maintain tests

Author: Z80coder

neurallogic/symbolic_generation.py

@@ -308,9 +308,9 @@ def eval_symbolic_expression(x: str):
     return eval(eval_str)
 
 
-#@dispatch
-#def eval_symbolic_expression(x: numpy.ndarray):
-#    return numpy.vectorize(eval)(x)
+@dispatch
+def eval_symbolic_expression(x: numpy.ndarray):
+    return numpy.vectorize(eval_symbolic_expression)(x)
 
 
 #@dispatch

neurallogic/symbolic_primitives.py

@@ -1,8 +1,9 @@
-import numpy
-from plum import dispatch
 import typing
+
 import jax
 import jax._src.lax_reference as lax_reference
+import numpy
+from plum import dispatch
 
 
 # TODO: remove me?
@@ -175,6 +176,15 @@ def symbolic_operator(operator: str, x: bool, y: str):
 @dispatch
 def symbolic_operator(operator: str, x: str, y: numpy.ndarray):
     return numpy.vectorize(symbolic_operator, otypes=[object])(operator, x, y)
+@dispatch
+def symbolic_operator(operator: str, x: str, y: int):
+    return symbolic_operator(operator, x, str(y))
+@dispatch
+def symbolic_operator(operator: str, x: list, y: numpy.ndarray):
+    return numpy.vectorize(symbolic_operator, otypes=[object])(operator, x, y)
+@dispatch
+def symbolic_operator(operator: str, x: numpy.ndarray, y: jax.numpy.ndarray):
+    return numpy.vectorize(symbolic_operator, otypes=[object])(operator, x, y)
 # XXX
 
 
@@ -188,6 +198,7 @@ def symbolic_operator(operator: str, x: list):
     return symbolic_operator(operator, numpy.array(x))
 
 
+# TODO: remove infix_operator?
 @dispatch
 def symbolic_infix_operator(operator: str, a: str, b: str) -> str:
     return f'{a} {operator} {b}'.replace('\'', '')

tests/test_hard_and.py

@@ -9,7 +9,6 @@
 from tests import utils
 
 
-
 def test_include():
     test_data = [
         [[1.0, 1.0], 1.0],
@@ -23,7 +22,7 @@ def test_include():
     ]
     for input, expected in test_data:
         utils.check_consistency(hard_and.soft_and_include, hard_and.hard_and_include,
-                           expected, input[0], input[1])
+                                expected, input[0], input[1])
 
 
 def test_neuron():
@@ -43,7 +42,7 @@ def hard(weights, input):
             return hard_and.hard_and_neuron(weights, input)
 
         utils.check_consistency(soft, hard, expected,
-                          jax.numpy.array(weights), jax.numpy.array(input))
+                                jax.numpy.array(weights), jax.numpy.array(input))
 
 
 def test_layer():
@@ -66,9 +65,8 @@ def soft(weights, input):
         def hard(weights, input):
             return hard_and.hard_and_layer(weights, input)
 
-
         utils.check_consistency(soft, hard, jax.numpy.array(expected),
-                          jax.numpy.array(weights), jax.numpy.array(input))
+                                jax.numpy.array(weights), jax.numpy.array(input))
 
 
 def test_and():
@@ -172,7 +170,7 @@ def test_net(type, x):
     soft_input = jax.numpy.array([0.6, 0.45])
     weights = soft.init(random.PRNGKey(0), soft_input)
     soft_result = soft.apply(weights, numpy.array(soft_input))
-    
+
     # Compute hard result
     hard_weights = harden.hard_weights(weights)
     hard_input = harden.harden(soft_input)
@@ -189,25 +187,24 @@ def test_net(type, x):
     symbolic_input = ['True', 'False']
     symbolic_weights = symbolic_generation.make_symbolic(hard_weights)
     symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
-    symbolic_output = symbolic_generation.eval_symbolic_expression(symbolic_output)
+    symbolic_output = symbolic_generation.eval_symbolic_expression(
+        symbolic_output)
     # Check that the symbolic result is the same as the hard result
     assert numpy.array_equal(symbolic_output, hard_result)
 
     # Compute symbolic result with symbolic inputs and non-symbolic weights
     symbolic_input = ['x1', 'x2']
     symbolic_output = symbolic.apply(hard_weights, symbolic_input)
     # Check the form of the symbolic expression
-    assert numpy.array_equal(symbolic_output, ['True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
- 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
- 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True)',
- 'True and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or True) and ((True and ((x1 != 0) or False) and ((x2 != 0) or False) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False) and ((True and ((x1 != 0) or False) and ((x2 != 0) or True) != 0) or False)'])
+    assert numpy.array_equal(symbolic_output, ['numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), False)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), False)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), False)), 0), True)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), True)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), False)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False)), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), False)), numpy.logical_or(lax_reference.ne(x2, 0), True)), 0), False))'])
 
     # Compute symbolic result with symbolic inputs and symbolic weights
     symbolic_output = symbolic.apply(symbolic_weights, symbolic_input)
     # Check the form of the symbolic expression
-    assert numpy.array_equal(symbolic_output, ['True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
- 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
- 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0)))',
- 'True and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((False != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((True != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0))) and ((True and ((x1 != 0) or not((True != 0))) and ((x2 != 0) or not((False != 0))) != 0) or not((True != 0)))'])
-
-    
+    assert numpy.array_equal(symbolic_output, ['numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(True, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0))))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(True, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0))))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(True, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0))))',
+                                               'numpy.logical_and(numpy.logical_and(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(False, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(True, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(numpy.logical_and(numpy.logical_and(True, numpy.logical_or(lax_reference.ne(x1, 0), numpy.logical_not(lax_reference.ne(True, 0)))), numpy.logical_or(lax_reference.ne(x2, 0), numpy.logical_not(lax_reference.ne(False, 0)))), 0), numpy.logical_not(lax_reference.ne(True, 0))))'])