge(recipe, recipe_overrides) + + self.is_nova_recipe = _is_nova_recipe(recipe) + if self.is_nova_recipe: + return self._setup_for_nova_recipe( + recipe, + recipe_name, + source_dir, + kwargs, + ) + else: + return self._setup_for_standard_recipe( + recipe, + recipe_name, + source_dir, + kwargs, + recipe_train_dir, + training_recipes_cfg, + region_name, + ) + + def _setup_for_nova_recipe( + self, + recipe, + recipe_name, + source_dir, + kwargs, + ): + """Set up configuration specifically for Nova recipes. + + Args: + recipe (OmegaConf): Recipe configuration. + recipe_name (str): Recipe name. + source_dir (str): Path to the source directory. + kwargs (dict): Dictionary of keyword arguments. + + Returns: + dict: Arguments dictionary for estimator initialization. + """ + # Initialize args + args = _recipe_initialize_args(source_dir) + + # Set up Nova-specific configuration + run_config = recipe.get("run", {}) + model_name_or_path = run_config.get("model_name_or_path") + + # Set hyperparameters based on model_name_or_path + if model_name_or_path: + if model_name_or_path.startswith("s3://"): + args["hyperparameters"]["base_model_location"] = model_name_or_path + else: + args["hyperparameters"]["base_model"] = model_name_or_path + + args["entry_point"] = None + args["source_dir"] = None + args["distribution"] = {} + + logger.info("Remote debugging, profiler and debugger hooks are disabled for Nova recipes.") + kwargs["enable_remote_debug"] = False + kwargs["disable_profiler"] = True + kwargs["debugger_hook_config"] = False + + # Handle instance count for Nova recipes + if "instance_count" in kwargs: + if "replicas" in recipe.get("run", {}): + logger.warning( + "Using instance_count argument to estimator to set number " + "of nodes. Ignoring run -> replicas in recipe." + ) + elif "run" in recipe and "replicas" in recipe["run"]: + kwargs["instance_count"] = recipe["run"]["replicas"] + else: + raise ValueError( + "Must set either instance_count argument for estimator or " + "set run -> replicas in recipe for nova jobs." + ) + + training_config = recipe.get("training_config", {}) + is_distillation = training_config.get("distillation_data", {}) + if bool(is_distillation): + args["hyperparameters"]["distillation_data"] = is_distillation + args["hyperparameters"]["role_arn"] = kwargs["role"] + kms_key = training_config.get("kms_key") + if kms_key is None: + ValueError( + 'Nova distillation job recipe requires "kms_key" field in "training_config"' + ) + args["hyperparameters"]["kms_key"] = kms_key + + # Resolve and save the final recipe + self._recipe_resolve_and_save(recipe, recipe_name, args["source_dir"]) + + return args + + def _setup_for_standard_recipe( + self, + recipe, + recipe_name, + source_dir, + kwargs, + recipe_train_dir, + training_recipes_cfg, + region_name, + ): + """Set up configuration for standard (non-Nova) recipes. + + Args: + recipe (OmegaConf): Recipe configuration. + recipe_name (str): Recipe name. + source_dir (str): Path to the source directory. + kwargs (dict): Dictionary of keyword arguments. + recipe_train_dir (str): Path to the recipe training directory. + training_recipes_cfg (dict): Training recipes configuration. + region_name (str): AWS region name. + + Returns: + dict: Arguments dictionary for estimator initialization. + """ + # Initialize args + args = _recipe_initialize_args(source_dir) + + # Validate recipe structure + if "trainer" not in recipe: + raise ValueError("Supplied recipe does not contain required field trainer.") + + # Handle instance count for standard recipes + if "instance_count" in kwargs: + if "num_nodes" in recipe.get("trainer", {}): + logger.warning( + "Using instance_count argument to estimator to set number " + "of nodes. Ignoring trainer -> num_nodes in recipe." + ) + elif "trainer" in recipe and "num_nodes" in recipe["trainer"]: + kwargs["instance_count"] = recipe["trainer"]["num_nodes"] + else: + raise ValueError( + "Must set either instance_count argument for estimator or " + "set trainer -> num_nodes in recipe." + ) + + # Determine device type + device_type = PyTorch._device_validate_and_get_type(kwargs, recipe) + + # Get image URI + image_uri = PyTorch._device_get_image_uri( + args, device_type, training_recipes_cfg, region_name, recipe + ) + args["default_image_uri"] = image_uri if image_uri is not None else "" + + # Setup device-specific configuration + args["distribution"] = _device_get_distribution(device_type) + + # Set entry point if not already set + if "entry_point" not in args: + script = PyTorch._device_get_entry_point_script( + device_type, recipe_train_dir, recipe, args["source_dir"], training_recipes_cfg + ) + if script: + args["entry_point"] = os.path.basename(script) + + # Handle container configuration + if "container" in recipe and not recipe["container"]: + logger.warning( + "Ignoring container from training_recipe. Use image_uri arg for estimator." + ) + + # Resolve and save the final recipe + self._recipe_resolve_and_save(recipe, recipe_name, args["source_dir"]) + + # Update hyperparameters with recipe configuration + args["hyperparameters"].update( + { + "config-path": ".", + "config-name": os.path.basename(self.training_recipe_file.name), + } + ) return args diff --git a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py index 585a4d2745..a58b1f641e 100644 --- a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py +++ b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py @@ -14,9 +14,10 @@ from __future__ import absolute_import import pytest -from unittest.mock import patch +from unittest.mock import patch, MagicMock import yaml +from omegaconf import OmegaConf from urllib.request import urlretrieve from tempfile import NamedTemporaryFile @@ -27,6 +28,8 @@ _configure_gpu_args, _configure_trainium_args, _get_trainining_recipe_gpu_model_name_and_script, + _is_nova_recipe, + _get_args_from_nova_recipe, ) from sagemaker.modules.utils import _run_clone_command_silent from sagemaker.modules.configs import Compute @@ -181,6 +184,35 @@ def test_get_args_from_recipe_compute( assert args is None +@patch("sagemaker.modules.train.sm_recipes.utils._get_args_from_nova_recipe") +def test_get_args_from_recipe_with_nova_and_role(mock_get_args_from_nova_recipe, temporary_recipe): + # Set up mock return value + mock_args = {"hyperparameters": {}} + mock_dir = MagicMock() + mock_get_args_from_nova_recipe.return_value = (mock_args, mock_dir) + + # Create a Nova recipe with distillation data + recipe = OmegaConf.create( + {"training_config": {"distillation_data": True, "kms_key": "alias/my-kms-key"}} + ) + compute = Compute(instance_type="ml.g5.xlarge") + role = "arn:aws:iam::123456789012:role/SageMakerRole" + + # Mock the Nova recipe detection to return True + with patch("sagemaker.modules.train.sm_recipes.utils._is_nova_recipe", return_value=True): + _get_args_from_recipe( + training_recipe=recipe, + compute=compute, + region_name="us-west-2", + recipe_overrides=None, + requirements=None, + role=role, + ) + + # Verify _get_args_from_nova_recipe was called with the role parameter + mock_get_args_from_nova_recipe.assert_called_once_with(recipe, compute, role=role) + + @pytest.mark.parametrize( "test_case", [ @@ -213,3 +245,199 @@ def test_get_trainining_recipe_gpu_model_name_and_script(test_case): model_base_name, script = _get_trainining_recipe_gpu_model_name_and_script(model_type) assert model_base_name == test_case["model_base_name"] assert script == test_case["script"] + + +@pytest.mark.parametrize( + "test_case", + [ + { + "recipe": { + "run": { + "model_type": "amazon.nova", + "model_name_or_path": "some-model", + } + }, + "is_nova": True, + }, + { + "recipe": { + "run": { + "model_type": "amazon.nova.other", + "model_name_or_path": "some-model", + } + }, + "is_nova": True, + }, + {"recipe": {"run": {"model_type": "amazon.nova.other"}}, "is_nova": False}, + { + "recipe": {"run": {"model_type": "other.model", "model_name_or_path": "some-model"}}, + "is_nova": False, + }, + { + "recipe": {"training_config": {"distillation_data": "s3://bucket/distillation-data"}}, + "is_nova": True, + }, + { + "recipe": {"training_config": {"some_other_field": "value"}}, + "is_nova": False, + }, + ], + ids=[ + "nova_model", + "nova_model_subtype", + "nova_missing_model_path", + "non_nova_model", + "distillation_data", + "no_distillation_data", + ], +) +def test_is_nova_recipe(test_case): + recipe = OmegaConf.create(test_case["recipe"]) + is_nova = _is_nova_recipe(recipe) + assert is_nova == test_case["is_nova"] + + +@pytest.mark.parametrize( + "test_case", + [ + { + "recipe": { + "run": {"model_type": "amazon.nova", "model_name_or_path": "dummy-test"}, + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "expected_args": { + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "hyperparameters": {"base_model": "dummy-test"}, + "training_image": None, + "source_code": None, + "distributed": None, + }, + }, + { + "recipe": { + "run": { + "model_type": "amazon.nova", + "model_name_or_path": "s3://bucket/path/to/model", + }, + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "expected_args": { + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "hyperparameters": {"base_model_location": "s3://bucket/path/to/model"}, + "training_image": None, + "source_code": None, + "distributed": None, + }, + }, + { + "recipe": { + "run": { + "model_type": "amazon.nova", + "model_name_or_path": "s3://bucket/path/to/model", + "replicas": 4, + }, + }, + "compute": Compute(instance_type="ml.m5.xlarge"), + "expected_args": { + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=4), + "hyperparameters": {"base_model_location": "s3://bucket/path/to/model"}, + "training_image": None, + "source_code": None, + "distributed": None, + }, + }, + { + "recipe": { + "run": { + "model_type": "amazon.nova", + "model_name_or_path": "s3://bucket/path/to/model", + "replicas": 2, + }, + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=4), + "expected_args": { + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=4), + "hyperparameters": {"base_model_location": "s3://bucket/path/to/model"}, + "training_image": None, + "source_code": None, + "distributed": None, + }, + }, + ], +) +def test_get_args_from_nova_recipe(test_case): + recipe = OmegaConf.create(test_case["recipe"]) + args, _ = _get_args_from_nova_recipe(recipe=recipe, compute=test_case["compute"]) + assert args == test_case["expected_args"] + + +@pytest.mark.parametrize( + "test_case", + [ + { + "recipe": { + "training_config": { + "distillation_data": "s3://bucket/distillation-data", + "kms_key": "alias/my-kms-key", + } + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "role": "arn:aws:iam::123456789012:role/SageMakerRole", + "expected_args": { + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "hyperparameters": { + "distillation_data": "s3://bucket/distillation-data", + "role_arn": "arn:aws:iam::123456789012:role/SageMakerRole", + "kms_key": "alias/my-kms-key", + }, + "training_image": None, + "source_code": None, + "distributed": None, + }, + }, + ], +) +def test_get_args_from_nova_recipe_with_distillation(test_case): + recipe = OmegaConf.create(test_case["recipe"]) + args, _ = _get_args_from_nova_recipe( + recipe=recipe, compute=test_case["compute"], role=test_case["role"] + ) + assert args == test_case["expected_args"] + + +@pytest.mark.parametrize( + "test_case", + [ + { + "recipe": { + "training_config": { + "distillation_data": "s3://bucket/distillation-data", + # Missing kms_key + } + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + "role": "arn:aws:iam::123456789012:role/SageMakerRole", + }, + { + "recipe": { + "training_config": { + "distillation_data": "s3://bucket/distillation-data", + "kms_key": "alias/my-kms-key", + } + }, + "compute": Compute(instance_type="ml.m5.xlarge", instance_count=2), + # Missing role + "role": None, + }, + ], + ids=[ + "missing_kms_key", + "missing_role", + ], +) +def test_get_args_from_nova_recipe_with_distillation_errors(test_case): + recipe = OmegaConf.create(test_case["recipe"]) + with pytest.raises(ValueError): + _get_args_from_nova_recipe( + recipe=recipe, compute=test_case["compute"], role=test_case.get("role") + ) diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 23ea167ecf..184f9c30da 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -21,6 +21,7 @@ import pytest from pydantic import ValidationError from unittest.mock import patch, MagicMock, ANY, mock_open +from tempfile import NamedTemporaryFile from sagemaker import image_uris from sagemaker_core.main.resources import TrainingJob @@ -43,6 +44,7 @@ DISTRIBUTED_JSON, SOURCE_CODE_JSON, TRAIN_SCRIPT, + SM_RECIPE_CONTAINER_PATH, ) from sagemaker.modules.configs import ( Compute, @@ -1339,3 +1341,91 @@ def test_input_merge(mock_training_job, modules_session): input_mode="File", ), ] + + +@patch("sagemaker.modules.train.model_trainer._get_unique_name") +@patch("sagemaker.modules.train.model_trainer.TrainingJob") +def test_nova_recipe(mock_training_job, mock_unique_name, modules_session): + def mock_upload_data(path, bucket, key_prefix): + if os.path.isfile(path): + file_name = os.path.basename(path) + return f"s3://{bucket}/{key_prefix}/{file_name}" + else: + return f"s3://{bucket}/{key_prefix}" + + unique_name = "base-job-0123456789" + base_name = "base-job" + + modules_session.upload_data.side_effect = mock_upload_data + mock_unique_name.return_value = unique_name + + recipe_data = { + "run": { + "name": "dummy-model", + "model_type": "amazon.nova", + "model_name_or_path": "dummy-model", + } + } + with NamedTemporaryFile(suffix=".yaml", delete=False) as recipe: + with open(recipe.name, "w") as file: + yaml.dump(recipe_data, file) + + trainer = ModelTrainer.from_recipe( + training_recipe=recipe.name, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + training_image=DEFAULT_IMAGE, + base_job_name=base_name, + ) + + assert trainer._is_nova_recipe + + trainer.train() + mock_training_job.create.assert_called_once() + assert mock_training_job.create.call_args.kwargs["hyper_parameters"] == { + "base_model": "dummy-model", + "sagemaker_recipe_local_path": SM_RECIPE_CONTAINER_PATH, + } + + default_base_path = f"s3://{DEFAULT_BUCKET}/{DEFAULT_BUCKET_PREFIX}/{base_name}" + assert mock_training_job.create.call_args.kwargs["input_data_config"] == [ + Channel( + channel_name="recipe", + data_source=DataSource( + s3_data_source=S3DataSource( + s3_data_type="S3Prefix", + s3_uri=f"{default_base_path}/{unique_name}/input/recipe/recipe.yaml", + s3_data_distribution_type="FullyReplicated", + ) + ), + input_mode="File", + ) + ] + + +def test_nova_recipe_with_distillation(modules_session): + recipe_data = {"training_config": {"distillation_data": "true", "kms_key": "alias/my-kms-key"}} + + with NamedTemporaryFile(suffix=".yaml", delete=False) as recipe: + with open(recipe.name, "w") as file: + yaml.dump(recipe_data, file) + + # Create ModelTrainer from recipe + trainer = ModelTrainer.from_recipe( + training_recipe=recipe.name, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + training_image=DEFAULT_IMAGE, + ) + + # Verify that the hyperparameters were set correctly + assert trainer.hyperparameters == { + "distillation_data": "true", + "role_arn": DEFAULT_ROLE, + "kms_key": "alias/my-kms-key", + } + + # Clean up the temporary file + os.unlink(recipe.name) diff --git a/tests/unit/test_pytorch_nova.py b/tests/unit/test_pytorch_nova.py new file mode 100644 index 0000000000..f78bdcae7d --- /dev/null +++ b/tests/unit/test_pytorch_nova.py @@ -0,0 +1,753 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import +import pytest +import tempfile +from mock import Mock, patch +from omegaconf import OmegaConf + +from sagemaker.estimator import EstimatorBase + +from sagemaker.pytorch import PyTorch +from sagemaker.pytorch.estimator import ( + _is_nova_recipe, + _device_get_distribution, +) +from sagemaker.inputs import TrainingInput +from sagemaker.session_settings import SessionSettings + +# Constants for testing +ROLE = "Dummy" +REGION = "us-west-2" +BUCKET_NAME = "mybucket" +INSTANCE_COUNT = 1 +INSTANCE_TYPE = "ml.c4.4xlarge" +INSTANCE_TYPE_GPU = "ml.p4d.24xlarge" +IMAGE_URI = "sagemaker-pytorch" + + +@pytest.fixture(name="sagemaker_session") +def fixture_sagemaker_session(): + boto_mock = Mock(name="boto_session", region_name=REGION) + session = Mock( + name="sagemaker_session", + boto_session=boto_mock, + boto_region_name=REGION, + config=None, + local_mode=False, + s3_resource=None, + s3_client=None, + settings=SessionSettings(), + default_bucket_prefix=None, + ) + session.default_bucket = Mock(name="default_bucket", return_value=BUCKET_NAME) + session.expand_role = Mock(name="expand_role", return_value=ROLE) + session.upload_data = Mock(return_value="s3://mybucket/recipes/nova-recipe.yaml") + session.sagemaker_config = {} + return session + + +def test_is_nova_recipe(): + """Test that _is_nova_recipe correctly identifies Nova recipes.""" + # Valid Nova recipe + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foo-bar", + "model_name_or_path": "foo-bar/foo-bar123", + } + } + ) + assert _is_nova_recipe(recipe) is True + + # Not a Nova recipe - missing run section + recipe = OmegaConf.create( + { + "trainer": { + "model_type": "amazon.nova.foo-bar", + "model_name_or_path": "foo-bar/foo-bar123", + } + } + ) + assert _is_nova_recipe(recipe) is False + + # Not a Nova recipe - wrong model_type + recipe = OmegaConf.create( + {"run": {"model_type": "foo-bar3", "model_name_or_path": "foo-bar/foo-bar123"}} + ) + assert _is_nova_recipe(recipe) is False + + # Not a Nova recipe - missing model_name_or_path + recipe = OmegaConf.create({"run": {"model_type": "amazon.nova.foo-bar"}}) + assert _is_nova_recipe(recipe) is False + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_resolve_and_save") +def test_setup_for_nova_recipe_with_model_name(mock_resolve_save, sagemaker_session): + """Test that _setup_for_nova_recipe correctly sets up hyperparameters for Nova recipes with model name.""" + # Create a mock recipe + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foobar3", + "model_name_or_path": "foobar/foobar-3-8b", + "replicas": 4, + } + } + ) + + # Setup the expected return value + expected_args = { + "hyperparameters": {"base_model": "foobar/foobar-3-8b"}, + "entry_point": None, + "source_dir": None, + "distribution": {}, + "default_image_uri": IMAGE_URI, + } + + # Mock the _setup_for_nova_recipe method + with patch( + "sagemaker.pytorch.estimator.PyTorch._setup_for_nova_recipe", return_value=expected_args + ) as mock_nova_setup: + # Create the PyTorch estimator with mocked _recipe_load + with patch( + "sagemaker.pytorch.estimator.PyTorch._recipe_load", return_value=("nova_recipe", recipe) + ): + # Mock _recipe_resolve_and_save to return our recipe + mock_resolve_save.return_value = recipe + + pytorch = PyTorch( + training_recipe="nova_recipe", + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + ) + + # Check that the Nova recipe was correctly identified + assert pytorch.is_nova_recipe is True + + # Verify _setup_for_nova_recipe was called + mock_nova_setup.assert_called_once() + call_args = mock_nova_setup.call_args + assert len(call_args[0]) >= 2 # Check that at least recipe and recipe_name were passed + assert call_args[0][0] == recipe # first arg should be recipe + assert call_args[0][1] == "nova_recipe" # second arg should be recipe_name + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_resolve_and_save") +def test_setup_for_nova_recipe_with_s3_path(mock_resolve_save, sagemaker_session): + """Test that _setup_for_nova_recipe correctly sets up hyperparameters for Nova recipes with S3 path.""" + # Create a mock recipe with S3 path + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foobar3", + "model_name_or_path": "s3://mybucket/models/foobar3", + "replicas": 4, + } + } + ) + + # Setup the expected return value + expected_args = { + "hyperparameters": {"base_model_location": "s3://mybucket/models/foobar3"}, + "entry_point": None, + "source_dir": None, + "distribution": {}, + "default_image_uri": IMAGE_URI, + } + + # Mock the _setup_for_nova_recipe method + with patch( + "sagemaker.pytorch.estimator.PyTorch._setup_for_nova_recipe", return_value=expected_args + ) as mock_nova_setup: + # Create the PyTorch estimator with mocked _recipe_load + with patch( + "sagemaker.pytorch.estimator.PyTorch._recipe_load", return_value=("nova_recipe", recipe) + ): + # Mock _recipe_resolve_and_save to return our recipe + mock_resolve_save.return_value = recipe + + pytorch = PyTorch( + training_recipe="nova_recipe", + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + ) + + # Check that the Nova recipe was correctly identified + assert pytorch.is_nova_recipe is True + + # Verify _setup_for_nova_recipe was called + mock_nova_setup.assert_called_once() + + # Verify that hyperparameters were set correctly + assert ( + pytorch._hyperparameters.get("base_model_location") + == "s3://mybucket/models/foobar3" + ) + + +def test_device_handle_instance_count_with_nova_replicas(): + """Test that _device_handle_instance_count correctly gets instance_count from Nova recipe replicas.""" + # Create mock recipe with replicas + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foobar3", + "model_name_or_path": "foobar/foobar-3-8b", + "replicas": 4, + } + } + ) + + # Test with no instance_count in kwargs + kwargs = {} + PyTorch._device_handle_instance_count(kwargs, recipe) + assert kwargs["instance_count"] == 4 + + +def test_device_handle_instance_count_with_nova_no_replicas(): + """Test that _device_handle_instance_count raises an error when no instance_count or replicas are provided.""" + # Create mock recipe without replicas + recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Test with no instance_count in kwargs + kwargs = {} + with pytest.raises(ValueError) as error: + PyTorch._device_handle_instance_count(kwargs, recipe) + + assert "Must set either instance_count argument for estimator or" in str(error) + + +@patch("sagemaker.pytorch.estimator.logger.warning") +def test_device_handle_instance_count_with_nova_both_provided(mock_warning): + """Test that _device_handle_instance_count warns when both instance_count and replicas are provided.""" + # Create mock recipe with replicas + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foobar3", + "model_name_or_path": "foobar/foobar-3-8b", + "replicas": 4, + } + } + ) + + # Test with instance_count in kwargs + kwargs = {"instance_count": 2} + PyTorch._device_handle_instance_count(kwargs, recipe) + + # Verify warning was logged + mock_warning.assert_called_with( + "Using instance_count argument to estimator to set number " + "of nodes. Ignoring run -> replicas in recipe." + ) + + # Verify instance_count wasn't changed + assert kwargs["instance_count"] == 2 + + +def test_device_validate_and_get_type_with_nova(): + """Test that _device_validate_and_get_type works correctly with Nova recipes.""" + # Create mock recipe + recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Test with GPU instance type + kwargs = {"instance_type": INSTANCE_TYPE_GPU} + device_type = PyTorch._device_validate_and_get_type(kwargs, recipe) + assert device_type == "gpu" + + # Test with CPU instance type + kwargs = {"instance_type": INSTANCE_TYPE} + device_type = PyTorch._device_validate_and_get_type(kwargs, recipe) + assert device_type == "cpu" + + +def test_device_validate_and_get_type_no_instance_type(): + """Test that _device_validate_and_get_type raises an error when no instance_type is provided.""" + # Create mock recipe + recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Test with no instance_type + kwargs = {} + with pytest.raises(ValueError) as error: + PyTorch._device_validate_and_get_type(kwargs, recipe) + + assert "Must pass instance type to estimator" in str(error) + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_load") +@patch("time.time", return_value=1714500000) # May 1, 2024 +def test_upload_recipe_to_s3(mock_time, mock_recipe_load, sagemaker_session): + """Test that _upload_recipe_to_s3 correctly uploads the recipe file to S3.""" + # Create a mock recipe that will be identified as a Nova recipe + mock_recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Set up the mock to return a recipe name and the mock recipe + mock_recipe_load.return_value = ("nova_recipe", mock_recipe) + + # Setup + pytorch = PyTorch( + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + training_recipe="nova_recipe", + ) + + # Set Nova recipe attributes + pytorch.is_nova_recipe = True + + # Create a temporary file to use as the recipe file + with tempfile.NamedTemporaryFile(suffix=".yaml") as temp_file: + # Test uploading the recipe file to S3 + s3_uri = pytorch._upload_recipe_to_s3(sagemaker_session, temp_file.name) + + # Verify the upload_data method was called with the correct parameters + sagemaker_session.upload_data.assert_called_once() + + # Check that the S3 URI is returned correctly + assert s3_uri == sagemaker_session.upload_data.return_value + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_load") +@patch("tempfile.NamedTemporaryFile") +@patch("omegaconf.OmegaConf.save") +@patch("sagemaker.pytorch.estimator._try_resolve_recipe") +def test_recipe_resolve_and_save( + mock_try_resolve, mock_save, mock_temp_file, mock_recipe_load, sagemaker_session +): + """Test that _recipe_resolve_and_save correctly resolves an`d saves the recipe.""" + # Create a mock recipe that will be identified as a Nova recipe + mock_recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Set up the mock to return a recipe name and the mock recipe + mock_recipe_load.return_value = ("nova_recipe", mock_recipe) + + # Setup + pytorch = PyTorch( + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + training_recipe="nova_recipe", + ) + + # Set Nova recipe attributes + pytorch.is_nova_recipe = True + + # Mock the temporary file + mock_temp_file_instance = Mock() + mock_temp_file_instance.name = "/tmp/nova-recipe_12345.yaml" + mock_temp_file.return_value = mock_temp_file_instance + + # Create mock recipe + recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Mock the recipe resolution + mock_try_resolve.side_effect = [recipe, None, None] + + # Call the _recipe_resolve_and_save method + result = pytorch._recipe_resolve_and_save(recipe, "nova-recipe", ".") + + # Verify the recipe was resolved and saved + mock_try_resolve.assert_called_with(recipe) + mock_save.assert_called_with(config=recipe, f=mock_temp_file_instance.name) + + # Verify the result is the resolved recipe + assert result == recipe + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_load") +@patch("sagemaker.pytorch.estimator.Framework.fit") +def test_fit_with_nova_recipe_s3_upload(mock_framework_fit, mock_recipe_load, sagemaker_session): + """Test that fit correctly uploads the recipe to S3 and adds it to the inputs.""" + # Create a mock recipe that will be identified as a Nova recipe + mock_recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar", "model_name_or_path": "foobar/foobar123"}} + ) + + # Set up the mock to return a recipe name and the mock recipe + mock_recipe_load.return_value = ("nova_recipe", mock_recipe) + + # Create a PyTorch estimator with a Nova recipe + with tempfile.NamedTemporaryFile(suffix=".yaml") as temp_file: + pytorch = PyTorch( + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + training_recipe="nova_recipe", + ) + + # Set Nova recipe attributes + pytorch.is_nova_recipe = True + pytorch.training_recipe_file = temp_file + + # Mock the _upload_recipe_to_s3 method + with patch.object(pytorch, "_upload_recipe_to_s3") as mock_upload_recipe: + mock_upload_recipe.return_value = "s3://mybucket/recipes/nova-recipe.yaml" + + # Call the fit method + pytorch.fit() + + # Verify the upload_recipe_to_s3 method was called + mock_upload_recipe.assert_called_once_with(sagemaker_session, temp_file.name) + + # Verify the fit method was called with the recipe channel + call_args = mock_framework_fit.call_args[1] + assert "inputs" in call_args + assert "recipe" in call_args["inputs"] + + # Verify the hyperparameters were updated with the recipe path + assert "sagemaker_recipe_local_path" in pytorch._hyperparameters + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_load") +@patch("sagemaker.pytorch.estimator.PyTorch._upload_recipe_to_s3") +@patch("sagemaker.pytorch.estimator.Framework.fit") +def test_fit_with_nova_recipe_and_inputs( + mock_framework_fit, mock_upload_recipe, mock_recipe_load, sagemaker_session +): + """Test that fit correctly handles Nova recipes with additional inputs.""" + # Create a mock recipe that will be identified as a Nova recipe + mock_recipe = OmegaConf.create( + {"run": {"model_type": "amazon.nova.foobar3", "model_name_or_path": "foobar/foobar-3-8b"}} + ) + + # Set up the mock to return a recipe name and the mock recipe + mock_recipe_load.return_value = ("nova_recipe", mock_recipe) + mock_upload_recipe.return_value = "s3://mybucket/recipes/nova-recipe.yaml" + + # Create a PyTorch estimator with a Nova recipe + with tempfile.NamedTemporaryFile(suffix=".yaml") as temp_file: + pytorch = PyTorch( + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + training_recipe="nova_recipe", + ) + + # Set Nova recipe attributes + pytorch.is_nova_recipe = True + pytorch.training_recipe_file = temp_file + + # Create training inputs + train_input = TrainingInput(s3_data="s3://mybucket/train") + val_input = TrainingInput(s3_data="s3://mybucket/validation") + inputs = {"train": train_input, "validation": val_input} + + # Call the fit method with inputs + pytorch.fit(inputs=inputs) + + # Verify the fit method was called with both the recipe channel and the provided inputs + call_args = mock_framework_fit.call_args[1] + assert "inputs" in call_args + assert "recipe" in call_args["inputs"] + assert "train" in call_args["inputs"] + assert "validation" in call_args["inputs"] + + # Verify the hyperparameters were updated with the recipe path + assert "sagemaker_recipe_local_path" in pytorch._hyperparameters + + +def test_device_get_distribution(): + """Test that _device_get_distribution returns the correct distribution configuration.""" + # Test with GPU device type + gpu_distribution = _device_get_distribution("gpu") + expected_gpu_distribution = { + "torch_distributed": {"enabled": True}, + "smdistributed": { + "modelparallel": { + "enabled": True, + "parameters": { + "placement_strategy": "cluster", + }, + }, + }, + } + assert gpu_distribution == expected_gpu_distribution + + # Test with Trainium device type + trainium_distribution = _device_get_distribution("trainium") + expected_trainium_distribution = { + "torch_distributed": {"enabled": True}, + } + assert trainium_distribution == expected_trainium_distribution + + # Test with CPU device type + cpu_distribution = _device_get_distribution("cpu") + assert cpu_distribution == {} + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_load") +@patch("sagemaker.pytorch.estimator.PyTorch._upload_recipe_to_s3") +@patch("sagemaker.pytorch.estimator.Framework.fit") +def test_fit_with_nova_recipe( + mock_framework_fit, mock_upload_recipe, mock_recipe_load, sagemaker_session +): + """Test that fit correctly handles Nova recipes.""" + + # Create a mock recipe that will be identified as a Nova recipe + mock_recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foo-bar", + "model_name_or_path": "foo-bar123", + } + } + ) + + # Set up the mock to return a recipe name and the mock recipe + mock_recipe_load.return_value = ("nova_recipe", mock_recipe) + + # Create a PyTorch estimator with a Nova recipe + with tempfile.NamedTemporaryFile(suffix=".yaml") as temp_file: + pytorch = PyTorch( + role=ROLE, + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + training_recipe="nova_recipe", + ) + + # Set Nova recipe attributes + pytorch.is_nova_recipe = True + pytorch.training_recipe_file = temp_file + + # Mock the upload_recipe_to_s3 method + mock_upload_recipe.return_value = "s3://mybucket/recipes/nova-recipe.yaml" + + # Call the fit method + pytorch.fit() + + # Verify the upload_recipe_to_s3 method was called + mock_upload_recipe.assert_called_once_with(sagemaker_session, temp_file.name) + + # Verify the fit method was called with the recipe channel + call_args = mock_framework_fit.call_args[1] + assert "inputs" in call_args + assert "recipe" in call_args["inputs"] + + # Verify the hyperparameters were updated with the recipe path + assert "sagemaker_recipe_local_path" in pytorch._hyperparameters + + +def test_nova_encode_hyperparameters(): + """Test that _nova_encode_hyperparameters correctly preserves string values and encodes non-string values.""" + # Setup test hyperparameters + hyperparameters = { + "string_param": "string_value", + "int_param": 42, + "float_param": 3.14, + "bool_param": True, + "list_param": [1, 2, 3], + "dict_param": {"key": "value"}, + } + + # Call the method + encoded = EstimatorBase._nova_encode_hyperparameters(hyperparameters) + + # Verify string values are preserved + assert encoded["string_param"] == "string_value" + + # Verify non-string values are JSON-encoded + assert encoded["int_param"] == "42" + assert encoded["float_param"] == "3.14" + assert encoded["bool_param"] == "true" + assert encoded["list_param"] == "[1, 2, 3]" + assert encoded["dict_param"] == '{"key": "value"}' + + +def test_framework_set_hyperparameters_nova(): + """Test that Framework.set_hyperparameters uses _nova_encode_hyperparameters for Nova jobs.""" + # Setup + framework = PyTorch( + entry_point="dummy.py", + role=ROLE, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE, + framework_version="1.13.1", + py_version="py3", + image_uri=IMAGE_URI, + ) + + framework.is_nova_job = True + + # Add hyperparameters + framework.set_hyperparameters(string_param="string_value", int_param=42, bool_param=True) + + # Verify string values are preserved and non-string values are encoded + assert framework._hyperparameters["string_param"] == "string_value" + assert framework._hyperparameters["int_param"] == "42" + assert framework._hyperparameters["bool_param"] == "true" + + +def test_framework_set_hyperparameters_non_nova(): + """Test that Framework.set_hyperparameters uses _json_encode_hyperparameters for non-Nova jobs.""" + # Setup + framework = PyTorch( + entry_point="dummy.py", + role=ROLE, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE, + framework_version="1.13.1", + py_version="py3", + image_uri=IMAGE_URI, + ) + framework.is_nova_recipe = False + + # Add hyperparameters + framework.set_hyperparameters(string_param="string_value", int_param=42, bool_param=True) + + # Verify all values are JSON-encoded + assert framework._hyperparameters["string_param"] == '"string_value"' + assert framework._hyperparameters["int_param"] == "42" + assert framework._hyperparameters["bool_param"] == "true" + + +def test_framework_hyperparameters_nova(): + """Test that Framework.hyperparameters uses _nova_encode_hyperparameters for Nova jobs.""" + # Setup + framework = PyTorch( + entry_point="dummy.py", + role=ROLE, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE, + framework_version="1.13.1", + py_version="py3", + image_uri=IMAGE_URI, + ) + + framework.is_nova_job = True + + # Add hyperparameters directly to _hyperparameters + framework._hyperparameters = { + "string_param": "string_value", + "int_param": 42, + "bool_param": True, + } + + # Get hyperparameters + hyperparams = framework.hyperparameters() + + # Verify string values are preserved and non-string values are encoded + assert hyperparams["string_param"] == "string_value" + assert hyperparams["int_param"] == "42" + assert hyperparams["bool_param"] == "true" + + +@patch("sagemaker.pytorch.estimator.PyTorch._recipe_resolve_and_save") +def test_setup_for_nova_recipe_with_distillation(mock_resolve_save, sagemaker_session): + """Test that _setup_for_nova_recipe correctly handles distillation configurations.""" + # Create a mock recipe with distillation config + recipe = OmegaConf.create( + { + "run": { + "model_type": "amazon.nova.foobar3", + "model_name_or_path": "foobar/foobar-3-8b", + "replicas": 4, + }, + "training_config": { + "distillation_data": "s3://mybucket/distillation-data", + "kms_key": "alias/my-kms-key", + }, + } + ) + + # Setup the expected return value + expected_args = { + "hyperparameters": { + "base_model": "foobar/foobar-3-8b", + "distillation_data": "s3://mybucket/distillation-data", + "role_arn": "arn:aws:iam::123456789012:role/SageMakerRole", + "kms_key": "alias/my-kms-key", + }, + "entry_point": None, + "source_dir": None, + "distribution": {}, + "default_image_uri": IMAGE_URI, + } + + with patch( + "sagemaker.pytorch.estimator.PyTorch._setup_for_nova_recipe", return_value=expected_args + ) as mock_nova_setup: + with patch( + "sagemaker.pytorch.estimator.PyTorch._recipe_load", return_value=("nova_recipe", recipe) + ): + mock_resolve_save.return_value = recipe + + pytorch = PyTorch( + training_recipe="nova_recipe", + role="arn:aws:iam::123456789012:role/SageMakerRole", + sagemaker_session=sagemaker_session, + instance_count=INSTANCE_COUNT, + instance_type=INSTANCE_TYPE_GPU, + image_uri=IMAGE_URI, + framework_version="1.13.1", + py_version="py3", + ) + + # Check that the Nova recipe was correctly identified + assert pytorch.is_nova_recipe is True + + # Verify _setup_for_nova_recipe was called + mock_nova_setup.assert_called_once() + + # Verify that hyperparameters were set correctly for distillation + assert ( + pytorch._hyperparameters.get("distillation_data") + == "s3://mybucket/distillation-data" + ) + assert pytorch._hyperparameters.get("kms_key") == "alias/my-kms-key" + assert ( + pytorch._hyperparameters.get("role_arn") + == "arn:aws:iam::123456789012:role/SageMakerRole" + ) From b79c438efe01dc490a4d97a6a036eef2f2687a3d Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 16 Jul 2025 04:22:49 +0000 Subject: [PATCH 141/164] prepare release v2.248.1 --- CHANGELOG.md | 6 ++++++ VERSION | 2 +- 2 files changed, 7 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 13a72a8f6a..14ccb198d6 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,11 @@ # Changelog +## v2.248.1 (2025-07-16) + +### Bug Fixes and Other Changes + + * Nova training support + ## v2.248.0 (2025-07-15) ### Features diff --git a/VERSION b/VERSION index c6caf264f5..3abf3a6533 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.1.dev0 +2.248.1 From f472320ec8c72cbd9431ed719b2f9304b32dabf8 Mon Sep 17 00:00:00 2001 From: ci Date: Wed, 16 Jul 2025 04:22:54 +0000 Subject: [PATCH 142/164] update development version to v2.248.2.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 3abf3a6533..fe9f027c66 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.1 +2.248.2.dev0 From ed3c2964003e129a89dee1dcc0a86909b9f85c13 Mon Sep 17 00:00:00 2001 From: Jiali Xing <53011060+Jiali-Xing@users.noreply.github.com> Date: Wed, 16 Jul 2025 09:25:31 -0700 Subject: [PATCH 143/164] change: When rootlessDocker is enabled, return a fixed SageMaker IP (#5236) * change: When rootlessDocker is enabled, return a fixed SageMaker IP * Add logging for docker info command failure --------- Co-authored-by: Jiali Xing Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> --- src/sagemaker/local/utils.py | 24 ++++++- .../unit/sagemaker/local/test_local_utils.py | 62 +++++++++++++++++++ 2 files changed, 85 insertions(+), 1 deletion(-) diff --git a/src/sagemaker/local/utils.py b/src/sagemaker/local/utils.py index 2c2a5a1c90..3c7c3cda61 100644 --- a/src/sagemaker/local/utils.py +++ b/src/sagemaker/local/utils.py @@ -153,7 +153,8 @@ def get_child_process_ids(pid): def get_docker_host(): """Discover remote docker host address (if applicable) or use "localhost" - Use "docker context inspect" to read current docker host endpoint url, + When rootlessDocker is enabled (Cgroup Driver: none), use fixed SageMaker IP. + Otherwise, Use "docker context inspect" to read current docker host endpoint url, url must start with "tcp://" Args: @@ -161,6 +162,27 @@ def get_docker_host(): Returns: docker_host (str): Docker host DNS or IP address """ + # Check if using SageMaker rootless Docker by examining storage driver + try: + cmd = ["docker", "info"] + process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) + output, err = process.communicate() + if process.returncode == 0: # Check return code instead of stderr + output_text = output.decode("utf-8") + # Check for rootless Docker by looking at Cgroup Driver + if "Cgroup Driver: none" in output_text: + # log the result of check + logger.warning("RootlessDocker detected (Cgroup Driver: none), returning fixed IP.") + # SageMaker rootless Docker detected - return fixed IP + return "172.17.0.1" + else: + logger.warning( + "RootlessDocker not detected, falling back to remote host IP or localhost." + ) + except subprocess.SubprocessError as e: + logger.warning("Failed to run 'docker info' command when checking rootlessDocker: %s.", e) + + # Fallback to existing logic for remote Docker hosts cmd = "docker context inspect".split() process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) output, err = process.communicate() diff --git a/tests/unit/sagemaker/local/test_local_utils.py b/tests/unit/sagemaker/local/test_local_utils.py index a9aae53fb2..82e3207266 100644 --- a/tests/unit/sagemaker/local/test_local_utils.py +++ b/tests/unit/sagemaker/local/test_local_utils.py @@ -135,6 +135,68 @@ def test_get_docker_host(m_subprocess): assert host == endpoint["result"] +@patch("sagemaker.local.utils.subprocess") +def test_get_docker_host_rootless_docker(m_subprocess): + """Test that rootless Docker is detected and returns fixed IP""" + # Mock docker info process for rootless Docker + info_process_mock = Mock() + info_attrs = {"communicate.return_value": (b"Cgroup Driver: none", b""), "returncode": 0} + info_process_mock.configure_mock(**info_attrs) + m_subprocess.Popen.return_value = info_process_mock + + host = sagemaker.local.utils.get_docker_host() + assert host == "172.17.0.1" + + # Verify docker info was called + m_subprocess.Popen.assert_called_with( + ["docker", "info"], stdout=m_subprocess.PIPE, stderr=m_subprocess.PIPE + ) + + +@patch("sagemaker.local.utils.subprocess") +def test_get_docker_host_traditional_docker(m_subprocess): + """Test that traditional Docker falls back to existing logic""" + scenarios = [ + { + "docker_info": b"Cgroup Driver: cgroupfs", + "context_host": "tcp://host:port", + "result": "host", + }, + { + "docker_info": b"Cgroup Driver: cgroupfs", + "context_host": "unix:///var/run/docker.sock", + "result": "localhost", + }, + { + "docker_info": b"Cgroup Driver: cgroupfs", + "context_host": "fd://something", + "result": "localhost", + }, + ] + + for scenario in scenarios: + # Mock docker info process for traditional Docker + info_process_mock = Mock() + info_attrs = {"communicate.return_value": (scenario["docker_info"], b""), "returncode": 0} + info_process_mock.configure_mock(**info_attrs) + + # Mock docker context inspect process + context_return_value = ( + '[\n{\n"Endpoints":{\n"docker":{\n"Host": "%s"}\n}\n}\n]\n' % scenario["context_host"] + ) + context_process_mock = Mock() + context_attrs = { + "communicate.return_value": (context_return_value.encode("utf-8"), None), + "returncode": 0, + } + context_process_mock.configure_mock(**context_attrs) + + m_subprocess.Popen.side_effect = [info_process_mock, context_process_mock] + + host = sagemaker.local.utils.get_docker_host() + assert host == scenario["result"] + + @pytest.mark.parametrize( "json_path, expected", [ From 2b20b20cad5f5b86427b712bc04e6cf5b657b751 Mon Sep 17 00:00:00 2001 From: "parknate@" Date: Wed, 16 Jul 2025 11:30:28 -0700 Subject: [PATCH 144/164] fix: add hard dependency on sagemaker-core pypi lib (#5241) --- tox.ini | 1 + 1 file changed, 1 insertion(+) diff --git a/tox.ini b/tox.ini index 566e46a9a7..e4df36587a 100644 --- a/tox.ini +++ b/tox.ini @@ -87,6 +87,7 @@ commands = pip install 'torchvision==0.18.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' pip install 'dill>=0.3.9' pip install 'altair>=5.3' # needed for amtviz + pip install -U "sagemaker-core" # needed to keep sagemaker-core up to date pytest {posargs} deps = .[test] From dc8f8a5c94fc4794338b85f4b3169dfe185dd035 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Fri, 18 Jul 2025 14:18:28 +0000 Subject: [PATCH 145/164] change: update image_uri_configs 07-18-2025 07:18:28 PST --- src/sagemaker/image_uri_config/spark.json | 46 +++++++++++++++++++++++ 1 file changed, 46 insertions(+) diff --git a/src/sagemaker/image_uri_config/spark.json b/src/sagemaker/image_uri_config/spark.json index 48c43fca15..0a430ebc77 100644 --- a/src/sagemaker/image_uri_config/spark.json +++ b/src/sagemaker/image_uri_config/spark.json @@ -228,6 +228,52 @@ "us-west-2": "153931337802" }, "repository": "sagemaker-spark-processing" + }, + "3.5": { + "py_versions": [ + "py39", + "py312" + ], + "registries": { + "af-south-1": "309385258863", + "ap-east-1": "732049463269", + "ap-east-2": "533267296287", + "ap-northeast-1": "411782140378", + "ap-northeast-2": "860869212795", + "ap-northeast-3": "102471314380", + "ap-south-1": "105495057255", + "ap-south-2": "873151114052", + "ap-southeast-1": "759080221371", + "ap-southeast-2": "440695851116", + "ap-southeast-3": "800295151634", + "ap-southeast-4": "819679513684", + "ap-southeast-5": "841784149062", + "ap-southeast-7": "471112967968", + "ca-central-1": "446299261295", + "ca-west-1": "000907499111", + "cn-north-1": "671472414489", + "cn-northwest-1": "844356804704", + "eu-central-1": "906073651304", + "eu-central-2": "142351485170", + "eu-north-1": "330188676905", + "eu-south-1": "753923664805", + "eu-south-2": "833944533722", + "eu-west-1": "571004829621", + "eu-west-2": "836651553127", + "eu-west-3": "136845547031", + "il-central-1": "408426139102", + "me-central-1": "395420993607", + "me-south-1": "750251592176", + "mx-central-1": "211125459255", + "sa-east-1": "737130764395", + "us-east-1": "173754725891", + "us-east-2": "314815235551", + "us-gov-east-1": "260923028637", + "us-gov-west-1": "271483468897", + "us-west-1": "667973535471", + "us-west-2": "153931337802" + }, + "repository": "sagemaker-spark-processing" } } } From fc4cfcc10ad616c7eafd7a1e4e9b103aab6dd556 Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Tue, 22 Jul 2025 14:18:25 +0000 Subject: [PATCH 146/164] change: update image_uri_configs 07-22-2025 07:18:25 PST --- .../huggingface-llm-neuronx.json | 12 +++ .../image_uri_config/huggingface-llm.json | 21 +++++ src/sagemaker/image_uri_config/pytorch.json | 56 ++++++++++++ .../image_uri_config/tensorflow.json | 85 +++++++++++++++++++ 4 files changed, 174 insertions(+) diff --git a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json index 9b7b18ee94..1c425b37ec 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json +++ b/src/sagemaker/image_uri_config/huggingface-llm-neuronx.json @@ -25,6 +25,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -78,6 +79,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -131,6 +133,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -184,6 +187,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -237,6 +241,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -290,6 +295,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -343,6 +349,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -396,6 +403,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -449,6 +457,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -502,6 +511,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -555,6 +565,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -608,6 +619,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", diff --git a/src/sagemaker/image_uri_config/huggingface-llm.json b/src/sagemaker/image_uri_config/huggingface-llm.json index ed85f0d2bf..58fffa0ed9 100644 --- a/src/sagemaker/image_uri_config/huggingface-llm.json +++ b/src/sagemaker/image_uri_config/huggingface-llm.json @@ -37,6 +37,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -90,6 +91,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -143,6 +145,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -196,6 +199,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -249,6 +253,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -302,6 +307,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -355,6 +361,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -408,6 +415,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -461,6 +469,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -514,6 +523,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -567,6 +577,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -620,6 +631,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -673,6 +685,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -726,6 +739,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -779,6 +793,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -832,6 +847,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -885,6 +901,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -938,6 +955,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -991,6 +1009,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1044,6 +1063,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1097,6 +1117,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", diff --git a/src/sagemaker/image_uri_config/pytorch.json b/src/sagemaker/image_uri_config/pytorch.json index 58b1fdfff7..8a1993e52a 100644 --- a/src/sagemaker/image_uri_config/pytorch.json +++ b/src/sagemaker/image_uri_config/pytorch.json @@ -210,6 +210,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -258,6 +259,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -306,6 +308,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -354,6 +357,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -402,6 +406,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -450,6 +455,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -498,6 +504,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -546,6 +553,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -593,6 +601,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -640,6 +649,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -687,6 +697,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -734,6 +745,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -781,6 +793,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -828,6 +841,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -875,6 +889,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -922,6 +937,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -969,6 +985,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1016,6 +1033,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1063,6 +1081,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1112,6 +1131,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1161,6 +1181,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1206,6 +1227,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1251,6 +1273,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1296,6 +1319,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1359,6 +1383,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1409,6 +1434,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1457,6 +1483,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1505,6 +1532,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1553,6 +1581,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1601,6 +1630,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1649,6 +1679,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1830,6 +1861,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1878,6 +1910,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1927,6 +1960,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1975,6 +2009,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2023,6 +2058,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2071,6 +2107,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2119,6 +2156,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2167,6 +2205,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2214,6 +2253,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2261,6 +2301,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2308,6 +2349,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2355,6 +2397,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2402,6 +2445,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2449,6 +2493,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2496,6 +2541,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2543,6 +2589,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2590,6 +2637,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2637,6 +2685,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2684,6 +2733,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2733,6 +2783,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2782,6 +2833,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2831,6 +2883,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2876,6 +2929,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2921,6 +2975,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2966,6 +3021,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", diff --git a/src/sagemaker/image_uri_config/tensorflow.json b/src/sagemaker/image_uri_config/tensorflow.json index 8450b2d22f..f410ec8b95 100644 --- a/src/sagemaker/image_uri_config/tensorflow.json +++ b/src/sagemaker/image_uri_config/tensorflow.json @@ -643,6 +643,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -687,6 +688,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -731,6 +733,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -775,6 +778,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -819,6 +823,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -863,6 +868,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -907,6 +913,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -951,6 +958,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -995,6 +1003,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1039,6 +1048,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1083,6 +1093,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1127,6 +1138,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1171,6 +1183,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1215,6 +1228,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1259,6 +1273,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1303,6 +1318,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1347,6 +1363,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1391,6 +1408,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1435,6 +1453,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1479,6 +1498,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1523,6 +1543,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1567,6 +1588,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1611,6 +1633,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1655,6 +1678,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1699,6 +1723,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1743,6 +1768,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1787,6 +1813,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1831,6 +1858,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1875,6 +1903,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1919,6 +1948,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -1963,6 +1993,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2007,6 +2038,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2051,6 +2083,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2095,6 +2128,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2139,6 +2173,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2183,6 +2218,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2227,6 +2263,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2271,6 +2308,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2317,6 +2355,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2363,6 +2402,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2405,6 +2445,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2447,6 +2488,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2509,6 +2551,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2559,6 +2602,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2609,6 +2653,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2659,6 +2704,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -2709,6 +2755,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3166,6 +3213,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3214,6 +3262,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3263,6 +3312,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3312,6 +3362,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3361,6 +3412,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3410,6 +3462,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3458,6 +3511,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3506,6 +3560,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3554,6 +3609,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3602,6 +3658,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3650,6 +3707,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3698,6 +3756,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3746,6 +3805,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3794,6 +3854,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3842,6 +3903,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3889,6 +3951,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3936,6 +3999,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -3983,6 +4047,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4030,6 +4095,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4077,6 +4143,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4124,6 +4191,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4171,6 +4239,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4218,6 +4287,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4265,6 +4335,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4312,6 +4383,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4359,6 +4431,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4406,6 +4479,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4453,6 +4527,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4500,6 +4575,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4547,6 +4623,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4594,6 +4671,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4641,6 +4719,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4688,6 +4767,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4735,6 +4815,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4780,6 +4861,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4829,6 +4911,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4878,6 +4961,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", @@ -4923,6 +5007,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", From 03de1aa664c395af06893facb442e97f782b8b96 Mon Sep 17 00:00:00 2001 From: papriwal Date: Tue, 22 Jul 2025 09:34:02 -0700 Subject: [PATCH 147/164] Relax boto3 version requirement (#5245) --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 87bc0a4d3c..aa3391d9bd 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -32,7 +32,7 @@ classifiers = [ ] dependencies = [ "attrs>=24,<26", - "boto3>=1.35.75,<2.0", + "boto3>=1.35.36,<2.0", "cloudpickle>=2.2.1", "docker", "fastapi", From c93a632d4bc0e586bea4f5f2688bf67638d318f3 Mon Sep 17 00:00:00 2001 From: ci Date: Tue, 22 Jul 2025 22:54:14 +0000 Subject: [PATCH 148/164] prepare release v2.248.2 --- CHANGELOG.md | 10 ++++++++++ VERSION | 2 +- 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 14ccb198d6..922dbe09eb 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,15 @@ # Changelog +## v2.248.2 (2025-07-22) + +### Bug Fixes and Other Changes + + * Relax boto3 version requirement + * update image_uri_configs 07-22-2025 07:18:25 PST + * update image_uri_configs 07-18-2025 07:18:28 PST + * add hard dependency on sagemaker-core pypi lib + * When rootlessDocker is enabled, return a fixed SageMaker IP + ## v2.248.1 (2025-07-16) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index fe9f027c66..9d12da5cbe 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.2.dev0 +2.248.2 From c860c51e43427b9bfe25bcd6dbfd59009359da5e Mon Sep 17 00:00:00 2001 From: ci Date: Tue, 22 Jul 2025 22:54:18 +0000 Subject: [PATCH 149/164] update development version to v2.248.3.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 9d12da5cbe..fcc1c85c53 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.2 +2.248.3.dev0 From 23c38409d2988b960a25ec18f20d33434e37ad2f Mon Sep 17 00:00:00 2001 From: sagemaker-bot Date: Wed, 23 Jul 2025 14:18:25 +0000 Subject: [PATCH 150/164] change: update image_uri_configs 07-23-2025 07:18:25 PST --- src/sagemaker/image_uri_config/tensorflow.json | 1 + 1 file changed, 1 insertion(+) diff --git a/src/sagemaker/image_uri_config/tensorflow.json b/src/sagemaker/image_uri_config/tensorflow.json index f410ec8b95..f793edb4c9 100644 --- a/src/sagemaker/image_uri_config/tensorflow.json +++ b/src/sagemaker/image_uri_config/tensorflow.json @@ -5053,6 +5053,7 @@ "ap-southeast-3": "907027046896", "ap-southeast-4": "457447274322", "ap-southeast-5": "550225433462", + "ap-southeast-6": "633930458069", "ap-southeast-7": "590183813437", "ca-central-1": "763104351884", "ca-west-1": "204538143572", From ed4fbe8dee97a85e9de9e6d7cbae5497ba40b717 Mon Sep 17 00:00:00 2001 From: cj-zhang <32367995+cj-zhang@users.noreply.github.com> Date: Mon, 28 Jul 2025 16:42:45 -0400 Subject: [PATCH 151/164] Directly use customer-provided endpoint name for ModelBuilder deployment. (#5246) * Directly use customer-provided endpoint name for deployment in ModelBuilder. * Fix ModelBuilder UTs after removing unique_name_from_base import. --------- Co-authored-by: Joseph Zhang --- src/sagemaker/serve/builder/model_builder.py | 4 +--- tests/integ/sagemaker/serve/test_base_model_builder_deploy.py | 4 ++-- .../test_serve_model_builder_inference_component_happy.py | 3 ++- tests/unit/sagemaker/serve/builder/test_model_builder.py | 4 +--- 4 files changed, 6 insertions(+), 9 deletions(-) diff --git a/src/sagemaker/serve/builder/model_builder.py b/src/sagemaker/serve/builder/model_builder.py index ed5455daec..3c19e4aa43 100644 --- a/src/sagemaker/serve/builder/model_builder.py +++ b/src/sagemaker/serve/builder/model_builder.py @@ -116,7 +116,7 @@ validate_image_uri_and_hardware, ) from sagemaker.serverless import ServerlessInferenceConfig -from sagemaker.utils import Tags, unique_name_from_base +from sagemaker.utils import Tags from sagemaker.workflow.entities import PipelineVariable from sagemaker.huggingface.llm_utils import ( get_huggingface_model_metadata, @@ -1983,8 +1983,6 @@ def deploy( """ if not hasattr(self, "built_model") and not hasattr(self, "_deployables"): raise ValueError("Model needs to be built before deploying") - if not update_endpoint: - endpoint_name = unique_name_from_base(endpoint_name) if not hasattr(self, "_deployables"): if not inference_config: # Real-time Deployment diff --git a/tests/integ/sagemaker/serve/test_base_model_builder_deploy.py b/tests/integ/sagemaker/serve/test_base_model_builder_deploy.py index 80f9c50e4b..a0de64225d 100644 --- a/tests/integ/sagemaker/serve/test_base_model_builder_deploy.py +++ b/tests/integ/sagemaker/serve/test_base_model_builder_deploy.py @@ -185,7 +185,7 @@ def invoke(self, input_object: object, model: object): def test_real_time_deployment(xgboost_model_builder): real_time_predictor = xgboost_model_builder.deploy( - endpoint_name="test", initial_instance_count=1 + endpoint_name=f"test-{uuid.uuid1().hex}", initial_instance_count=1 ) assert real_time_predictor is not None @@ -198,7 +198,7 @@ def test_real_time_deployment(xgboost_model_builder): def test_serverless_deployment(xgboost_model_builder): serverless_predictor = xgboost_model_builder.deploy( - endpoint_name="test1", inference_config=ServerlessInferenceConfig() + endpoint_name=f"test1-{uuid.uuid1().hex}", inference_config=ServerlessInferenceConfig() ) assert serverless_predictor is not None diff --git a/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py b/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py index b72b84aeac..7191de4e7d 100644 --- a/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py +++ b/tests/integ/sagemaker/serve/test_serve_model_builder_inference_component_happy.py @@ -14,6 +14,7 @@ import pytest import tests.integ +import uuid from botocore.exceptions import ClientError from sagemaker.predictor import Predictor @@ -88,7 +89,7 @@ def test_model_builder_ic_sagemaker_endpoint( with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT): try: logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...") - endpoint_name = "llama-ic-endpoint-name" + endpoint_name = f"llama-ic-endpoint-name-{uuid.uuid1().hex}" predictors = chain.deploy( instance_type=INSTANCE_TYPE, initial_instance_count=1, diff --git a/tests/unit/sagemaker/serve/builder/test_model_builder.py b/tests/unit/sagemaker/serve/builder/test_model_builder.py index de4304d63d..8ae6072ee5 100644 --- a/tests/unit/sagemaker/serve/builder/test_model_builder.py +++ b/tests/unit/sagemaker/serve/builder/test_model_builder.py @@ -4241,9 +4241,7 @@ def test_neuron_configurations_rule_set(self): "Batch", ], ) -@patch("sagemaker.serve.builder.model_builder.unique_name_from_base") -def test_deploy(mock_unique_name_from_base, test_case): - mock_unique_name_from_base.return_value = "test" +def test_deploy(test_case): model: Model = MagicMock() model_builder = ModelBuilder( model="meta-llama/Meta-Llama-3-8B-Instruct", From 907f923f14399d02b4f55b8de2e86e577a7fe4b3 Mon Sep 17 00:00:00 2001 From: Erick Benitez-Ramos <141277478+benieric@users.noreply.github.com> Date: Wed, 30 Jul 2025 12:35:07 -0700 Subject: [PATCH 152/164] feature: AWS Batch for SageMaker Training jobs (#5249) --------- Co-authored-by: Greg Katkov Co-authored-by: haoxinwa <138720323+haoxinwa@users.noreply.github.com> Co-authored-by: JennaZhao <100809398+JennaZhao@users.noreply.github.com> Co-authored-by: Jessica Zhu <106775307+jessicazhu3@users.noreply.github.com> Co-authored-by: David Lindskog --- src/sagemaker/aws_batch/__init__.py | 0 src/sagemaker/aws_batch/batch_api_helper.py | 186 ++++++++ src/sagemaker/aws_batch/boto_client.py | 33 ++ src/sagemaker/aws_batch/constants.py | 34 ++ src/sagemaker/aws_batch/exception.py | 52 +++ src/sagemaker/aws_batch/training_queue.py | 212 +++++++++ .../aws_batch/training_queued_job.py | 217 +++++++++ src/sagemaker/estimator.py | 5 + src/sagemaker/modules/train/model_trainer.py | 182 +++++--- src/sagemaker/session.py | 233 +++++++++- src/sagemaker/utils.py | 18 + .../data/modules/script_mode/custom_script.py | 58 ++- tests/integ/sagemaker/aws_batch/__init__.py | 0 tests/integ/sagemaker/aws_batch/manager.py | 133 ++++++ tests/integ/sagemaker/aws_batch/test_queue.py | 93 ++++ ...sor.py => test_feature_processor_integ.py} | 0 tests/integ/sagemaker/modules/conftest.py | 2 +- tests/unit/sagemaker/aws_batch/__init__.py | 0 tests/unit/sagemaker/aws_batch/constants.py | 72 +++ tests/unit/sagemaker/aws_batch/mock_client.py | 44 ++ .../sagemaker/aws_batch/mock_estimator.py | 35 ++ .../aws_batch/test_batch_api_helper.py | 186 ++++++++ .../aws_batch/test_training_queue.py | 411 ++++++++++++++++++ .../aws_batch/test_training_queued_job.py | 170 ++++++++ .../modules/train/test_model_trainer.py | 47 ++ tox.ini | 9 +- 26 files changed, 2354 insertions(+), 78 deletions(-) create mode 100644 src/sagemaker/aws_batch/__init__.py create mode 100644 src/sagemaker/aws_batch/batch_api_helper.py create mode 100644 src/sagemaker/aws_batch/boto_client.py create mode 100644 src/sagemaker/aws_batch/constants.py create mode 100644 src/sagemaker/aws_batch/exception.py create mode 100644 src/sagemaker/aws_batch/training_queue.py create mode 100644 src/sagemaker/aws_batch/training_queued_job.py create mode 100644 tests/integ/sagemaker/aws_batch/__init__.py create mode 100644 tests/integ/sagemaker/aws_batch/manager.py create mode 100644 tests/integ/sagemaker/aws_batch/test_queue.py rename tests/integ/sagemaker/feature_store/feature_processor/{test_feature_processor.py => test_feature_processor_integ.py} (100%) create mode 100644 tests/unit/sagemaker/aws_batch/__init__.py create mode 100644 tests/unit/sagemaker/aws_batch/constants.py create mode 100644 tests/unit/sagemaker/aws_batch/mock_client.py create mode 100644 tests/unit/sagemaker/aws_batch/mock_estimator.py create mode 100644 tests/unit/sagemaker/aws_batch/test_batch_api_helper.py create mode 100644 tests/unit/sagemaker/aws_batch/test_training_queue.py create mode 100644 tests/unit/sagemaker/aws_batch/test_training_queued_job.py diff --git a/src/sagemaker/aws_batch/__init__.py b/src/sagemaker/aws_batch/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/sagemaker/aws_batch/batch_api_helper.py b/src/sagemaker/aws_batch/batch_api_helper.py new file mode 100644 index 0000000000..4482a644ab --- /dev/null +++ b/src/sagemaker/aws_batch/batch_api_helper.py @@ -0,0 +1,186 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""The module provides helper function for Batch Submit/Describe/Terminal job APIs.""" +from __future__ import absolute_import + +import json +from typing import List, Dict, Optional +from sagemaker.aws_batch.constants import ( + SAGEMAKER_TRAINING, + DEFAULT_TIMEOUT, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, +) +from sagemaker.aws_batch.boto_client import get_batch_boto_client + + +def submit_service_job( + training_payload: Dict, + job_name: str, + job_queue: str, + retry_config: Optional[Dict] = None, + scheduling_priority: Optional[int] = None, + timeout: Optional[Dict] = None, + share_identifier: Optional[str] = None, + tags: Optional[Dict] = None, +) -> Dict: + """Batch submit_service_job API helper function. + + Args: + training_payload: a dict containing a dict of arguments for Training job. + job_name: Batch job name. + job_queue: Batch job queue ARN. + retry_config: Batch job retry configuration. + scheduling_priority: An integer representing scheduling priority. + timeout: Set with value of timeout if specified, else default to 1 day. + share_identifier: value of shareIdentifier if specified. + tags: A dict of string to string representing Batch tags. + + Returns: + A dict containing jobArn, jobName and jobId. + """ + if timeout is None: + timeout = DEFAULT_TIMEOUT + client = get_batch_boto_client() + training_payload_tags = training_payload.pop("Tags", None) + payload = { + "jobName": job_name, + "jobQueue": job_queue, + "retryStrategy": DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + "serviceJobType": SAGEMAKER_TRAINING, + "serviceRequestPayload": json.dumps(training_payload), + "timeoutConfig": timeout, + } + if retry_config: + payload["retryStrategy"] = retry_config + if scheduling_priority: + payload["schedulingPriority"] = scheduling_priority + if share_identifier: + payload["shareIdentifier"] = share_identifier + if tags or training_payload_tags: + payload["tags"] = __merge_tags(tags, training_payload_tags) + return client.submit_service_job(**payload) + + +def describe_service_job(job_id: str) -> Dict: + """Batch describe_service_job API helper function. + + Args: + job_id: Job ID used. + + Returns: a dict. See the sample below + { + 'attempts': [ + { + 'serviceResourceId': { + 'name': 'string', + 'value': 'string' + }, + 'startedAt': 123, + 'stoppedAt': 123, + 'statusReason': 'string' + }, + ], + 'createdAt': 123, + 'isTerminated': True|False, + 'jobArn': 'string', + 'jobId': 'string', + 'jobName': 'string', + 'jobQueue': 'string', + 'retryStrategy': { + 'attempts': 123 + }, + 'schedulingPriority': 123, + 'serviceRequestPayload': 'string', + 'serviceJobType': 'EKS'|'ECS'|'ECS_FARGATE'|'SAGEMAKER_TRAINING', + 'shareIdentifier': 'string', + 'startedAt': 123, + 'status': 'SUBMITTED'|'PENDING'|'RUNNABLE'|'STARTING'|'RUNNING'|'SUCCEEDED'|'FAILED', + 'statusReason': 'string', + 'stoppedAt': 123, + 'tags': { + 'string': 'string' + }, + 'timeout': { + 'attemptDurationSeconds': 123 + } + } + """ + client = get_batch_boto_client() + return client.describe_service_job(jobId=job_id) + + +def terminate_service_job(job_id: str, reason: Optional[str] = "default terminate reason") -> Dict: + """Batch terminate_service_job API helper function. + + Args: + job_id: Job ID + reason: A string representing terminate reason. + + Returns: an empty dict + """ + client = get_batch_boto_client() + return client.terminate_service_job(jobId=job_id, reason=reason) + + +def list_service_job( + job_queue: str, + job_status: Optional[str] = None, + filters: Optional[List] = None, + next_token: Optional[str] = None, +) -> Dict: + """Batch list_service_job API helper function. + + Args: + job_queue: Batch job queue ARN. + job_status: Batch job status. + filters: A list of Dict. Each contains a filter. + next_token: Used to retrieve data in next page. + + Returns: A generator containing list results. + + """ + client = get_batch_boto_client() + payload = {"jobQueue": job_queue} + if filters: + payload["filters"] = filters + if next_token: + payload["nextToken"] = next_token + if job_status: + payload["jobStatus"] = job_status + part_of_jobs = client.list_service_jobs(**payload) + next_token = part_of_jobs.get("nextToken") + yield part_of_jobs + if next_token: + yield from list_service_job(job_queue, job_status, filters, next_token) + + +def __merge_tags(batch_tags: Optional[Dict], training_tags: Optional[List]) -> Optional[Dict]: + """Merges Batch and training payload tags. + + Returns a copy of Batch tags merged with training payload tags. Training payload tags take + precedence in the case of key conflicts. + + :param batch_tags: A dict of string to string representing Batch tags. + :param training_tags: A list of `{"Key": "string", "Value": "string"}` objects representing + training payload tags. + :return: A dict of string to string representing batch tags merged with training tags. + batch_tags is returned unaltered if training_tags is None or empty. + """ + if not training_tags: + return batch_tags + + training_tags_to_merge = {tag["Key"]: tag["Value"] for tag in training_tags} + batch_tags_copy = batch_tags.copy() if batch_tags else {} + batch_tags_copy.update(training_tags_to_merge) + + return batch_tags_copy diff --git a/src/sagemaker/aws_batch/boto_client.py b/src/sagemaker/aws_batch/boto_client.py new file mode 100644 index 0000000000..87f3486887 --- /dev/null +++ b/src/sagemaker/aws_batch/boto_client.py @@ -0,0 +1,33 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""The file provides helper function for getting Batch boto client.""" +from __future__ import absolute_import + +from typing import Optional +import boto3 + + +def get_batch_boto_client( + region: Optional[str] = None, + endpoint: Optional[str] = None, +) -> boto3.session.Session.client: + """Helper function for getting Batch boto3 client. + + Args: + region: Region specified + endpoint: Batch API endpoint. + + Returns: Batch boto3 client. + + """ + return boto3.client("batch", region_name=region, endpoint_url=endpoint) diff --git a/src/sagemaker/aws_batch/constants.py b/src/sagemaker/aws_batch/constants.py new file mode 100644 index 0000000000..ee41d3a413 --- /dev/null +++ b/src/sagemaker/aws_batch/constants.py @@ -0,0 +1,34 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""The file defines constants used for Batch API helper functions.""" + +from __future__ import absolute_import + +SAGEMAKER_TRAINING = "SAGEMAKER_TRAINING" +DEFAULT_ATTEMPT_DURATION_IN_SECONDS = 86400 # 1 day in seconds. +DEFAULT_TIMEOUT = {"attemptDurationSeconds": DEFAULT_ATTEMPT_DURATION_IN_SECONDS} +POLL_IN_SECONDS = 5 +JOB_STATUS_RUNNING = "RUNNING" +JOB_STATUS_COMPLETED = "SUCCEEDED" +JOB_STATUS_FAILED = "FAILED" +DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG = { + "attempts": 1, + "evaluateOnExit": [ + { + "action": "RETRY", + "onStatusReason": "Received status from SageMaker:InternalServerError: " + "We encountered an internal error. Please try again.", + }, + {"action": "EXIT", "onStatusReason": "*"}, + ], +} diff --git a/src/sagemaker/aws_batch/exception.py b/src/sagemaker/aws_batch/exception.py new file mode 100644 index 0000000000..94318bbce4 --- /dev/null +++ b/src/sagemaker/aws_batch/exception.py @@ -0,0 +1,52 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""The file Defines customized exception for Batch queueing""" +from __future__ import absolute_import + + +class NoTrainingJob(Exception): + """Define NoTrainingJob Exception. + + It means no Training job has been created by AWS Batch service. + """ + + def __init__(self, value): + super().__init__(value) + self.value = value + + def __str__(self): + """Convert Exception to string. + + Returns: a String containing exception error messages. + + """ + return repr(self.value) + + +class MissingRequiredArgument(Exception): + """Define MissingRequiredArgument exception. + + It means some required arguments are missing. + """ + + def __init__(self, value): + super().__init__(value) + self.value = value + + def __str__(self): + """Convert Exception to string. + + Returns: a String containing exception error messages. + + """ + return repr(self.value) diff --git a/src/sagemaker/aws_batch/training_queue.py b/src/sagemaker/aws_batch/training_queue.py new file mode 100644 index 0000000000..b540fad0a9 --- /dev/null +++ b/src/sagemaker/aws_batch/training_queue.py @@ -0,0 +1,212 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Define Queue class for AWS Batch service""" +from __future__ import absolute_import + +from typing import Dict, Optional, List, Union +import logging +from sagemaker.estimator import EstimatorBase, _TrainingJob +from sagemaker.modules.train.model_trainer import ModelTrainer, Mode +from .training_queued_job import TrainingQueuedJob +from .batch_api_helper import submit_service_job, list_service_job +from .exception import MissingRequiredArgument +from .constants import DEFAULT_TIMEOUT, JOB_STATUS_RUNNING + + +class TrainingQueue: + """TrainingQueue class for AWS Batch service + + With this class, customers are able to create a new queue and submit jobs to AWS Batch Service. + """ + + def __init__(self, queue_name: str): + self.queue_name = queue_name + + def submit( + self, + training_job: Union[EstimatorBase, ModelTrainer], + inputs, + job_name: Optional[str] = None, + retry_config: Optional[Dict] = None, + priority: Optional[int] = None, + share_identifier: Optional[str] = None, + timeout: Optional[Dict] = None, + tags: Optional[Dict] = None, + experiment_config: Optional[Dict] = None, + ) -> TrainingQueuedJob: + """Submit a queued job and return a QueuedJob object. + + Args: + training_job: Training job EstimatorBase or ModelTrainer object. + inputs: Training job inputs. + job_name: Batch job name. + retry_config: Retry configuration for Batch job. + priority: Scheduling priority for Batch job. + share_identifier: Share identifier for Batch job. + timeout: Timeout configuration for Batch job. + tags: Tags apply to Batch job. These tags are for Batch job only. + experiment_config: Experiment management configuration. + Optionally, the dict can contain four keys: + 'ExperimentName', 'TrialName', 'TrialComponentDisplayName' and 'RunName'. + + Returns: a TrainingQueuedJob object with Batch job ARN and job name. + + """ + if not isinstance(training_job, (EstimatorBase, ModelTrainer)): + raise TypeError( + "training_job must be an instance of EstimatorBase or ModelTrainer, " + f"but got {type(training_job)}" + ) + + training_payload = {} + if isinstance(training_job, EstimatorBase): + if experiment_config is None: + experiment_config = {} + training_job.prepare_workflow_for_training(job_name) + training_args = _TrainingJob.get_train_args(training_job, inputs, experiment_config) + training_payload = training_job.sagemaker_session.get_train_request(**training_args) + else: + if training_job.training_mode != Mode.SAGEMAKER_TRAINING_JOB: + raise ValueError( + "TrainingQueue requires using a ModelTrainer with Mode.SAGEMAKER_TRAINING_JOB" + ) + if experiment_config is not None: + logging.warning( + "ExperimentConfig is not supported for ModelTrainer. " + "It will be ignored when submitting the job." + ) + training_payload = training_job._create_training_job_args( + input_data_config=inputs, boto3=True + ) + + if timeout is None: + timeout = DEFAULT_TIMEOUT + if job_name is None: + job_name = training_payload["TrainingJobName"] + + resp = submit_service_job( + training_payload, + job_name, + self.queue_name, + retry_config, + priority, + timeout, + share_identifier, + tags, + ) + if "jobArn" not in resp or "jobName" not in resp: + raise MissingRequiredArgument( + "jobArn or jobName is missing in response from Batch submit_service_job API" + ) + return TrainingQueuedJob(resp["jobArn"], resp["jobName"]) + + def map( + self, + training_job: Union[EstimatorBase, ModelTrainer], + inputs, + job_names: Optional[List[str]] = None, + retry_config: Optional[Dict] = None, + priority: Optional[int] = None, + share_identifier: Optional[str] = None, + timeout: Optional[Dict] = None, + tags: Optional[Dict] = None, + experiment_config: Optional[Dict] = None, + ) -> List[TrainingQueuedJob]: + """Submit queued jobs to the provided estimator and return a list of TrainingQueuedJob objects. + + Args: + training_job: Training job EstimatorBase or ModelTrainer object. + inputs: List of Training job inputs. + job_names: List of Batch job names. + retry_config: Retry config for the Batch jobs. + priority: Scheduling priority for the Batch jobs. + share_identifier: Share identifier for the Batch jobs. + timeout: Timeout configuration for the Batch jobs. + tags: Tags apply to Batch job. These tags are for Batch job only. + experiment_config: Experiment management configuration. + Optionally, the dict can contain four keys: + 'ExperimentName', 'TrialName', 'TrialComponentDisplayName' and 'RunName'. + + Returns: a list of TrainingQueuedJob objects with each Batch job ARN and job name. + + """ + if experiment_config is None: + experiment_config = {} + + if job_names is not None: + if len(job_names) != len(inputs): + raise ValueError( + "When specified, the number of job names must match the number of inputs" + ) + else: + job_names = [None] * len(inputs) + + queued_batch_job_list = [] + for index, value in enumerate(inputs): + queued_batch_job = self.submit( + training_job, + value, + job_names[index], + retry_config, + priority, + share_identifier, + timeout, + tags, + experiment_config, + ) + queued_batch_job_list.append(queued_batch_job) + + return queued_batch_job_list + + def list_jobs( + self, job_name: Optional[str] = None, status: Optional[str] = JOB_STATUS_RUNNING + ) -> List[TrainingQueuedJob]: + """List Batch jobs according to job_name or status. + + Args: + job_name: Batch job name. + status: Batch job status. + + Returns: A list of QueuedJob. + + """ + filters = None + if job_name: + filters = [{"name": "JOB_NAME", "values": [job_name]}] + status = None # job_status is ignored when job_name is specified. + jobs_to_return = [] + next_token = None + for job_result_dict in list_service_job(self.queue_name, status, filters, next_token): + for job_result in job_result_dict.get("jobSummaryList", []): + if "jobArn" in job_result and "jobName" in job_result: + jobs_to_return.append( + TrainingQueuedJob(job_result["jobArn"], job_result["jobName"]) + ) + else: + logging.warning("Missing JobArn or JobName in Batch ListJobs API") + continue + return jobs_to_return + + def get_job(self, job_name): + """Get a Batch job according to job_name. + + Args: + job_name: Batch job name. + + Returns: The QueuedJob with name matching job_name. + + """ + jobs_to_return = self.list_jobs(job_name) + if len(jobs_to_return) == 0: + raise ValueError(f"Cannot find job: {job_name}") + return jobs_to_return[0] diff --git a/src/sagemaker/aws_batch/training_queued_job.py b/src/sagemaker/aws_batch/training_queued_job.py new file mode 100644 index 0000000000..6bb42c3c61 --- /dev/null +++ b/src/sagemaker/aws_batch/training_queued_job.py @@ -0,0 +1,217 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +"""Define QueuedJob class for AWS Batch service""" +from __future__ import absolute_import + +import logging +import time +import asyncio +from typing import Optional, Dict +import nest_asyncio +from sagemaker.estimator import Estimator +from .batch_api_helper import terminate_service_job, describe_service_job +from .exception import NoTrainingJob, MissingRequiredArgument +from ..utils import get_training_job_name_from_training_job_arn +from .constants import JOB_STATUS_COMPLETED, JOB_STATUS_FAILED, POLL_IN_SECONDS + +logging.basicConfig( + format="%(asctime)s %(message)s", level=logging.INFO, datefmt="%Y-%m-%d %H:%M:%S" +) + + +class TrainingQueuedJob: + """TrainingQueuedJob class for AWS Batch service. + + With this class, customers are able to attach the latest training job to an estimator. + """ + + def __init__(self, job_arn: str, job_name: str): + self.job_arn = job_arn + self.job_name = job_name + self._no_training_job_status = {"SUBMITTED", "PENDING", "RUNNABLE"} + + def get_estimator(self) -> Estimator: + """Attach the latest training job to an estimator and return. + + Returns: an Estimator instance. + + """ + describe_resp = self.describe() + job_status = describe_resp.get("status", "") + if self._training_job_created(job_status): + if "latestAttempt" not in describe_resp: + raise MissingRequiredArgument("No LatestAttempt in describe call") + new_training_job_name = _get_new_training_job_name_from_latest_attempt( + describe_resp["latestAttempt"] + ) + output_estimator = _construct_estimator_from_training_job_name(new_training_job_name) + _remove_system_tags_in_place_in_estimator_object(output_estimator) + return output_estimator + + _output_attempt_history(describe_resp) + raise NoTrainingJob("No Training job created. Job is still waiting in queue") + + def terminate(self, reason: Optional[str] = "Default terminate reason") -> None: + """Terminate Batch job. + + Args: + reason: Reason for terminating a job. + + Returns: None + + """ + terminate_service_job(self.job_arn, reason) + + def describe(self) -> Dict: + """Describe Batch job. + + Returns: A dict which includes job parameters, job status, attempts and so on. + + """ + return describe_service_job(self.job_arn) + + def _training_job_created(self, status: str) -> bool: + """Return True if a Training job has been created + + Args: + status: Job status returned from Batch API. + + Returns: a boolean indicating whether a Training job has been created. + + """ + return status not in self._no_training_job_status + + def result(self, timeout: int = None) -> Dict: + """Fetch the terminal result of the Batch job. + + Args: + timeout: The time to wait for the Batch job to complete. Defaults to ``None``. + + Returns: The results of the Batch job, represented as a Dict. + + """ + nest_asyncio.apply() + loop = asyncio.get_event_loop() + task = loop.create_task(self.fetch_job_results(timeout)) + resp = loop.run_until_complete(task) + return resp + + async def fetch_job_results(self, timeout: int = None) -> Dict: + """Async method that waits for the Batch job to complete or until timeout. + + Args: + timeout: The time to wait for the Batch job to complete. Defaults to ``None``. + + Returns: The results of the Batch job, represented as a Dict, or an Error. + + """ + self.wait(timeout) + + describe_resp = self.describe() + if describe_resp.get("status", "") == JOB_STATUS_COMPLETED: + return describe_resp + if describe_resp.get("status", "") == JOB_STATUS_FAILED: + raise RuntimeError(describe_resp["statusReason"]) + raise TimeoutError("Reached timeout before the Batch job reached a terminal status") + + def wait(self, timeout: int = None) -> Dict: + """Wait for the Batch job to finish. + + This method blocks on the job completing for up to the timeout value (if specified). + If timeout is ``None``, this method will block until the job is completed. + + Args: + timeout (int): Timeout in seconds to wait until the job is completed. ``None`` by + default. + + Returns: The last describe_service_job response for the Batch job. + """ + request_end_time = time.time() + timeout if timeout else None + describe_resp = self.describe() + job_status = describe_resp.get("status", "") + job_completed = job_status in (JOB_STATUS_COMPLETED, JOB_STATUS_FAILED) + + while not job_completed: + if timeout and time.time() > request_end_time: + logging.info( + "Timeout exceeded: %d seconds elapsed. Returning current results", timeout + ) + break + if job_status in (JOB_STATUS_COMPLETED, JOB_STATUS_FAILED): + break + + time.sleep(POLL_IN_SECONDS) + describe_resp = self.describe() + job_status = describe_resp.get("status", "") + job_completed = job_status in (JOB_STATUS_COMPLETED, JOB_STATUS_FAILED) + + return describe_resp + + +def _construct_estimator_from_training_job_name(training_job_name: str) -> Estimator: + """Build Estimator instance from payload. + + Args: + training_job_name: Training job name. + + Returns: an Estimator instance. + + """ + return Estimator.attach(training_job_name) + + +def _output_attempt_history(describe_resp: Dict) -> None: + """Print attempt history if no Training job created. + + Args: + describe_resp: Describe response from Batch API. + + Returns: None + + """ + has_seen_status_reason = False + for i, attempt_dict in enumerate(describe_resp.get("attempts", [])): + if "statusReason" in attempt_dict: + logging.info("Attempt %d - %s", i + 1, attempt_dict["statusReason"]) + has_seen_status_reason = True + if not has_seen_status_reason: + logging.info("No attempts found or no statusReason found.") + + +def _get_new_training_job_name_from_latest_attempt(latest_attempt: Dict) -> str: + """Extract new Training job name from latest attempt in Batch Describe response. + + Args: + latest_attempt: a Dict containing Training job arn. + + Returns: new Training job name or None if not found. + + """ + training_job_arn = latest_attempt.get("serviceResourceId", {}).get("value", None) + return get_training_job_name_from_training_job_arn(training_job_arn) + + +def _remove_system_tags_in_place_in_estimator_object(estimator: Estimator) -> None: + """Remove system tags in place. + + Args: + estimator: input Estimator object. + + Returns: None. Remove system tags in place. + + """ + new_tags = [] + for tag_dict in estimator.tags: + if not tag_dict.get("Key", "").startswith("aws:"): + new_tags.append(tag_dict) + estimator.tags = new_tags diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py index 9b4beae5c4..0055416327 100644 --- a/src/sagemaker/estimator.py +++ b/src/sagemaker/estimator.py @@ -2546,6 +2546,11 @@ def start_new(cls, estimator, inputs, experiment_config): return cls(estimator.sagemaker_session, estimator._current_job_name) + @classmethod + def get_train_args(cls, estimator, inputs, experiment_config): + """A public function which is same as _get_train_args function.""" + return cls._get_train_args(estimator, inputs, experiment_config) + @classmethod def _get_train_args(cls, estimator, inputs, experiment_config): """Constructs a dict of arguments for an Amazon SageMaker training job from the estimator. diff --git a/src/sagemaker/modules/train/model_trainer.py b/src/sagemaker/modules/train/model_trainer.py index 24b7922895..828c5da198 100644 --- a/src/sagemaker/modules/train/model_trainer.py +++ b/src/sagemaker/modules/train/model_trainer.py @@ -27,6 +27,7 @@ from sagemaker_core.resources import TrainingJob from sagemaker_core import shapes from sagemaker_core.shapes import AlgorithmSpecification +from sagemaker_core.main.utils import serialize from pydantic import BaseModel, ConfigDict, PrivateAttr, validate_call @@ -252,6 +253,7 @@ class ModelTrainer(BaseModel): _is_nova_recipe: Optional[bool] = PrivateAttr(default=None) _temp_recipe_train_dir: Optional[TemporaryDirectory] = PrivateAttr(default=None) + _temp_code_dir: Optional[TemporaryDirectory] = PrivateAttr(default=None) CONFIGURABLE_ATTRIBUTES: ClassVar[List[str]] = [ "role", @@ -380,6 +382,8 @@ def __del__(self): if hasattr(self, "__pydantic_fields_set__"): if self._temp_recipe_train_dir is not None: self._temp_recipe_train_dir.cleanup() + if self._temp_code_dir is not None: + self._temp_code_dir.cleanup() def _validate_training_image_and_algorithm_name( self, training_image: Optional[str], algorithm_name: Optional[str] @@ -590,28 +594,25 @@ def _fetch_bucket_name_and_prefix(session: Session) -> str: return f"{session.default_bucket()}/{session.default_bucket_prefix}" return session.default_bucket() - @_telemetry_emitter(feature=Feature.MODEL_TRAINER, func_name="model_trainer.train") - @validate_call - def train( + def _create_training_job_args( self, input_data_config: Optional[List[Union[Channel, InputData]]] = None, - wait: Optional[bool] = True, - logs: Optional[bool] = True, - ): - """Train a model using AWS SageMaker. + boto3: bool = False, + ) -> Dict[str, Any]: + """Create the training job arguments. Args: + input_data_config (Optional[List[Union[Channel, InputData]]]): input_data_config (Optional[List[Union[Channel, InputData]]]): The input data config for the training job. Takes a list of Channel objects or a dictionary of channel names to DataSourceType. DataSourceType can be an S3 URI string, local file path string, S3DataSource object, or FileSystemDataSource object. - wait (Optional[bool]): - Whether to wait for the training job to complete before returning. - Defaults to True. - logs (Optional[bool]): - Whether to display the training container logs while training. - Defaults to True. + boto3 (bool): Whether to return the arguments in boto3 format. Defaults to False. + By default, the arguments are returned in the format used by the SageMaker Core. + + Returns: + Dict[str, Any]: The training job arguments. """ self._populate_intelligent_defaults() current_training_job_name = _get_unique_name(self.base_job_name) @@ -672,16 +673,18 @@ def train( container_arguments = None if self.source_code: if self.training_mode == Mode.LOCAL_CONTAINER: - tmp_dir = TemporaryDirectory(prefix=os.path.join(self.local_container_root + "/")) + self._temp_code_dir = TemporaryDirectory( + prefix=os.path.join(self.local_container_root + "/") + ) else: - tmp_dir = TemporaryDirectory() + self._temp_code_dir = TemporaryDirectory() # Copy everything under container_drivers/ to a temporary directory - shutil.copytree(SM_DRIVERS_LOCAL_PATH, tmp_dir.name, dirs_exist_ok=True) + shutil.copytree(SM_DRIVERS_LOCAL_PATH, self._temp_code_dir.name, dirs_exist_ok=True) # If distributed is provided, overwrite code under /drivers if self.distributed: distributed_driver_dir = self.distributed.driver_dir - driver_dir = os.path.join(tmp_dir.name, "distributed_drivers") + driver_dir = os.path.join(self._temp_code_dir.name, "distributed_drivers") shutil.copytree(distributed_driver_dir, driver_dir, dirs_exist_ok=True) # If source code is provided, create a channel for the source code @@ -696,7 +699,7 @@ def train( final_input_data_config.append(source_code_channel) self._prepare_train_script( - tmp_dir=tmp_dir, + tmp_dir=self._temp_code_dir, source_code=self.source_code, distributed=self.distributed, ) @@ -705,13 +708,13 @@ def train( mp_parameters = self.distributed.smp._to_mp_hyperparameters() string_hyper_parameters.update(mp_parameters) - self._write_source_code_json(tmp_dir=tmp_dir, source_code=self.source_code) - self._write_distributed_json(tmp_dir=tmp_dir, distributed=self.distributed) + self._write_source_code_json(tmp_dir=self._temp_code_dir, source_code=self.source_code) + self._write_distributed_json(tmp_dir=self._temp_code_dir, distributed=self.distributed) # Create an input channel for drivers packaged by the sdk sm_drivers_channel = self.create_input_data_channel( channel_name=SM_DRIVERS, - data_source=tmp_dir.name, + data_source=self._temp_code_dir.name, key_prefix=input_data_key_prefix, ignore_patterns=self.source_code.ignore_patterns, ) @@ -738,40 +741,93 @@ def train( resource_config = self.compute._to_resource_config() vpc_config = self.networking._to_vpc_config() if self.networking else None - if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB: - training_job = TrainingJob.create( - training_job_name=current_training_job_name, - algorithm_specification=algorithm_specification, - hyper_parameters=string_hyper_parameters, - input_data_config=final_input_data_config, - resource_config=resource_config, - vpc_config=vpc_config, - # Public Instance Attributes - session=self.sagemaker_session.boto_session, - role_arn=self.role, - tags=self.tags, - stopping_condition=self.stopping_condition, - output_data_config=self.output_data_config, - checkpoint_config=self.checkpoint_config, - environment=self.environment, - enable_managed_spot_training=self.compute.enable_managed_spot_training, - enable_inter_container_traffic_encryption=( - self.networking.enable_inter_container_traffic_encryption - if self.networking - else None - ), - enable_network_isolation=( - self.networking.enable_network_isolation if self.networking else None - ), - # Private Instance Attributes - remote_debug_config=self._remote_debug_config, - tensor_board_output_config=self._tensorboard_output_config, - retry_strategy=self._retry_strategy, - infra_check_config=self._infra_check_config, - session_chaining_config=self._session_chaining_config, + if boto3: + args = {} + args["TrainingJobName"] = current_training_job_name + args["AlgorithmSpecification"] = algorithm_specification + args["HyperParameters"] = string_hyper_parameters + args["InputDataConfig"] = final_input_data_config + args["ResourceConfig"] = resource_config + args["VpcConfig"] = vpc_config + args["RoleArn"] = self.role + args["Tags"] = self.tags + args["StoppingCondition"] = self.stopping_condition + args["OutputDataConfig"] = self.output_data_config + args["CheckpointConfig"] = self.checkpoint_config + args["Environment"] = self.environment + args["EnableManagedSotTraining"] = self.compute.enable_managed_spot_training + args["EnableInterContainerTrafficEncryption"] = ( + self.networking.enable_inter_container_traffic_encryption + if self.networking + else None ) - self._latest_training_job = training_job + args["EnableNetworkIsolation"] = ( + self.networking.enable_network_isolation if self.networking else None + ) + args["RemoteDebugConfig"] = self._remote_debug_config + args["TensorBoardOutputConfig"] = self._tensorboard_output_config + args["RetryStrategy"] = self._retry_strategy + args["InfraCheckConfig"] = self._infra_check_config + args["SessionChainingConfig"] = self._session_chaining_config + return serialize(args) + else: + args = {} + args["training_job_name"] = current_training_job_name + args["algorithm_specification"] = algorithm_specification + args["hyper_parameters"] = string_hyper_parameters + args["input_data_config"] = final_input_data_config + args["resource_config"] = resource_config + args["vpc_config"] = vpc_config + args["session"] = self.sagemaker_session.boto_session + args["role_arn"] = self.role + args["tags"] = self.tags + args["stopping_condition"] = self.stopping_condition + args["output_data_config"] = self.output_data_config + args["checkpoint_config"] = self.checkpoint_config + args["environment"] = self.environment + args["enable_managed_spot_training"] = self.compute.enable_managed_spot_training + args["enable_inter_container_traffic_encryption"] = ( + self.networking.enable_inter_container_traffic_encryption + if self.networking + else None + ) + args["enable_network_isolation"] = ( + self.networking.enable_network_isolation if self.networking else None + ) + args["remote_debug_config"] = self._remote_debug_config + args["tensor_board_output_config"] = self._tensorboard_output_config + args["retry_strategy"] = self._retry_strategy + args["infra_check_config"] = self._infra_check_config + args["session_chaining_config"] = self._session_chaining_config + return args + @_telemetry_emitter(feature=Feature.MODEL_TRAINER, func_name="model_trainer.train") + @validate_call + def train( + self, + input_data_config: Optional[List[Union[Channel, InputData]]] = None, + wait: Optional[bool] = True, + logs: Optional[bool] = True, + ): + """Train a model using AWS SageMaker. + + Args: + input_data_config (Optional[List[Union[Channel, InputData]]]): + The input data config for the training job. + Takes a list of Channel objects or a dictionary of channel names to DataSourceType. + DataSourceType can be an S3 URI string, local file path string, + S3DataSource object, or FileSystemDataSource object. + wait (Optional[bool]): + Whether to wait for the training job to complete before returning. + Defaults to True. + logs (Optional[bool]): + Whether to display the training container logs while training. + Defaults to True. + """ + args = self._create_training_job_args(input_data_config=input_data_config) + if self.training_mode == Mode.SAGEMAKER_TRAINING_JOB: + training_job = TrainingJob.create(**args) + self._latest_training_job = training_job if wait: training_job.wait(logs=logs) if logs and not wait: @@ -780,19 +836,21 @@ def train( ) else: local_container = _LocalContainer( - training_job_name=_get_unique_name(self.base_job_name), - instance_type=resource_config.instance_type, - instance_count=resource_config.instance_count, - image=algorithm_specification.training_image, + training_job_name=args["training_job_name"], + instance_type=args["resource_config"].instance_type, + instance_count=args["resource_config"].instance_count, + image=args["algorithm_specification"].training_image, container_root=self.local_container_root, sagemaker_session=self.sagemaker_session, - container_entrypoint=algorithm_specification.container_entrypoint, - container_arguments=algorithm_specification.container_arguments, - input_data_config=final_input_data_config, - hyper_parameters=string_hyper_parameters, - environment=self.environment, + container_entrypoint=args["algorithm_specification"].container_entrypoint, + container_arguments=args["algorithm_specification"].container_arguments, + input_data_config=args["input_data_config"], + hyper_parameters=args["hyper_parameters"], + environment=args["environment"], ) local_container.train(wait) + if self._temp_code_dir is not None: + self._temp_code_dir.cleanup() def create_input_data_channel( self, diff --git a/src/sagemaker/session.py b/src/sagemaker/session.py index 2ff561d784..705d9892fe 100644 --- a/src/sagemaker/session.py +++ b/src/sagemaker/session.py @@ -782,7 +782,7 @@ def _append_sagemaker_config_tags(self, tags: List[TagsDict], config_path_to_tag return all_tags - def train( # noqa: C901 + def get_train_request( self, input_mode, input_config, @@ -817,7 +817,7 @@ def train( # noqa: C901 retry_strategy=None, remote_debug_config=None, session_chaining_config=None, - ): + ) -> Dict: """Create an Amazon SageMaker training job. Args: @@ -960,12 +960,7 @@ def train( # noqa: C901 "EnableInfraCheck": True, } Returns: - str: ARN of the training job, if it is created. - - Raises: - - botocore.exceptions.ClientError: If Sagemaker throws an exception while creating - training job. - - ValueError: If both image_uri and algorithm are provided, or if neither is provided. + Dict: a Dict containing CreateTrainingJob request. """ tags = _append_project_tags(format_tags(tags)) tags = self._append_sagemaker_config_tags( @@ -1047,6 +1042,228 @@ def train( # noqa: C901 environment=environment, retry_strategy=retry_strategy, ) + return train_request + + def train( # noqa: C901 + self, + input_mode, + input_config, + role=None, + job_name=None, + output_config=None, + resource_config=None, + vpc_config=None, + hyperparameters=None, + stop_condition=None, + tags=None, + metric_definitions=None, + enable_network_isolation=None, + image_uri=None, + training_image_config=None, + infra_check_config=None, + container_entry_point=None, + container_arguments=None, + algorithm_arn=None, + encrypt_inter_container_traffic=None, + use_spot_instances=False, + checkpoint_s3_uri=None, + checkpoint_local_path=None, + experiment_config=None, + debugger_rule_configs=None, + debugger_hook_config=None, + tensorboard_output_config=None, + enable_sagemaker_metrics=None, + profiler_rule_configs=None, + profiler_config=None, + environment: Optional[Dict[str, str]] = None, + retry_strategy=None, + remote_debug_config=None, + session_chaining_config=None, + ): + """Create an Amazon SageMaker training job. + + Args: + input_mode (str): The input mode that the algorithm supports. Valid modes: + * 'File' - Amazon SageMaker copies the training dataset from the S3 location to + a directory in the Docker container. + * 'Pipe' - Amazon SageMaker streams data directly from S3 to the container via a + Unix-named pipe. + * 'FastFile' - Amazon SageMaker streams data from S3 on demand instead of + downloading the entire dataset before training begins. + input_config (list): A list of Channel objects. Each channel is a named input source. + Please refer to the format details described: + https://botocore.readthedocs.io/en/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job + role (str): An AWS IAM role (either name or full ARN). The Amazon SageMaker training + jobs and APIs that create Amazon SageMaker endpoints use this role to access + training data and model artifacts. You must grant sufficient permissions to this + role. + job_name (str): Name of the training job being created. + output_config (dict): The S3 URI where you want to store the training results and + optional KMS key ID. + resource_config (dict): Contains values for ResourceConfig: + * instance_count (int): Number of EC2 instances to use for training. + The key in resource_config is 'InstanceCount'. + * instance_type (str): Type of EC2 instance to use for training, for example, + 'ml.c4.xlarge'. The key in resource_config is 'InstanceType'. + vpc_config (dict): Contains values for VpcConfig: + * subnets (list[str]): List of subnet ids. + The key in vpc_config is 'Subnets'. + * security_group_ids (list[str]): List of security group ids. + The key in vpc_config is 'SecurityGroupIds'. + hyperparameters (dict): Hyperparameters for model training. The hyperparameters are + made accessible as a dict[str, str] to the training code on SageMaker. For + convenience, this accepts other types for keys and values, but ``str()`` will be + called to convert them before training. + stop_condition (dict): Defines when training shall finish. Contains entries that can + be understood by the service like ``MaxRuntimeInSeconds``. + tags (Optional[Tags]): Tags for labeling a training job. For more, see + https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html. + metric_definitions (list[dict]): A list of dictionaries that defines the metric(s) + used to evaluate the training jobs. Each dictionary contains two keys: 'Name' for + the name of the metric, and 'Regex' for the regular expression used to extract the + metric from the logs. + enable_network_isolation (bool): Whether to request for the training job to run with + network isolation or not. + image_uri (str): Docker image containing training code. + training_image_config(dict): Training image configuration. + Optionally, the dict can contain 'TrainingRepositoryAccessMode' and + 'TrainingRepositoryCredentialsProviderArn' (under 'TrainingRepositoryAuthConfig'). + For example, + + .. code:: python + + training_image_config = { + "TrainingRepositoryAccessMode": "Vpc", + "TrainingRepositoryAuthConfig": { + "TrainingRepositoryCredentialsProviderArn": + "arn:aws:lambda:us-west-2:1234567890:function:test" + }, + } + + If TrainingRepositoryAccessMode is set to Vpc, the training image is accessed + through a private Docker registry in customer Vpc. If it's set to Platform or None, + the training image is accessed through ECR. + If TrainingRepositoryCredentialsProviderArn is provided, the credentials to + authenticate to the private Docker registry will be retrieved from this AWS Lambda + function. (default: ``None``). When it's set to None, SageMaker will not do + authentication before pulling the image in the private Docker registry. + container_entry_point (List[str]): Optional. The entrypoint script for a Docker + container used to run a training job. This script takes precedence over + the default train processing instructions. + container_arguments (List[str]): Optional. The arguments for a container used to run + a training job. + algorithm_arn (str): Algorithm Arn from Marketplace. + encrypt_inter_container_traffic (bool): Specifies whether traffic between training + containers is encrypted for the training job (default: ``False``). + use_spot_instances (bool): whether to use spot instances for training. + checkpoint_s3_uri (str): The S3 URI in which to persist checkpoints + that the algorithm persists (if any) during training. (default: + ``None``). + checkpoint_local_path (str): The local path that the algorithm + writes its checkpoints to. SageMaker will persist all files + under this path to `checkpoint_s3_uri` continually during + training. On job startup the reverse happens - data from the + s3 location is downloaded to this path before the algorithm is + started. If the path is unset then SageMaker assumes the + checkpoints will be provided under `/opt/ml/checkpoints/`. + (default: ``None``). + experiment_config (dict[str, str]): Experiment management configuration. + Optionally, the dict can contain four keys: + 'ExperimentName', 'TrialName', 'TrialComponentDisplayName' and 'RunName'. + The behavior of setting these keys is as follows: + * If `ExperimentName` is supplied but `TrialName` is not a Trial will be + automatically created and the job's Trial Component associated with the Trial. + * If `TrialName` is supplied and the Trial already exists the job's Trial Component + will be associated with the Trial. + * If both `ExperimentName` and `TrialName` are not supplied the trial component + will be unassociated. + * `TrialComponentDisplayName` is used for display in Studio. + * `RunName` is used to record an experiment run. + enable_sagemaker_metrics (bool): enable SageMaker Metrics Time + Series. For more information see: + https://docs.aws.amazon.com/sagemaker/latest/dg/API_AlgorithmSpecification.html + #SageMaker-Type + -AlgorithmSpecification-EnableSageMakerMetricsTimeSeries + (default: ``None``). + profiler_rule_configs (list[dict]): A list of profiler rule + configurations.src/sagemaker/lineage/artifact.py:285 + profiler_config (dict): Configuration for how profiling information is emitted + with SageMaker Profiler. (default: ``None``). + remote_debug_config(dict): Configuration for RemoteDebug. (default: ``None``) + The dict can contain 'EnableRemoteDebug'(bool). + For example, + + .. code:: python + + remote_debug_config = { + "EnableRemoteDebug": True, + } + session_chaining_config(dict): Configuration for SessionChaining. (default: ``None``) + The dict can contain 'EnableSessionTagChaining'(bool). + For example, + + .. code:: python + + session_chaining_config = { + "EnableSessionTagChaining": True, + } + environment (dict[str, str]) : Environment variables to be set for + use during training job (default: ``None``) + retry_strategy(dict): Defines RetryStrategy for InternalServerFailures. + * max_retry_attsmpts (int): Number of times a job should be retried. + The key in RetryStrategy is 'MaxRetryAttempts'. + infra_check_config(dict): Infra check configuration. + Optionally, the dict can contain 'EnableInfraCheck'(bool). + For example, + + .. code:: python + + infra_check_config = { + "EnableInfraCheck": True, + } + Returns: + str: ARN of the training job, if it is created. + + Raises: + - botocore.exceptions.ClientError: If Sagemaker throws an exception while creating + training job. + - ValueError: If both image_uri and algorithm are provided, or if neither is provided. + """ + train_request = self.get_train_request( + input_mode, + input_config, + role, + job_name, + output_config, + resource_config, + vpc_config, + hyperparameters, + stop_condition, + tags, + metric_definitions, + enable_network_isolation, + image_uri, + training_image_config, + infra_check_config, + container_entry_point, + container_arguments, + algorithm_arn, + encrypt_inter_container_traffic, + use_spot_instances, + checkpoint_s3_uri, + checkpoint_local_path, + experiment_config, + debugger_rule_configs, + debugger_hook_config, + tensorboard_output_config, + enable_sagemaker_metrics, + profiler_rule_configs, + profiler_config, + environment, + retry_strategy, + remote_debug_config, + session_chaining_config, + ) def submit(request): try: diff --git a/src/sagemaker/utils.py b/src/sagemaker/utils.py index d4faa5ad9f..2a31dfab04 100644 --- a/src/sagemaker/utils.py +++ b/src/sagemaker/utils.py @@ -1502,6 +1502,24 @@ def instance_supports_kms(instance_type: str) -> bool: return volume_size_supported(instance_type) +def get_training_job_name_from_training_job_arn(training_job_arn: str) -> str: + """Extract Training job name from Training job arn. + + Args: + training_job_arn: Training job arn. + + Returns: Training job name. + + """ + if training_job_arn is None: + return None + pattern = "arn:aws[a-z-]*:sagemaker:[a-z0-9-]*:[0-9]{12}:training-job/(.+)" + match = re.match(pattern, training_job_arn) + if match: + return match.group(1) + return None + + def get_instance_type_family(instance_type: str) -> str: """Return the family of the instance type. diff --git a/tests/data/modules/script_mode/custom_script.py b/tests/data/modules/script_mode/custom_script.py index 26e5826267..a57ddee743 100644 --- a/tests/data/modules/script_mode/custom_script.py +++ b/tests/data/modules/script_mode/custom_script.py @@ -76,14 +76,60 @@ def predict_fn(input_data, model): return model(input_data.float()).numpy()[0] +def parse_args(): + """ + Parse the command line arguments + """ + + parser = argparse.ArgumentParser() + parser.add_argument( + "--model-dir", + type=str, + default=os.environ.get("SM_MODEL_DIR", os.path.join(current_dir, "data/model")), + help="Directory to save the model", + ) + parser.add_argument( + "--train-dir", + type=str, + default=os.environ.get("SM_CHANNEL_TRAIN", os.path.join(current_dir, "data/train")), + help="Directory containing training data", + ) + parser.add_argument( + "--test-dir", + type=str, + default=os.environ.get("SM_CHANNEL_TEST", os.path.join(current_dir, "data/test")), + help="Directory containing testing data", + ) + parser.add_argument( + "--batch-size", + type=int, + default=64, + help="Batch size for training", + ) + parser.add_argument( + "--epochs", + type=int, + default=1, + help="Number of epochs for training", + ) + parser.add_argument( + "--learning-rate", + type=float, + default=0.1, + help="Learning rate for training", + ) + return parser.parse_args() + + def train(): """ Train the PyTorch model """ + args = parse_args() # Directories: train, test and model - train_dir = os.path.join(current_dir, "data/train") - test_dir = os.path.join(current_dir, "data/test") - model_dir = os.environ.get("SM_MODEL_DIR", os.path.join(current_dir, "data/model")) + train_dir = args.train_dir + test_dir = args.test_dir + model_dir = args.model_dir # Load the training and testing data x_train, y_train = get_train_data(train_dir) @@ -91,9 +137,9 @@ def train(): train_ds = TensorDataset(x_train, y_train) # Training parameters - used to configure the training loop - batch_size = 64 - epochs = 1 - learning_rate = 0.1 + batch_size = args.batch_size + epochs = args.epochs + learning_rate = args.learning_rate logger.info( "batch_size = {}, epochs = {}, learning rate = {}".format(batch_size, epochs, learning_rate) ) diff --git a/tests/integ/sagemaker/aws_batch/__init__.py b/tests/integ/sagemaker/aws_batch/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/integ/sagemaker/aws_batch/manager.py b/tests/integ/sagemaker/aws_batch/manager.py new file mode 100644 index 0000000000..b417f86b53 --- /dev/null +++ b/tests/integ/sagemaker/aws_batch/manager.py @@ -0,0 +1,133 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +import time + + +class BatchTestResourceManager: + + def __init__( + self, + batch_client, + queue_name="pysdk-test-queue", + service_env_name="pysdk-test-queue-service-environment", + ): + self.batch_client = batch_client + self.queue_name = queue_name + self.service_environment_name = service_env_name + + def _create_or_get_service_environment(self, service_environment_name): + print(f"Creating service environment: {service_environment_name}") + try: + response = self.batch_client.create_service_environment( + serviceEnvironmentName=service_environment_name, + serviceEnvironmentType="SAGEMAKER_TRAINING", + capacityLimits=[{"maxCapacity": 10, "capacityUnit": "NUM_INSTANCES"}], + ) + print(f"Service environment {service_environment_name} created successfully.") + return response + except Exception as e: + if "Object already exists" in str(e): + print("Resource already exists. Fetching existing resource.") + response = self.batch_client.describe_service_environments( + serviceEnvironments=[service_environment_name] + ) + return response["serviceEnvironments"][0] + else: + print(f"Error creating service environment: {e}") + raise + + def _create_or_get_queue(self, queue_name, service_environment_arn): + + print(f"Creating job queue: {queue_name}") + try: + response = self.batch_client.create_job_queue( + jobQueueName=queue_name, + priority=1, + computeEnvironmentOrder=[], + serviceEnvironmentOrder=[ + { + "order": 1, + "serviceEnvironment": service_environment_arn, + }, + ], + jobQueueType="SAGEMAKER_TRAINING", + ) + print(f"Job queue {queue_name} created successfully.") + return response + except Exception as e: + if "Object already exists" in str(e): + print("Resource already exists. Fetching existing resource.") + response = self.batch_client.describe_job_queues(jobQueues=[queue_name]) + return response["jobQueues"][0] + else: + print(f"Error creating job queue: {e}") + raise + + def _update_queue_state(self, queue_name, state): + try: + print(f"Updating queue {queue_name} to state {state}") + response = self.batch_client.update_job_queue(jobQueue=queue_name, state=state) + return response + except Exception as e: + print(f"Error updating queue: {e}") + + def _update_service_environment_state(self, service_environment_name, state): + print(f"Updating service environment {service_environment_name} to state {state}") + try: + response = self.batch_client.update_service_environment( + serviceEnvironment=service_environment_name, state=state + ) + return response + except Exception as e: + print(f"Error updating service environment: {e}") + + def _wait_for_queue_state(self, queue_name, state): + print(f"Waiting for queue {queue_name} to be {state}...") + while True: + response = self.batch_client.describe_job_queues(jobQueues=[queue_name]) + print(f"Current state: {response}") + if response["jobQueues"][0]["state"] == state: + break + time.sleep(5) + print(f"Queue {queue_name} is now {state}.") + + def _wait_for_service_environment_state(self, service_environment_name, state): + print(f"Waiting for service environment {service_environment_name} to be {state}...") + while True: + response = self.batch_client.describe_service_environments( + serviceEnvironments=[service_environment_name] + ) + print(f"Current state: {response}") + if response["serviceEnvironments"][0]["state"] == state: + break + time.sleep(5) + print(f"Service environment {service_environment_name} is now {state}.") + + def get_or_create_resources(self, queue_name=None, service_environment_name=None): + queue_name = queue_name or self.queue_name + service_environment_name = service_environment_name or self.service_environment_name + + service_environment = self._create_or_get_service_environment(service_environment_name) + if service_environment.get("state") != "ENABLED": + self._update_service_environment_state(service_environment_name, "ENABLED") + self._wait_for_service_environment_state(service_environment_name, "ENABLED") + time.sleep(10) + + queue = self._create_or_get_queue(queue_name, service_environment["serviceEnvironmentArn"]) + if queue.get("state") != "ENABLED": + self._update_queue_state(queue_name, "ENABLED") + self._wait_for_queue_state(queue_name, "ENABLED") + time.sleep(10) + return queue, service_environment diff --git a/tests/integ/sagemaker/aws_batch/test_queue.py b/tests/integ/sagemaker/aws_batch/test_queue.py new file mode 100644 index 0000000000..20b8de55c1 --- /dev/null +++ b/tests/integ/sagemaker/aws_batch/test_queue.py @@ -0,0 +1,93 @@ +# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"). You +# may not use this file except in compliance with the License. A copy of +# the License is located at +# +# http://aws.amazon.com/apache2.0/ +# +# or in the "license" file accompanying this file. This file is +# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF +# ANY KIND, either express or implied. See the License for the specific +# language governing permissions and limitations under the License. +from __future__ import absolute_import + +import boto3 +import botocore +import pytest + +from sagemaker.modules.train import ModelTrainer +from sagemaker.modules.configs import SourceCode, InputData, Compute + +from sagemaker.aws_batch.training_queue import TrainingQueue + +from tests.integ import DATA_DIR +from tests.integ.sagemaker.modules.conftest import modules_sagemaker_session # noqa: F401 +from tests.integ.sagemaker.modules.train.test_model_trainer import ( + DEFAULT_CPU_IMAGE, +) +from tests.integ.sagemaker.aws_batch.manager import BatchTestResourceManager + + +@pytest.fixture(scope="module") +def batch_client(): + return boto3.client("batch", region_name="us-west-2") + + +@pytest.fixture(scope="function") +def batch_test_resource_manager(batch_client): + resource_manager = BatchTestResourceManager(batch_client=batch_client) + resource_manager.get_or_create_resources() + return resource_manager + + +def test_model_trainer_submit(batch_test_resource_manager, modules_sagemaker_session): # noqa: F811 + queue_name = batch_test_resource_manager.queue_name + + source_code = SourceCode( + source_dir=f"{DATA_DIR}/modules/script_mode/", + requirements="requirements.txt", + entry_script="custom_script.py", + ) + hyperparameters = { + "batch-size": 32, + "epochs": 1, + "learning-rate": 0.01, + } + compute = Compute(instance_type="ml.m5.2xlarge") + model_trainer = ModelTrainer( + sagemaker_session=modules_sagemaker_session, + training_image=DEFAULT_CPU_IMAGE, + source_code=source_code, + compute=compute, + hyperparameters=hyperparameters, + base_job_name="test-batch-model-trainer", + ) + train_data = InputData( + channel_name="train", + data_source=f"{DATA_DIR}/modules/script_mode/data/train/", + ) + test_data = InputData( + channel_name="test", + data_source=f"{DATA_DIR}/modules/script_mode/data/test/", + ) + + training_queue = TrainingQueue(queue_name=queue_name) + + try: + queued_job = training_queue.submit( + training_job=model_trainer, + inputs=[train_data, test_data], + ) + except botocore.exceptions.ClientError as e: + print(e.response["ResponseMetadata"]) + print(e.response["Error"]["Message"]) + raise e + res = queued_job.describe() + assert res is not None + assert res["status"] == "SUBMITTED" + + queued_job.wait(timeout=1800) + res = queued_job.describe() + assert res is not None + assert res["status"] == "SUCCEEDED" diff --git a/tests/integ/sagemaker/feature_store/feature_processor/test_feature_processor.py b/tests/integ/sagemaker/feature_store/feature_processor/test_feature_processor_integ.py similarity index 100% rename from tests/integ/sagemaker/feature_store/feature_processor/test_feature_processor.py rename to tests/integ/sagemaker/feature_store/feature_processor/test_feature_processor_integ.py diff --git a/tests/integ/sagemaker/modules/conftest.py b/tests/integ/sagemaker/modules/conftest.py index c3de81157a..d6d3877de4 100644 --- a/tests/integ/sagemaker/modules/conftest.py +++ b/tests/integ/sagemaker/modules/conftest.py @@ -29,7 +29,7 @@ def modules_sagemaker_session(): os.environ["AWS_DEFAULT_REGION"] = DEFAULT_REGION region_manual_set = True else: - region_manual_set = True + region_manual_set = False boto_session = boto3.Session(region_name=os.environ["AWS_DEFAULT_REGION"]) sagemaker_session = Session(boto_session=boto_session) diff --git a/tests/unit/sagemaker/aws_batch/__init__.py b/tests/unit/sagemaker/aws_batch/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/unit/sagemaker/aws_batch/constants.py b/tests/unit/sagemaker/aws_batch/constants.py new file mode 100644 index 0000000000..8745e3558f --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/constants.py @@ -0,0 +1,72 @@ +from __future__ import absolute_import + + +TRAINING_JOB_NAME = "my-training-job" +TRAINING_IMAGE = "763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:1.8.0-cpu-py3" +TRAINING_INPUT_MODE = "File" +CONTAINER_ENTRYPOINT = ["echo", "hello"] +EXECUTION_ROLE = "myrole" +S3_OUTPUT_PATH = "s3://output" +INSTANCE_TYPE = "ml.m4.xlarge" +INSTANCE_COUNT = 1 +VOLUME_SIZE_IN_GB = 1 +MAX_RUNTIME_IN_SECONDS = 600 +TRAINING_JOB_ARN = "arn:aws:sagemaker:us-west-2:476748761737:training-job/jobName" +JOB_NAME = "jobName" +JOB_NAME_IN_PAYLOAD = "jobNameInPayload" +JOB_ID = "123" +JOB_ARN = "arn:batch:job" +JOB_QUEUE = "testQueue" +JOB_STATUS_RUNNABLE = "RUNNABLE" +JOB_STATUS_RUNNING = "RUNNING" +JOB_STATUS_COMPLETED = "SUCCEEDED" +JOB_STATUS_FAILED = "FAILED" +NEXT_TOKEN = "SomeNextToken" +SCHEDULING_PRIORITY = 1 +ATTEMPT_DURATION_IN_SECONDS = 100 +REASON = "killed by Batch API" +SHARE_IDENTIFIER = "shareId" +BATCH_TAGS = {"batch_k": "batch_v"} +TRAINING_TAGS = [{"Key": "training_k", "Value": "training_v"}] +TRAINING_TAGS_DUPLICATING_BATCH_TAGS = [ + *TRAINING_TAGS, + {"Key": "batch_k", "Value": "this value should win"}, +] +TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS = {"training_k": "training_v"} +MERGED_TAGS = {**BATCH_TAGS, **TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS} +MERGED_TAGS_TRAINING_OVERRIDE = { + **TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS, + "batch_k": "this value should win", +} +EXPERIMENT_CONFIG_EMPTY = {} + +TRAINING_JOB_PAYLOAD_IN_PASCALCASE = {"TrainingJobName": JOB_NAME_IN_PAYLOAD} +TIMEOUT_CONFIG = {"attemptDurationSeconds": ATTEMPT_DURATION_IN_SECONDS} +SUBMIT_SERVICE_JOB_RESP = {"jobArn": JOB_ARN, "jobName": JOB_NAME, "jobId": JOB_ID} +FIRST_LIST_SERVICE_JOB_RESP = { + "jobSummaryList": [{"jobName": JOB_NAME, "jobArn": JOB_ARN}], + "nextToken": NEXT_TOKEN, +} +SECOND_LIST_SERVICE_JOB_RESP = { + "jobSummaryList": [ + {"jobName": JOB_NAME, "jobArn": JOB_ARN}, + {"jobName": JOB_NAME, "jobArn": JOB_ARN}, + ], + "nextToken": NEXT_TOKEN, +} +INCORRECT_FIRST_LIST_SERVICE_JOB_RESP = { + "jobSummaryList": [{"jobName": JOB_NAME}], + "nextToken": NEXT_TOKEN, +} +EMPTY_LIST_SERVICE_JOB_RESP = {"jobSummaryList": [], "nextToken": None} +DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG = { + "attempts": 1, + "evaluateOnExit": [ + { + "action": "RETRY", + "onStatusReason": "Received status from SageMaker:InternalServerError: " + "We encountered an internal error. Please try again.", + }, + {"action": "EXIT", "onStatusReason": "*"}, + ], +} diff --git a/tests/unit/sagemaker/aws_batch/mock_client.py b/tests/unit/sagemaker/aws_batch/mock_client.py new file mode 100644 index 0000000000..c13bb9db93 --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/mock_client.py @@ -0,0 +1,44 @@ +from __future__ import absolute_import +from typing import Optional, List, Dict +from .constants import ( + JOB_ARN, + JOB_ID, + FIRST_LIST_SERVICE_JOB_RESP, + EMPTY_LIST_SERVICE_JOB_RESP, + JOB_STATUS_RUNNING, + TIMEOUT_CONFIG, +) + + +class MockClient: + def submit_service_job( + self, + jobName, + jobQueue, + serviceRequestPayload, + serviceJobType, + retryStrategy: Optional[Dict] = None, + schedulingPriority: Optional[int] = None, + shareIdentifier: Optional[str] = "", + tags: Optional[Dict] = None, + timeoutConfig: Optional[Dict] = TIMEOUT_CONFIG, + ): + return {"jobArn": JOB_ARN, "jobName": jobName, "jobId": JOB_ID} + + def describe_service_job(self, jobId): + return {"jobId": jobId} + + def terminate_service_job(self, jobId, reason): + return {} + + def list_service_jobs( + self, + jobQueue, + jobStatus: Optional[str] = JOB_STATUS_RUNNING, + nextToken: Optional[str] = "", + filters: Optional[List] = [], + ): + if nextToken: + return FIRST_LIST_SERVICE_JOB_RESP + else: + return EMPTY_LIST_SERVICE_JOB_RESP diff --git a/tests/unit/sagemaker/aws_batch/mock_estimator.py b/tests/unit/sagemaker/aws_batch/mock_estimator.py new file mode 100644 index 0000000000..aa3d9e1b20 --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/mock_estimator.py @@ -0,0 +1,35 @@ +from __future__ import absolute_import +from sagemaker.estimator import Estimator +from sagemaker.pytorch import PyTorch + + +class Estimator(Estimator): + def __init__(self): + self.sagemaker_session = Session() + self.tags = [ + {"Key": "batch-non-prod", "Value": "true"}, + {"Key": "batch-training-job-name", "Value": "training-job"}, + ] + + def prepare_workflow_for_training(self, job_name): + pass + + +class PyTorch(PyTorch): + def __init__(self): + self.sagemaker_session = Session() + self.tags = [ + {"Key": "batch-non-prod", "Value": "true"}, + {"Key": "batch-training-job-name", "Value": "training-job"}, + ] + + def prepare_workflow_for_training(self, job_name): + pass + + +class Session: + def __init__(self): + pass + + def get_train_request(self, **kwargs): + return kwargs diff --git a/tests/unit/sagemaker/aws_batch/test_batch_api_helper.py b/tests/unit/sagemaker/aws_batch/test_batch_api_helper.py new file mode 100644 index 0000000000..e9384c135c --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/test_batch_api_helper.py @@ -0,0 +1,186 @@ +from __future__ import absolute_import +from sagemaker.aws_batch.batch_api_helper import ( + submit_service_job, + terminate_service_job, + describe_service_job, + list_service_job, + __merge_tags, +) + +import json +import pytest +from mock.mock import patch + +from sagemaker.aws_batch.constants import ( + DEFAULT_TIMEOUT, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SAGEMAKER_TRAINING, +) +from .mock_client import MockClient +from .constants import ( + JOB_NAME, + JOB_QUEUE, + SCHEDULING_PRIORITY, + JOB_ID, + REASON, + SHARE_IDENTIFIER, + BATCH_TAGS, + TRAINING_TAGS, + TRAINING_TAGS_DUPLICATING_BATCH_TAGS, + TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS, + MERGED_TAGS, + MERGED_TAGS_TRAINING_OVERRIDE, + JOB_STATUS_RUNNING, + NEXT_TOKEN, +) + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +def test_submit_service_job(patched_get_batch_boto_client): + patched_get_batch_boto_client.return_value = MockClient() + training_payload = {} + resp = submit_service_job( + training_payload, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + DEFAULT_TIMEOUT, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + assert resp["jobName"] == JOB_NAME + assert "jobArn" in resp + assert "jobId" in resp + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +@patch("sagemaker.aws_batch.batch_api_helper.__merge_tags") +@pytest.mark.parametrize( + "batch_tags,training_tags", + [ + (BATCH_TAGS, TRAINING_TAGS), + (None, TRAINING_TAGS), + ({}, TRAINING_TAGS), + (BATCH_TAGS, None), + (BATCH_TAGS, []), + ], +) +def test_submit_service_job_called_with_merged_tags( + patched_merge_tags, patched_get_batch_boto_client, batch_tags, training_tags +): + mock_client = MockClient() + patched_get_batch_boto_client.return_value = mock_client + patched_merge_tags.return_value = MERGED_TAGS + + with patch.object( + mock_client, "submit_service_job", wraps=mock_client.submit_service_job + ) as wrapped_submit_service_job: + training_payload = {"Tags": training_tags} + resp = submit_service_job( + training_payload, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + DEFAULT_TIMEOUT, + SHARE_IDENTIFIER, + batch_tags, + ) + assert resp["jobName"] == JOB_NAME + assert "jobArn" in resp + assert "jobId" in resp + patched_merge_tags.assert_called_once_with(batch_tags, training_tags) + wrapped_submit_service_job.assert_called_once_with( + jobName=JOB_NAME, + jobQueue=JOB_QUEUE, + retryStrategy=DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + serviceJobType=SAGEMAKER_TRAINING, + serviceRequestPayload=json.dumps(training_payload), + timeoutConfig=DEFAULT_TIMEOUT, + schedulingPriority=SCHEDULING_PRIORITY, + shareIdentifier=SHARE_IDENTIFIER, + tags={**MERGED_TAGS}, + ) + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +@patch("sagemaker.aws_batch.batch_api_helper.__merge_tags") +def test_submit_service_job_not_called_with_tags(patched_merge_tags, patched_get_batch_boto_client): + mock_client = MockClient() + patched_get_batch_boto_client.return_value = mock_client + patched_merge_tags.return_value = MERGED_TAGS + + with patch.object( + mock_client, "submit_service_job", wraps=mock_client.submit_service_job + ) as wrapped_submit_service_job: + training_payload = {} + resp = submit_service_job( + training_payload, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + DEFAULT_TIMEOUT, + SHARE_IDENTIFIER, + ) + assert resp["jobName"] == JOB_NAME + assert "jobArn" in resp + assert "jobId" in resp + patched_merge_tags.assert_not_called() + wrapped_submit_service_job.assert_called_once_with( + jobName=JOB_NAME, + jobQueue=JOB_QUEUE, + retryStrategy=DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + serviceJobType=SAGEMAKER_TRAINING, + serviceRequestPayload=json.dumps(training_payload), + timeoutConfig=DEFAULT_TIMEOUT, + schedulingPriority=SCHEDULING_PRIORITY, + shareIdentifier=SHARE_IDENTIFIER, + ) + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +def test_describe_service_job(patched_get_batch_boto_client): + patched_get_batch_boto_client.return_value = MockClient() + resp = describe_service_job(job_id=JOB_ID) + assert resp["jobId"] == JOB_ID + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +def test_terminate_service_job(patched_get_batch_boto_client): + patched_get_batch_boto_client.return_value = MockClient() + resp = terminate_service_job(job_id=JOB_ID, reason=REASON) + assert len(resp) == 0 + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +def test_list_service_job_has_next_token(patched_get_batch_boto_client): + patched_get_batch_boto_client.return_value = MockClient() + gen = list_service_job(job_queue=None, job_status=JOB_STATUS_RUNNING, next_token=NEXT_TOKEN) + resp = next(gen) + assert resp["nextToken"] == NEXT_TOKEN + + +@patch("sagemaker.aws_batch.batch_api_helper.get_batch_boto_client") +def test_list_service_job_no_next_token(patched_get_batch_boto_client): + patched_get_batch_boto_client.return_value = MockClient() + gen = list_service_job(job_queue=None, job_status=JOB_STATUS_RUNNING, next_token=None) + resp = next(gen) + assert resp["nextToken"] is None + + +@pytest.mark.parametrize( + "batch_tags,training_tags,expected", + [ + (BATCH_TAGS, TRAINING_TAGS, MERGED_TAGS), + (BATCH_TAGS, TRAINING_TAGS_DUPLICATING_BATCH_TAGS, MERGED_TAGS_TRAINING_OVERRIDE), + (BATCH_TAGS, None, BATCH_TAGS), + (BATCH_TAGS, [], BATCH_TAGS), + (None, TRAINING_TAGS, TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS), + ({}, TRAINING_TAGS, TRAINING_TAGS_CONVERTED_TO_BATCH_TAGS), + ], +) +def test___merge_tags(batch_tags, training_tags, expected): + result = __merge_tags(batch_tags=batch_tags, training_tags=training_tags) + assert result == expected diff --git a/tests/unit/sagemaker/aws_batch/test_training_queue.py b/tests/unit/sagemaker/aws_batch/test_training_queue.py new file mode 100644 index 0000000000..6fee3efad7 --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/test_training_queue.py @@ -0,0 +1,411 @@ +from __future__ import absolute_import +from sagemaker.aws_batch.constants import DEFAULT_TIMEOUT +from sagemaker.aws_batch.exception import MissingRequiredArgument +from sagemaker.aws_batch.training_queue import TrainingQueue + +from unittest.mock import Mock, call +from mock.mock import patch +import pytest + +from sagemaker.modules.train.model_trainer import ModelTrainer, Mode +from sagemaker.estimator import _TrainingJob +from .constants import ( + JOB_QUEUE, + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + JOB_ARN, + SUBMIT_SERVICE_JOB_RESP, + JOB_NAME_IN_PAYLOAD, + JOB_STATUS_RUNNING, + EMPTY_LIST_SERVICE_JOB_RESP, + FIRST_LIST_SERVICE_JOB_RESP, + INCORRECT_FIRST_LIST_SERVICE_JOB_RESP, + EXPERIMENT_CONFIG_EMPTY, + SECOND_LIST_SERVICE_JOB_RESP, + TRAINING_JOB_PAYLOAD_IN_PASCALCASE, +) +from .mock_estimator import Estimator, PyTorch + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_submit_with_timeout(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + + queue = TrainingQueue(JOB_QUEUE) + queue_job = queue.submit( + Estimator(), + {}, + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + patched_submit_service_job.assert_called_once_with( + TRAINING_JOB_PAYLOAD_IN_PASCALCASE, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + TIMEOUT_CONFIG, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + assert queue_job.job_name == JOB_NAME + assert queue_job.job_arn == JOB_ARN + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_submit_use_default_timeout(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + + queue = TrainingQueue(JOB_QUEUE) + queue.submit( + Estimator(), + {}, + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + None, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + patched_submit_service_job.assert_called_once_with( + TRAINING_JOB_PAYLOAD_IN_PASCALCASE, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + DEFAULT_TIMEOUT, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_submit_with_job_name(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + + queue = TrainingQueue(JOB_QUEUE) + queue.submit( + Estimator(), + {}, + None, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + patched_submit_service_job.assert_called_once_with( + TRAINING_JOB_PAYLOAD_IN_PASCALCASE, + JOB_NAME_IN_PAYLOAD, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + TIMEOUT_CONFIG, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_submit_encounter_error(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = {} + + queue = TrainingQueue(JOB_QUEUE) + with pytest.raises(MissingRequiredArgument): + queue.submit( + Estimator(), + {}, + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + + +def test_queue_map_with_job_names_mismatch_input_length_encounter_error(): + queue = TrainingQueue(JOB_QUEUE) + with pytest.raises(ValueError): + queue.map(Estimator(), {}, [JOB_NAME]) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_map_happy_case(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + input_list = {"test-input", "test-input-2"} + + queue = TrainingQueue(JOB_QUEUE) + queue.map( + Estimator(), + input_list, + None, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + assert patched_submit_service_job.call_count == len(input_list) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_queue_map_with_job_names(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + input_list = {"test-input", "test-input-2"} + job_names = [JOB_NAME, "job-name-2"] + + queue = TrainingQueue(JOB_QUEUE) + queue.map( + Estimator(), + input_list, + job_names, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + assert patched_submit_service_job.call_count == len(input_list) + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_list_default_argument(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + patched_list_service_job.return_value = [{"jobSummaryList": [], "nextToken": None}] + queue.list_jobs() + patched_list_service_job.assert_has_calls([call(JOB_QUEUE, JOB_STATUS_RUNNING, None, None)]) + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_list_happy_case_with_job_name(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = [{"name": "JOB_NAME", "values": [JOB_NAME]}] + + patched_list_service_job.return_value = [{"jobSummaryList": [], "nextToken": None}] + + queue.list_jobs(JOB_NAME, None) + patched_list_service_job.assert_has_calls([call(JOB_QUEUE, None, filters, None)]) + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_list_happy_case_with_job_status(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = None + + patched_list_service_job.return_value = [EMPTY_LIST_SERVICE_JOB_RESP] + + queue.list_jobs(None, JOB_STATUS_RUNNING) + patched_list_service_job.assert_has_calls([call(JOB_QUEUE, JOB_STATUS_RUNNING, filters, None)]) + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_list_happy_case_has_next_token(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = [{"name": "JOB_NAME", "values": [JOB_NAME]}] + + first_output = FIRST_LIST_SERVICE_JOB_RESP + second_output = SECOND_LIST_SERVICE_JOB_RESP + third_output = EMPTY_LIST_SERVICE_JOB_RESP + patched_list_service_job.return_value = iter([first_output, second_output, third_output]) + + jobs = queue.list_jobs(JOB_NAME, JOB_STATUS_RUNNING) + patched_list_service_job.assert_has_calls( + [call(JOB_QUEUE, None, filters, None)], + any_order=False, + ) + assert len(jobs) == 3 + assert jobs[0].job_arn == JOB_ARN + assert jobs[0].job_name == JOB_NAME + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_list_without_job_arn_in_list_resp(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = [{"name": "JOB_NAME", "values": [JOB_NAME]}] + + first_output = INCORRECT_FIRST_LIST_SERVICE_JOB_RESP + second_output = EMPTY_LIST_SERVICE_JOB_RESP + patched_list_service_job.return_value = iter([first_output, second_output]) + + jobs = queue.list_jobs(JOB_NAME, JOB_STATUS_RUNNING) + patched_list_service_job.assert_has_calls( + [call(JOB_QUEUE, None, filters, None)], + any_order=False, + ) + assert len(jobs) == 0 + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_get_happy_case_job_exists(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = [{"name": "JOB_NAME", "values": [JOB_NAME]}] + + patched_list_service_job.return_value = [FIRST_LIST_SERVICE_JOB_RESP] + + job = queue.get_job(JOB_NAME) + patched_list_service_job.assert_has_calls( + [call(JOB_QUEUE, None, filters, None)], + any_order=False, + ) + assert job.job_name == JOB_NAME + + +@patch("sagemaker.aws_batch.training_queue.list_service_job") +def test_queue_get_job_not_found_encounter_error(patched_list_service_job): + queue = TrainingQueue(JOB_QUEUE) + filters = [{"name": "JOB_NAME", "values": [JOB_NAME]}] + + patched_list_service_job.return_value = [EMPTY_LIST_SERVICE_JOB_RESP] + + with pytest.raises(ValueError): + queue.get_job(JOB_NAME) + patched_list_service_job.assert_has_calls([call(JOB_QUEUE, None, filters, None)]) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_submit_model_trainer(patch_submit_service_job): + trainer = Mock(spec=ModelTrainer) + trainer.training_mode = Mode.SAGEMAKER_TRAINING_JOB + payload = { + "TrainingJobName": JOB_NAME, + "ResourceConfig": { + "InstanceType": "ml.m5.xlarge", + "InstanceCount": 1, + "VolumeSizeInGB": 30, + }, + } + trainer._create_training_job_args.return_value = payload + + patch_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + + queue = TrainingQueue(JOB_QUEUE) + queue_job = queue.submit( + trainer, + [], + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + patch_submit_service_job.assert_called_once_with( + payload, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + TIMEOUT_CONFIG, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + assert queue_job.job_name == JOB_NAME + assert queue_job.job_arn == JOB_ARN + + +def test_submit_model_trainer_fail(): + trainer = Mock(spec=ModelTrainer) + trainer.training_mode = Mode.LOCAL_CONTAINER + + with pytest.raises( + ValueError, + match="TrainingQueue requires using a ModelTrainer with Mode.SAGEMAKER_TRAINING_JOB", + ): + queue = TrainingQueue(JOB_QUEUE) + queue.submit( + trainer, + [], + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + + +@patch("sagemaker.aws_batch.training_queue.submit_service_job") +def test_submit_pytorch_estimator(patched_submit_service_job): + training_job_cls = _TrainingJob + training_job_cls.get_train_args = Mock(return_value=TRAINING_JOB_PAYLOAD_IN_PASCALCASE) + + patched_submit_service_job.return_value = SUBMIT_SERVICE_JOB_RESP + + queue = TrainingQueue(JOB_QUEUE) + queue_job = queue.submit( + PyTorch(), + {}, + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + DEFAULT_TIMEOUT, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) + patched_submit_service_job.assert_called_once_with( + TRAINING_JOB_PAYLOAD_IN_PASCALCASE, + JOB_NAME, + JOB_QUEUE, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + DEFAULT_TIMEOUT, + SHARE_IDENTIFIER, + BATCH_TAGS, + ) + assert queue_job.job_name == JOB_NAME + assert queue_job.job_arn == JOB_ARN + + +def test_submit_with_invalid_training_job(): + with pytest.raises( + TypeError, + match="training_job must be an instance of EstimatorBase or ModelTrainer", + ): + queue = TrainingQueue(JOB_QUEUE) + queue.submit( + TrainingQueue("NotAnEstimatorOrModelTrainer"), + [], + JOB_NAME, + DEFAULT_SAGEMAKER_TRAINING_RETRY_CONFIG, + SCHEDULING_PRIORITY, + SHARE_IDENTIFIER, + TIMEOUT_CONFIG, + BATCH_TAGS, + EXPERIMENT_CONFIG_EMPTY, + ) diff --git a/tests/unit/sagemaker/aws_batch/test_training_queued_job.py b/tests/unit/sagemaker/aws_batch/test_training_queued_job.py new file mode 100644 index 0000000000..fe5231a01d --- /dev/null +++ b/tests/unit/sagemaker/aws_batch/test_training_queued_job.py @@ -0,0 +1,170 @@ +from __future__ import absolute_import + +import pytest +import time +from mock.mock import patch +from unittest.mock import Mock + +from sagemaker.aws_batch.exception import NoTrainingJob, MissingRequiredArgument +from sagemaker.aws_batch.training_queued_job import TrainingQueuedJob +from sagemaker.config import SAGEMAKER, TRAINING_JOB +from .constants import ( + JOB_ARN, + JOB_NAME, + REASON, + TRAINING_IMAGE, + JOB_STATUS_RUNNING, + JOB_STATUS_RUNNABLE, + JOB_STATUS_FAILED, + JOB_STATUS_COMPLETED, + EXECUTION_ROLE, + TRAINING_JOB_ARN, +) +from tests.unit import SAGEMAKER_CONFIG_TRAINING_JOB + + +@patch("sagemaker.aws_batch.training_queued_job.terminate_service_job") +def test_queued_job_terminate(patched_terminate_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + queued_job.terminate(REASON) + patched_terminate_service_job.assert_called_once_with(queued_job.job_arn, REASON) + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_describe(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + queued_job.describe() + patched_describe_service_job.assert_called_once_with(queued_job.job_arn) + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_estimator_no_training_job_created(patched_describe_service_job): + patched_describe_service_job.return_value = {"status": JOB_STATUS_RUNNABLE} + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + with pytest.raises(NoTrainingJob): + queued_job.get_estimator() + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_estimator_missing_required_argument(patched_describe_service_job): + patched_describe_service_job.return_value = {"status": JOB_STATUS_RUNNING} + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + with pytest.raises(MissingRequiredArgument): + queued_job.get_estimator() + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +@patch("sagemaker.aws_batch.training_queued_job._construct_estimator_from_training_job_name") +def test_queued_job_estimator_happy_case( + patched_construct_estimator_from_training_job_name, patched_describe_service_job +): + training_job_config = SAGEMAKER_CONFIG_TRAINING_JOB[SAGEMAKER][TRAINING_JOB] + training_job_config["image_uri"] = TRAINING_IMAGE + training_job_config["job_name"] = JOB_NAME + training_job_config["role"] = EXECUTION_ROLE + describe_resp = { + "status": JOB_STATUS_RUNNING, + "latestAttempt": { + "serviceResourceId": {"name": "trainingJobArn", "value": TRAINING_JOB_ARN} + }, + } + patched_describe_service_job.return_value = describe_resp + + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + queued_job.get_estimator() + patched_construct_estimator_from_training_job_name.assert_called_once_with(JOB_NAME) + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_wait_no_timeout(patched_describe_service_job): + patched_describe_service_job.return_value = {"status": JOB_STATUS_COMPLETED} + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + result = queued_job.wait() + assert result.get("status", "") == JOB_STATUS_COMPLETED + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_wait_with_timeout_succeeds(patched_describe_service_job): + patched_describe_service_job.side_effect = [ + {"status": JOB_STATUS_RUNNING}, + {"status": JOB_STATUS_RUNNING}, + {"status": JOB_STATUS_COMPLETED}, + ] + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + start_time = time.time() + result = queued_job.wait(timeout=15) + end_time = time.time() + + assert end_time - start_time < 15 + assert result.get("status", "") == JOB_STATUS_COMPLETED + assert patched_describe_service_job.call_count == 3 + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queued_job_wait_with_timeout_times_out(patched_describe_service_job): + patched_describe_service_job.return_value = {"status": JOB_STATUS_RUNNING} + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + start_time = time.time() + result = queued_job.wait(timeout=5) + end_time = time.time() + + assert end_time - start_time > 5 + assert result.get("status", "") == JOB_STATUS_RUNNING + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +@pytest.mark.asyncio +async def test_queued_job_async_fetch_job_results_happy_case(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + + queued_job.wait = Mock() + # queued_job.describe.return_value = {"status": JOB_STATUS_COMPLETED} + patched_describe_service_job.return_value = {"status": JOB_STATUS_COMPLETED} + + result = await queued_job.fetch_job_results() + assert result == {"status": JOB_STATUS_COMPLETED} + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +@pytest.mark.asyncio +async def test_queued_job_async_fetch_job_results_job_failed(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + + queued_job.wait = Mock() + patched_describe_service_job.return_value = { + "status": JOB_STATUS_FAILED, + "statusReason": "Job failed", + } + + with pytest.raises(RuntimeError): + await queued_job.fetch_job_results() + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +@pytest.mark.asyncio +async def test_queued_job_async_fetch_job_results_timeout(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + + queued_job.wait = Mock() + patched_describe_service_job.return_value = {"status": JOB_STATUS_RUNNING} + + with pytest.raises(TimeoutError): + await queued_job.fetch_job_results(timeout=1) + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queue_result_happy_case(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + patched_describe_service_job.return_value = {"status": JOB_STATUS_COMPLETED} + + result = queued_job.result(100) + assert result == {"status": JOB_STATUS_COMPLETED} + + +@patch("sagemaker.aws_batch.training_queued_job.describe_service_job") +def test_queue_result_job_times_out(patched_describe_service_job): + queued_job = TrainingQueuedJob(JOB_ARN, JOB_NAME) + patched_describe_service_job.return_value = {"status": JOB_STATUS_RUNNING} + + with pytest.raises(TimeoutError): + queued_job.result(1) diff --git a/tests/unit/sagemaker/modules/train/test_model_trainer.py b/tests/unit/sagemaker/modules/train/test_model_trainer.py index 184f9c30da..73893ea7f4 100644 --- a/tests/unit/sagemaker/modules/train/test_model_trainer.py +++ b/tests/unit/sagemaker/modules/train/test_model_trainer.py @@ -1302,6 +1302,53 @@ def mock_upload_data(path, bucket, key_prefix): assert kwargs["tensor_board_output_config"].local_path == "/opt/ml/output/tensorboard" +def test_create_training_job_args(modules_session): + model_trainer = ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + ) + + args = model_trainer._create_training_job_args() + assert args["algorithm_specification"] == AlgorithmSpecification( + training_image=DEFAULT_IMAGE, + algorithm_name=None, + training_input_mode="File", + container_entrypoint=None, + container_arguments=None, + training_image_config=None, + metric_definitions=None, + ) + assert args["resource_config"] == ResourceConfig( + instance_type=DEFAULT_INSTANCE_TYPE, + instance_count=1, + volume_size_in_gb=30, + ) + assert args["role_arn"] == DEFAULT_ROLE + + +def test_create_training_job_args_boto3(modules_session): + model_trainer = ModelTrainer( + training_image=DEFAULT_IMAGE, + role=DEFAULT_ROLE, + sagemaker_session=modules_session, + compute=DEFAULT_COMPUTE_CONFIG, + ) + + args = model_trainer._create_training_job_args(boto3=True) + assert args["AlgorithmSpecification"] == { + "TrainingImage": DEFAULT_IMAGE, + "TrainingInputMode": "File", + } + assert args["ResourceConfig"] == { + "InstanceType": DEFAULT_INSTANCE_TYPE, + "InstanceCount": 1, + "VolumeSizeInGB": 30, + } + assert args["RoleArn"] == DEFAULT_ROLE + + @patch("sagemaker.modules.train.model_trainer.TrainingJob") def test_input_merge(mock_training_job, modules_session): model_input = InputData(channel_name="model", data_source="s3://bucket/model/model.tar.gz") diff --git a/tox.ini b/tox.ini index e4df36587a..9c624b2052 100644 --- a/tox.ini +++ b/tox.ini @@ -68,6 +68,8 @@ markers = setenv = PYTHONHASHSEED=42 pip_version = pip==24.3 +allowlist_externals = + aws passenv = AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY @@ -82,6 +84,7 @@ passenv = # Can be used to specify which tests to run, e.g.: tox -- -s commands = python -c "import os; os.system('install-custom-pkgs --install-boto-wheels')" + pip install 'apache-airflow==2.10.4' --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.10.4/constraints-3.9.txt" pip install 'torch==2.3.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' pip install 'torchvision==0.18.1+cpu' -f 'https://download.pytorch.org/whl/torch_stable.html' @@ -90,7 +93,11 @@ commands = pip install -U "sagemaker-core" # needed to keep sagemaker-core up to date pytest {posargs} -deps = .[test] +deps = + .[test] + asyncio + nest_asyncio + pytest-asyncio depends = {py39,py310,py311,py312}: clean From 89f17e93978a4f5c7282f671f13d0800e5a7ce72 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 31 Jul 2025 01:07:22 +0000 Subject: [PATCH 153/164] prepare release v2.249.0 --- CHANGELOG.md | 11 +++++++++++ VERSION | 2 +- 2 files changed, 12 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 922dbe09eb..5d88b7716e 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,16 @@ # Changelog +## v2.249.0 (2025-07-31) + +### Features + + * AWS Batch for SageMaker Training jobs + +### Bug Fixes and Other Changes + + * Directly use customer-provided endpoint name for ModelBuilder deployment. + * update image_uri_configs 07-23-2025 07:18:25 PST + ## v2.248.2 (2025-07-22) ### Bug Fixes and Other Changes diff --git a/VERSION b/VERSION index fcc1c85c53..6208291c30 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.248.3.dev0 +2.249.0 From 40c791c4290f0ee2aa42fe4fdedc9903e0a5e8e1 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 31 Jul 2025 01:07:26 +0000 Subject: [PATCH 154/164] update development version to v2.249.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 6208291c30..c6259ee0a8 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.249.0 +2.249.1.dev0 From 754c3a52ccfdf43d5d3772392d287a2fd75b2e88 Mon Sep 17 00:00:00 2001 From: pintaoz-aws <167920275+pintaoz-aws@users.noreply.github.com> Date: Thu, 7 Aug 2025 11:46:44 -0700 Subject: [PATCH 155/164] Add more constraints to test requirements (#5254) * Add constraint file to test requirements * Add constraints --------- Co-authored-by: pintaoz --- requirements/extras/test_requirements.txt | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/requirements/extras/test_requirements.txt b/requirements/extras/test_requirements.txt index 81bff89ddf..d66235d84a 100644 --- a/requirements/extras/test_requirements.txt +++ b/requirements/extras/test_requirements.txt @@ -32,6 +32,7 @@ PyYAML>=6.0.1 xgboost>=1.6.2,<=1.7.6 pillow>=10.0.1,<=11 opentelemetry-proto==1.27.0 +opentelemetry_exporter_otlp==1.27.0 protobuf==4.25.8 tensorboard>=2.16.2,<=2.18.0 transformers==4.48.0 @@ -53,3 +54,10 @@ sagemaker-mlflow>=0.1.0 deepdiff>=8.0.0 orderly-set<5.4.0 lexicon +networkx==3.2.1 +mypy-boto3-appflow==1.35.39 +mypy-boto3-rds==1.35.72 +mypy-boto3-redshift-data==1.35.51 +mypy-boto3-s3==1.35.76 +mypy-extensions==1.0.0 +mypy==1.9.0 From f65a28e926cfceb76ada6bb36b910bebe9602c66 Mon Sep 17 00:00:00 2001 From: Greg Katkov Date: Fri, 8 Aug 2025 14:00:09 -0700 Subject: [PATCH 156/164] feature: Add support for InstancePlacementConfig in Estimator for training jobs running on ultraserver capacity (#5259) --------- Co-authored-by: Greg Katkov --- src/sagemaker/estimator.py | 39 ++++++++++++++++++++ src/sagemaker/job.py | 4 ++ src/sagemaker/jumpstart/estimator.py | 16 ++++++++ src/sagemaker/jumpstart/factory/estimator.py | 2 + src/sagemaker/jumpstart/types.py | 3 ++ tests/unit/test_estimator.py | 18 +++++++++ tests/unit/test_job.py | 26 +++++++++++++ 7 files changed, 108 insertions(+) diff --git a/src/sagemaker/estimator.py b/src/sagemaker/estimator.py index 0055416327..8cd6410ea0 100644 --- a/src/sagemaker/estimator.py +++ b/src/sagemaker/estimator.py @@ -186,6 +186,7 @@ def __init__( enable_remote_debug: Optional[Union[bool, PipelineVariable]] = None, enable_session_tag_chaining: Optional[Union[bool, PipelineVariable]] = None, training_plan: Optional[Union[str, PipelineVariable]] = None, + instance_placement_config: Optional[Dict] = None, **kwargs, ): """Initialize an ``EstimatorBase`` instance. @@ -560,6 +561,21 @@ def __init__( Specifies whether SessionTagChaining is enabled for the training job. training_plan (str or PipelineVariable): Optional. Specifies which training plan arn to use for the training job + instance_placement_config (dict): Optional. + Specifies UltraServer placement configuration for the training job + + .. code:: python + + instance_placement_config={ + "EnableMultipleJobs": True, + "PlacementSpecifications":[ + { + "UltraServerId": "ultraserver-1", + "InstanceCount": "2" + } + ] + } + """ instance_count = renamed_kwargs( "train_instance_count", "instance_count", instance_count, kwargs @@ -813,6 +829,8 @@ def __init__( self.training_plan = training_plan + self.instance_placement_config = instance_placement_config + # Internal flag self._is_output_path_set_from_default_bucket_and_prefix = False @@ -1997,6 +2015,11 @@ def _prepare_init_params_from_job_description(cls, job_details, model_channel_na if "TrainingPlanArn" in job_details["ResourceConfig"]: init_params["training_plan"] = job_details["ResourceConfig"]["TrainingPlanArn"] + if "InstancePlacementConfig" in job_details["ResourceConfig"]: + init_params["instance_placement_config"] = job_details["ResourceConfig"][ + "InstancePlacementConfig" + ] + has_hps = "HyperParameters" in job_details init_params["hyperparameters"] = job_details["HyperParameters"] if has_hps else {} @@ -2882,6 +2905,7 @@ def __init__( enable_remote_debug: Optional[Union[bool, PipelineVariable]] = None, enable_session_tag_chaining: Optional[Union[bool, PipelineVariable]] = None, training_plan: Optional[Union[str, PipelineVariable]] = None, + instance_placement_config: Optional[Dict] = None, **kwargs, ): """Initialize an ``Estimator`` instance. @@ -3249,6 +3273,20 @@ def __init__( Specifies whether SessionTagChaining is enabled for the training job training_plan (str or PipelineVariable): Optional. Specifies which training plan arn to use for the training job + instance_placement_config (dict): Optional. + Specifies UltraServer placement configuration for the training job + + .. code:: python + + instance_placement_config={ + "EnableMultipleJobs": True, + "PlacementSpecifications":[ + { + "UltraServerId": "ultraserver-1", + "InstanceCount": "2" + } + ] + } """ self.image_uri = image_uri self._hyperparameters = hyperparameters.copy() if hyperparameters else {} @@ -3303,6 +3341,7 @@ def __init__( enable_remote_debug=enable_remote_debug, enable_session_tag_chaining=enable_session_tag_chaining, training_plan=training_plan, + instance_placement_config=instance_placement_config, **kwargs, ) diff --git a/src/sagemaker/job.py b/src/sagemaker/job.py index 1ad7e3b981..6917421c04 100644 --- a/src/sagemaker/job.py +++ b/src/sagemaker/job.py @@ -85,6 +85,7 @@ def _load_config(inputs, estimator, expand_role=True, validate_uri=True): estimator.volume_kms_key, estimator.keep_alive_period_in_seconds, estimator.training_plan, + estimator.instance_placement_config, ) stop_condition = _Job._prepare_stop_condition(estimator.max_run, estimator.max_wait) vpc_config = estimator.get_vpc_config() @@ -333,6 +334,7 @@ def _prepare_resource_config( volume_kms_key, keep_alive_period_in_seconds, training_plan, + instance_placement_config=None, ): """Placeholder docstring""" resource_config = { @@ -360,6 +362,8 @@ def _prepare_resource_config( resource_config["InstanceType"] = instance_type if training_plan is not None: resource_config["TrainingPlanArn"] = training_plan + if instance_placement_config is not None: + resource_config["InstancePlacementConfig"] = instance_placement_config return resource_config diff --git a/src/sagemaker/jumpstart/estimator.py b/src/sagemaker/jumpstart/estimator.py index 4daf9b1810..e61e1c49a5 100644 --- a/src/sagemaker/jumpstart/estimator.py +++ b/src/sagemaker/jumpstart/estimator.py @@ -119,6 +119,7 @@ def __init__( config_name: Optional[str] = None, enable_session_tag_chaining: Optional[Union[bool, PipelineVariable]] = None, training_plan: Optional[Union[str, PipelineVariable]] = None, + instance_placement_config: Optional[Dict] = None, ): """Initializes a ``JumpStartEstimator``. @@ -517,6 +518,20 @@ def __init__( Specifies whether SessionTagChaining is enabled for the training job training_plan (str or PipelineVariable): Optional. Specifies which training plan arn to use for the training job + instance_placement_config (dict): Optional. + Specifies UltraServer placement configuration for the training job + + .. code:: python + + instance_placement_config={ + "EnableMultipleJobs": True, + "PlacementSpecifications":[ + { + "UltraServerId": "ultraserver-1", + "InstanceCount": "2" + } + ] + } Raises: ValueError: If the model ID is not recognized by JumpStart. @@ -606,6 +621,7 @@ def _validate_model_id_and_get_type_hook(): config_name=config_name, enable_session_tag_chaining=enable_session_tag_chaining, training_plan=training_plan, + instance_placement_config=instance_placement_config, ) self.hub_arn = estimator_init_kwargs.hub_arn diff --git a/src/sagemaker/jumpstart/factory/estimator.py b/src/sagemaker/jumpstart/factory/estimator.py index 051cda0f4a..81e1356050 100644 --- a/src/sagemaker/jumpstart/factory/estimator.py +++ b/src/sagemaker/jumpstart/factory/estimator.py @@ -145,6 +145,7 @@ def get_init_kwargs( config_name: Optional[str] = None, enable_session_tag_chaining: Optional[Union[bool, PipelineVariable]] = None, training_plan: Optional[Union[str, PipelineVariable]] = None, + instance_placement_config: Optional[Dict] = None, ) -> JumpStartEstimatorInitKwargs: """Returns kwargs required to instantiate `sagemaker.estimator.Estimator` object.""" @@ -207,6 +208,7 @@ def get_init_kwargs( config_name=config_name, enable_session_tag_chaining=enable_session_tag_chaining, training_plan=training_plan, + instance_placement_config=instance_placement_config, ) estimator_init_kwargs, orig_session = _set_temp_sagemaker_session_if_not_set( diff --git a/src/sagemaker/jumpstart/types.py b/src/sagemaker/jumpstart/types.py index 5b45b21bd8..f545425a51 100644 --- a/src/sagemaker/jumpstart/types.py +++ b/src/sagemaker/jumpstart/types.py @@ -2445,6 +2445,7 @@ class JumpStartEstimatorInitKwargs(JumpStartKwargs): "model_reference_arn", "specs", "training_plan", + "instance_placement_config", ] SERIALIZATION_EXCLUSION_SET = { @@ -2519,6 +2520,7 @@ def __init__( config_name: Optional[str] = None, enable_session_tag_chaining: Optional[Union[bool, PipelineVariable]] = None, training_plan: Optional[Union[str, PipelineVariable]] = None, + instance_placement_config: Optional[Dict] = None, ) -> None: """Instantiates JumpStartEstimatorInitKwargs object.""" @@ -2582,6 +2584,7 @@ def __init__( self.config_name = config_name self.enable_session_tag_chaining = enable_session_tag_chaining self.training_plan = training_plan + self.instance_placement_config = instance_placement_config class JumpStartEstimatorFitKwargs(JumpStartKwargs): diff --git a/tests/unit/test_estimator.py b/tests/unit/test_estimator.py index cfb243b563..1698da3e90 100644 --- a/tests/unit/test_estimator.py +++ b/tests/unit/test_estimator.py @@ -76,6 +76,8 @@ ) from sagemaker.model_life_cycle import ModelLifeCycle +from tests.unit.test_job import INSTANCE_PLACEMENT_CONFIG + MODEL_DATA = "s3://bucket/model.tar.gz" MODEL_IMAGE = "mi" ENTRY_POINT = "blah.py" @@ -879,6 +881,22 @@ def test_framework_with_training_plan(sagemaker_session): assert args["resource_config"]["TrainingPlanArn"] == TRAINING_PLAN +def test_framework_with_instance_placement(sagemaker_session): + f = DummyFramework( + entry_point=SCRIPT_PATH, + role=ROLE, + sagemaker_session=sagemaker_session, + instance_type="ml.c4.xlarge", + instance_count=2, + training_plan=TRAINING_PLAN, + instance_placement_config=INSTANCE_PLACEMENT_CONFIG, + ) + f.fit("s3://mydata") + sagemaker_session.train.assert_called_once() + _, args = sagemaker_session.train.call_args + assert args["resource_config"]["InstancePlacementConfig"] == INSTANCE_PLACEMENT_CONFIG + + def test_framework_with_both_training_repository_config(sagemaker_session): f = DummyFramework( entry_point=SCRIPT_PATH, diff --git a/tests/unit/test_job.py b/tests/unit/test_job.py index dc21f50b68..cdd4a2630e 100644 --- a/tests/unit/test_job.py +++ b/tests/unit/test_job.py @@ -32,6 +32,10 @@ INSTANCE_TYPE = "c4.4xlarge" KEEP_ALIVE_PERIOD = 1800 TRAINING_PLAN = "arn:aws:sagemaker:us-west-2:336:training-plan/test_training_plan" +INSTANCE_PLACEMENT_CONFIG = { + "EnableMultipleJobs": True, + "PlacementSpecifications": [{"UltraServerId": "us-1", "InstanceCount": "2"}], +} INSTANCE_GROUP = InstanceGroup("group", "ml.c4.xlarge", 1) VOLUME_SIZE = 1 MAX_RUNTIME = 1 @@ -756,6 +760,28 @@ def test_prepare_resource_config_with_training_plan(): } +def test_prepare_resource_config_with_placement_config(): + resource_config = _Job._prepare_resource_config( + INSTANCE_COUNT, + INSTANCE_TYPE, + None, + VOLUME_SIZE, + VOLUME_KMS_KEY, + None, + TRAINING_PLAN, + INSTANCE_PLACEMENT_CONFIG, + ) + + assert resource_config == { + "InstanceCount": INSTANCE_COUNT, + "InstanceType": INSTANCE_TYPE, + "VolumeSizeInGB": VOLUME_SIZE, + "VolumeKmsKeyId": VOLUME_KMS_KEY, + "TrainingPlanArn": TRAINING_PLAN, + "InstancePlacementConfig": INSTANCE_PLACEMENT_CONFIG, + } + + def test_prepare_resource_config_with_keep_alive_period(): resource_config = _Job._prepare_resource_config( INSTANCE_COUNT, From edb54e1f8fb38ecc1f2a73f3b4e1c891631458e5 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 8 Aug 2025 23:04:55 +0000 Subject: [PATCH 157/164] prepare release v2.250.0 --- CHANGELOG.md | 10 ++++++++++ VERSION | 2 +- 2 files changed, 11 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 5d88b7716e..26578e980a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,15 @@ # Changelog +## v2.250.0 (2025-08-08) + +### Features + + * Add support for InstancePlacementConfig in Estimator for training jobs running on ultraserver capacity + +### Bug Fixes and Other Changes + + * Add more constraints to test requirements + ## v2.249.0 (2025-07-31) ### Features diff --git a/VERSION b/VERSION index c6259ee0a8..342abcb512 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.249.1.dev0 +2.250.0 From 3521b872720a4c18dd633115b3cf295606bad885 Mon Sep 17 00:00:00 2001 From: ci Date: Fri, 8 Aug 2025 23:04:59 +0000 Subject: [PATCH 158/164] update development version to v2.250.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index 342abcb512..51f3762b3d 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.250.0 +2.250.1.dev0 From 9bfe85abe338375ea870b8bda6635d04e8d7fc4b Mon Sep 17 00:00:00 2001 From: Namrata Madan Date: Mon, 11 Aug 2025 16:05:40 -0700 Subject: [PATCH 159/164] feat: support pipeline versioning (#5248) Co-authored-by: Namrata Madan Co-authored-by: Gokul Anantha Narayanan <166456257+nargokul@users.noreply.github.com> --- pyproject.toml | 2 +- src/sagemaker/workflow/pipeline.py | 57 +++++++++++++++++-- .../integ/sagemaker/workflow/test_workflow.py | 55 +++++++++++++++++- .../unit/sagemaker/workflow/test_pipeline.py | 49 +++++++++++++--- 4 files changed, 147 insertions(+), 16 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index aa3391d9bd..e35a43c163 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -32,7 +32,7 @@ classifiers = [ ] dependencies = [ "attrs>=24,<26", - "boto3>=1.35.36,<2.0", + "boto3>=1.39.5,<2.0", "cloudpickle>=2.2.1", "docker", "fastapi", diff --git a/src/sagemaker/workflow/pipeline.py b/src/sagemaker/workflow/pipeline.py index 9749014531..f1a62fa637 100644 --- a/src/sagemaker/workflow/pipeline.py +++ b/src/sagemaker/workflow/pipeline.py @@ -125,6 +125,15 @@ def __init__( self.sagemaker_session.boto_session.client("scheduler"), ) + @property + def latest_pipeline_version_id(self): + """Retrieves the latest version id of this pipeline""" + summaries = self.list_pipeline_versions(max_results=1)["PipelineVersionSummaries"] + if not summaries: + return None + else: + return summaries[0].get("PipelineVersionId") + def create( self, role_arn: str = None, @@ -166,7 +175,8 @@ def create( kwargs, Tags=tags, ) - return self.sagemaker_session.sagemaker_client.create_pipeline(**kwargs) + response = self.sagemaker_session.sagemaker_client.create_pipeline(**kwargs) + return response def _create_args( self, role_arn: str, description: str, parallelism_config: ParallelismConfiguration @@ -214,15 +224,21 @@ def _create_args( ) return kwargs - def describe(self) -> Dict[str, Any]: + def describe(self, pipeline_version_id: int = None) -> Dict[str, Any]: """Describes a Pipeline in the Workflow service. + Args: + pipeline_version_id (Optional[str]): version ID of the pipeline to describe. + Returns: Response dict from the service. See `boto3 client documentation `_ """ - return self.sagemaker_session.sagemaker_client.describe_pipeline(PipelineName=self.name) + kwargs = dict(PipelineName=self.name) + if pipeline_version_id: + kwargs["PipelineVersionId"] = pipeline_version_id + return self.sagemaker_session.sagemaker_client.describe_pipeline(**kwargs) def update( self, @@ -257,7 +273,8 @@ def update( return self.sagemaker_session.sagemaker_client.update_pipeline(self, description) kwargs = self._create_args(role_arn, description, parallelism_config) - return self.sagemaker_session.sagemaker_client.update_pipeline(**kwargs) + response = self.sagemaker_session.sagemaker_client.update_pipeline(**kwargs) + return response def upsert( self, @@ -332,6 +349,7 @@ def start( execution_description: str = None, parallelism_config: ParallelismConfiguration = None, selective_execution_config: SelectiveExecutionConfig = None, + pipeline_version_id: int = None, ): """Starts a Pipeline execution in the Workflow service. @@ -345,6 +363,8 @@ def start( over the parallelism configuration of the parent pipeline. selective_execution_config (Optional[SelectiveExecutionConfig]): The configuration for selective step execution. + pipeline_version_id (Optional[str]): version ID of the pipeline to start the execution from. If not + specified, uses the latest version ID. Returns: A `_PipelineExecution` instance, if successful. @@ -366,6 +386,7 @@ def start( PipelineExecutionDisplayName=execution_display_name, ParallelismConfiguration=parallelism_config, SelectiveExecutionConfig=selective_execution_config, + PipelineVersionId=pipeline_version_id, ) if self.sagemaker_session.local_mode: update_args(kwargs, PipelineParameters=parameters) @@ -461,6 +482,32 @@ def list_executions( if key in response } + def list_pipeline_versions( + self, sort_order: str = None, max_results: int = None, next_token: str = None + ) -> str: + """Lists a pipeline's versions. + + Args: + sort_order (str): The sort order for results (Ascending/Descending). + max_results (int): The maximum number of pipeline executions to return in the response. + next_token (str): If the result of the previous `ListPipelineExecutions` request was + truncated, the response includes a `NextToken`. To retrieve the next set of pipeline + executions, use the token in the next request. + + Returns: + List of Pipeline Version Summaries. See + boto3 client list_pipeline_versions + https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker/client/list_pipeline_versions.html# + """ + kwargs = dict(PipelineName=self.name) + update_args( + kwargs, + SortOrder=sort_order, + NextToken=next_token, + MaxResults=max_results, + ) + return self.sagemaker_session.sagemaker_client.list_pipeline_versions(**kwargs) + def _get_latest_execution_arn(self): """Retrieves the latest execution of this pipeline""" response = self.list_executions( @@ -855,7 +902,7 @@ def describe(self): sagemaker.html#SageMaker.Client.describe_pipeline_execution>`_. """ return self.sagemaker_session.sagemaker_client.describe_pipeline_execution( - PipelineExecutionArn=self.arn, + PipelineExecutionArn=self.arn ) def list_steps(self): diff --git a/tests/integ/sagemaker/workflow/test_workflow.py b/tests/integ/sagemaker/workflow/test_workflow.py index 9ef0b14a04..a879ff88e5 100644 --- a/tests/integ/sagemaker/workflow/test_workflow.py +++ b/tests/integ/sagemaker/workflow/test_workflow.py @@ -312,6 +312,7 @@ def test_three_step_definition( rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}", create_arn, ) + assert pipeline.latest_pipeline_version_id == 1 finally: try: pipeline.delete() @@ -937,7 +938,6 @@ def test_large_pipeline(sagemaker_session_for_pipeline, role, pipeline_name, reg rf"arn:aws:sagemaker:{region_name}:\d{{12}}:pipeline/{pipeline_name}", create_arn, ) - response = pipeline.describe() assert len(json.loads(pipeline.describe()["PipelineDefinition"])["Steps"]) == 2000 pipeline.parameters = [ParameterInteger(name="InstanceCount", default_value=1)] @@ -1387,3 +1387,56 @@ def test_caching_behavior( except Exception: os.remove(script_dir + "/dummy_script.py") pass + + +def test_pipeline_versioning(pipeline_session, role, pipeline_name, script_dir): + sklearn_train = SKLearn( + framework_version="0.20.0", + entry_point=os.path.join(script_dir, "train.py"), + instance_type="ml.m5.xlarge", + sagemaker_session=pipeline_session, + role=role, + ) + + step1 = TrainingStep( + name="my-train-1", + display_name="TrainingStep", + description="description for Training step", + step_args=sklearn_train.fit(), + ) + + step2 = TrainingStep( + name="my-train-2", + display_name="TrainingStep", + description="description for Training step", + step_args=sklearn_train.fit(), + ) + pipeline = Pipeline( + name=pipeline_name, + steps=[step1], + sagemaker_session=pipeline_session, + ) + + try: + pipeline.create(role) + + assert pipeline.latest_pipeline_version_id == 1 + + describe_response = pipeline.describe(pipeline_version_id=1) + assert len(json.loads(describe_response["PipelineDefinition"])["Steps"]) == 1 + + pipeline.steps.append(step2) + pipeline.upsert(role) + + assert pipeline.latest_pipeline_version_id == 2 + + describe_response = pipeline.describe(pipeline_version_id=2) + assert len(json.loads(describe_response["PipelineDefinition"])["Steps"]) == 2 + + assert len(pipeline.list_pipeline_versions()["PipelineVersionSummaries"]) == 2 + + finally: + try: + pipeline.delete() + except Exception: + pass diff --git a/tests/unit/sagemaker/workflow/test_pipeline.py b/tests/unit/sagemaker/workflow/test_pipeline.py index 523b981736..d83bebd167 100644 --- a/tests/unit/sagemaker/workflow/test_pipeline.py +++ b/tests/unit/sagemaker/workflow/test_pipeline.py @@ -391,7 +391,6 @@ def _raise_does_already_exists_client_error(**kwargs): sagemaker_session_mock.sagemaker_client.create_pipeline = Mock( name="create_pipeline", side_effect=_raise_does_already_exists_client_error ) - sagemaker_session_mock.sagemaker_client.update_pipeline.return_value = { "PipelineArn": "pipeline-arn" } @@ -429,6 +428,12 @@ def _raise_does_already_exists_client_error(**kwargs): ResourceArn="pipeline-arn", Tags=tags ) + sagemaker_session_mock.sagemaker_client.list_pipeline_versions.return_value = { + "PipelineVersionSummaries": [{"PipelineVersionId": 2}] + } + + assert pipeline.latest_pipeline_version_id == 2 + def test_pipeline_upsert_create_unexpected_failure(sagemaker_session_mock, role_arn): @@ -476,18 +481,11 @@ def _raise_unexpected_client_error(**kwargs): sagemaker_session_mock.sagemaker_client.add_tags.assert_not_called() -def test_pipeline_upsert_resourse_doesnt_exist(sagemaker_session_mock, role_arn): +def test_pipeline_upsert_resource_doesnt_exist(sagemaker_session_mock, role_arn): # case 3: resource does not exist sagemaker_session_mock.sagemaker_client.create_pipeline = Mock(name="create_pipeline") - sagemaker_session_mock.sagemaker_client.update_pipeline.return_value = { - "PipelineArn": "pipeline-arn" - } - sagemaker_session_mock.sagemaker_client.list_tags.return_value = { - "Tags": [{"Key": "dummy", "Value": "dummy_tag"}] - } - tags = [ {"Key": "foo", "Value": "abc"}, {"Key": "bar", "Value": "xyz"}, @@ -542,6 +540,11 @@ def test_pipeline_describe(sagemaker_session_mock): PipelineName="MyPipeline", ) + pipeline.describe(pipeline_version_id=5) + sagemaker_session_mock.sagemaker_client.describe_pipeline.assert_called_with( + PipelineName="MyPipeline", PipelineVersionId=5 + ) + def test_pipeline_start(sagemaker_session_mock): sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = { @@ -568,6 +571,11 @@ def test_pipeline_start(sagemaker_session_mock): PipelineName="MyPipeline", PipelineParameters=[{"Name": "alpha", "Value": "epsilon"}] ) + pipeline.start(pipeline_version_id=5) + sagemaker_session_mock.sagemaker_client.start_pipeline_execution.assert_called_with( + PipelineName="MyPipeline", PipelineVersionId=5 + ) + def test_pipeline_start_selective_execution(sagemaker_session_mock): sagemaker_session_mock.sagemaker_client.start_pipeline_execution.return_value = { @@ -809,6 +817,29 @@ def test_pipeline_list_executions(sagemaker_session_mock): assert executions["NextToken"] == "token" +def test_pipeline_list_versions(sagemaker_session_mock): + sagemaker_session_mock.sagemaker_client.list_pipeline_versions.return_value = { + "PipelineVersionSummaries": [Mock()], + "NextToken": "token", + } + pipeline = Pipeline( + name="MyPipeline", + parameters=[ParameterString("alpha", "beta"), ParameterString("gamma", "delta")], + steps=[], + sagemaker_session=sagemaker_session_mock, + ) + versions = pipeline.list_pipeline_versions() + assert len(versions["PipelineVersionSummaries"]) == 1 + assert versions["NextToken"] == "token" + + sagemaker_session_mock.sagemaker_client.list_pipeline_versions.return_value = { + "PipelineVersionSummaries": [Mock(), Mock()], + } + versions = pipeline.list_pipeline_versions(next_token=versions["NextToken"]) + assert len(versions["PipelineVersionSummaries"]) == 2 + assert "NextToken" not in versions + + def test_pipeline_build_parameters_from_execution(sagemaker_session_mock): pipeline = Pipeline( name="MyPipeline", From 73bdd08d18de20b8483f95a27ce09c10217c3976 Mon Sep 17 00:00:00 2001 From: sage-maker Date: Tue, 12 Aug 2025 16:03:57 -0700 Subject: [PATCH 160/164] add sleep for model deployment (#5260) --- tests/integ/test_multidatamodel.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/tests/integ/test_multidatamodel.py b/tests/integ/test_multidatamodel.py index 59c79f5a9c..4c926a1c0e 100644 --- a/tests/integ/test_multidatamodel.py +++ b/tests/integ/test_multidatamodel.py @@ -14,6 +14,7 @@ import base64 import os +import time import requests import docker @@ -138,6 +139,7 @@ def test_multi_data_model_deploy_pretrained_models( multi_data_model.add_model(pretrained_model_data_local_path, PRETRAINED_MODEL_PATH_1) # Deploy model to an endpoint multi_data_model.deploy(1, cpu_instance_type, endpoint_name=endpoint_name) + time.sleep(30) # Add models after deploy multi_data_model.add_model(pretrained_model_data_local_path, PRETRAINED_MODEL_PATH_2) @@ -266,6 +268,7 @@ def test_multi_data_model_deploy_trained_model_from_framework_estimator( multi_data_model.add_model(mxnet_model_1.model_data, PRETRAINED_MODEL_PATH_1) # Deploy model to an endpoint multi_data_model.deploy(1, cpu_instance_type, endpoint_name=endpoint_name) + time.sleep(30) # Train another model mxnet_model_2 = _mxnet_training_job( @@ -373,6 +376,7 @@ def test_multi_data_model_deploy_train_model_from_amazon_first_party_estimator( multi_data_model.add_model(rcf_model_v1.model_data, PRETRAINED_MODEL_PATH_1) # Deploy model to an endpoint multi_data_model.deploy(1, cpu_instance_type, endpoint_name=endpoint_name) + time.sleep(30) # Train another model rcf_model_v2 = __rcf_training_job( sagemaker_session, container_image, cpu_instance_type, 70, 20 @@ -470,6 +474,7 @@ def test_multi_data_model_deploy_pretrained_models_update_endpoint( multi_data_model.add_model(pretrained_model_data_local_path, PRETRAINED_MODEL_PATH_1) # Deploy model to an endpoint multi_data_model.deploy(1, cpu_instance_type, endpoint_name=endpoint_name) + time.sleep(30) # Add model after deploy multi_data_model.add_model(pretrained_model_data_local_path, PRETRAINED_MODEL_PATH_2) From eb13102712d7b0fd5f631050e818101dffe75231 Mon Sep 17 00:00:00 2001 From: sage-maker Date: Mon, 18 Aug 2025 17:24:50 -0700 Subject: [PATCH 161/164] fix: dockerfile stuck on interactive shell (#5261) --- tests/integ/sagemaker/conftest.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/tests/integ/sagemaker/conftest.py b/tests/integ/sagemaker/conftest.py index fe7e7d61f8..421ef10b1d 100644 --- a/tests/integ/sagemaker/conftest.py +++ b/tests/integ/sagemaker/conftest.py @@ -14,16 +14,16 @@ import base64 import os -import subprocess -import shutil -import pytest -import docker import re +import shutil +import subprocess import sys +import docker +import pytest from docker.errors import BuildError -from sagemaker.utils import sagemaker_timestamp, _tmpdir, sts_regional_endpoint +from sagemaker.utils import _tmpdir, sagemaker_timestamp, sts_regional_endpoint REPO_ACCOUNT_ID = "033110030271" @@ -68,7 +68,7 @@ "RUN curl 'https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip' -o 'awscliv2.zip' \ && unzip awscliv2.zip \ && ./aws/install\n\n" - "RUN apt install sudo\n" + "RUN apt install -y sudo\n" "RUN useradd -ms /bin/bash integ-test-user\n" # Add the user to sudo group "RUN usermod -aG sudo integ-test-user\n" From 7ef18b1404ef9e547ba202a3e919cb7741ee315f Mon Sep 17 00:00:00 2001 From: adtian2 <55163384+adtian2@users.noreply.github.com> Date: Wed, 20 Aug 2025 16:45:41 -0700 Subject: [PATCH 162/164] GPT OSS Hotfix (#5263) * changes for gpt_oss jobs support * added unit tests * fixing unit test --- src/sagemaker/modules/train/sm_recipes/utils.py | 1 + src/sagemaker/pytorch/estimator.py | 1 + .../unit/sagemaker/modules/train/sm_recipes/test_utils.py | 5 +++++ tests/unit/test_pytorch.py | 8 ++++++++ 4 files changed, 15 insertions(+) diff --git a/src/sagemaker/modules/train/sm_recipes/utils.py b/src/sagemaker/modules/train/sm_recipes/utils.py index 3b7659016e..b6523e14dd 100644 --- a/src/sagemaker/modules/train/sm_recipes/utils.py +++ b/src/sagemaker/modules/train/sm_recipes/utils.py @@ -136,6 +136,7 @@ def _get_trainining_recipe_gpu_model_name_and_script(model_type: str): "mistral": ("mistral", "mistral_pretrain.py"), "mixtral": ("mixtral", "mixtral_pretrain.py"), "deepseek": ("deepseek", "deepseek_pretrain.py"), + "gpt_oss": ("custom_model", "custom_pretrain.py"), } for key in model_type_to_script: diff --git a/src/sagemaker/pytorch/estimator.py b/src/sagemaker/pytorch/estimator.py index 633317927b..208239e368 100644 --- a/src/sagemaker/pytorch/estimator.py +++ b/src/sagemaker/pytorch/estimator.py @@ -99,6 +99,7 @@ def _get_training_recipe_gpu_script(code_dir, recipe, source_dir): "mistral": ("mistral", "mistral_pretrain.py"), "mixtral": ("mixtral", "mixtral_pretrain.py"), "deepseek": ("deepseek", "deepseek_pretrain.py"), + "gpt_oss": ("custom_model", "custom_pretrain.py"), } if "model" not in recipe: diff --git a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py index a58b1f641e..17cfda55b0 100644 --- a/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py +++ b/tests/unit/sagemaker/modules/train/sm_recipes/test_utils.py @@ -237,6 +237,11 @@ def test_get_args_from_recipe_with_nova_and_role(mock_get_args_from_nova_recipe, "script": "deepseek_pretrain.py", "model_base_name": "deepseek", }, + { + "model_type": "gpt_oss", + "script": "custom_pretrain.py", + "model_base_name": "custom_model", + }, ], ) def test_get_trainining_recipe_gpu_model_name_and_script(test_case): diff --git a/tests/unit/test_pytorch.py b/tests/unit/test_pytorch.py index 34d3c6784b..8352f3090b 100644 --- a/tests/unit/test_pytorch.py +++ b/tests/unit/test_pytorch.py @@ -1087,6 +1087,14 @@ def test_training_recipe_for_trainium(sagemaker_session): }, }, }, + { + "script": "custom_pretrain.py", + "recipe": { + "model": { + "model_type": "gpt_oss", + }, + }, + }, ], ) @patch("shutil.copyfile") From 417fb56f3b14ab44d79f7078872e54ca2044983b Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 21 Aug 2025 04:26:16 +0000 Subject: [PATCH 163/164] prepare release v2.251.0 --- CHANGELOG.md | 12 ++++++++++++ VERSION | 2 +- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 26578e980a..37c1d155cc 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,17 @@ # Changelog +## v2.251.0 (2025-08-21) + +### Features + + * support pipeline versioning + +### Bug Fixes and Other Changes + + * GPT OSS Hotfix + * dockerfile stuck on interactive shell + * add sleep for model deployment + ## v2.250.0 (2025-08-08) ### Features diff --git a/VERSION b/VERSION index 51f3762b3d..b52df981a9 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.250.1.dev0 +2.251.0 From eb6d3c7aef2ea944eea39c1fbe0adfb21255c4e2 Mon Sep 17 00:00:00 2001 From: ci Date: Thu, 21 Aug 2025 04:26:20 +0000 Subject: [PATCH 164/164] update development version to v2.251.1.dev0 --- VERSION | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/VERSION b/VERSION index b52df981a9..a74cccc543 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -2.251.0 +2.251.1.dev0