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Pushing the docs to dev/ for branch: main, commit 06a6b931f359fb894c0750ed932a147d42eff049
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‎dev/.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: ac9b50a69ffb644129a81e421b4a4c4f
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config: 38cef46b6802d559794f4317c62c8a58
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tags: 645f666f9bcd5a90fca523b33c5a78b7

‎dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

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‎dev/_downloads/2c8efe31be0d68b7945dbfbff0788dd3/plot_prediction_latency.ipynb

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‎dev/_downloads/5f054219fb38e926537d741fe5832e8c/plot_prediction_latency.py

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fig, ax1 = plt.subplots(figsize=(10, 6))
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colors = ["r", "g", "b"]
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for i, cls_name in enumerate(percentiles.keys()):
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x = np.array(sorted([n for n in percentiles[cls_name].keys()]))
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x = np.array(sorted(percentiles[cls_name].keys()))
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y = np.array([percentiles[cls_name][n] for n in x])
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plt.plot(
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x,

‎dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip

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‎dev/_downloads/scikit-learn-docs.zip

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‎dev/_images/sphx_glr_plot_agglomerative_clustering_004.png

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‎dev/_images/sphx_glr_plot_anomaly_comparison_001.png

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‎dev/_images/sphx_glr_plot_caching_nearest_neighbors_001.png

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