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doc/amazon_sagemaker_debugger.rst

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.. warning::
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This page is no longer supported for maintenence. The live documentation is at `Debug and Profile Training Jobs Using Amazon SageMaker Debugger <https://docs.aws.amazon.com/sagemaker/latest/dg/train-debugger.html>`_
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and `Debugger API <https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html>`_.
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This page is no longer supported for maintenence. The live documentation is at `Debug and Profile Training Jobs Using Amazon SageMaker Debugger <https://docs.aws.amazon.com/sagemaker/latest/dg/train-debugger.html>`_
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and `Debugger API <https://sagemaker.readthedocs.io/en/stable/api/training/debugger.html>`_.
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Amazon SageMaker Debugger allows you to detect anomalies while training your machine learning model by emitting relevant data during training, storing the data and then analyzing it.

doc/api/training/debugger.rst

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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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.. warning::
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SageMaker Debugger deprecates the framework profiling feature starting from TensorFlow 2.11 and PyTorch 2.0. You can still use the feature in the previous versions of the frameworks and SDKs as follows.
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* SageMaker Python SDK <= v2.130.0
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* PyTorch >= v1.6.0, < v2.0
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* TensorFlow >= v2.3.1, < v2.11
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With the deprecation, SageMaker Debugger discontinues support for the APIs below this note.
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See also `Amazon SageMaker Debugger Release Notes: March 16, 2023 <https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-release-notes.html#debugger-release-notes-20230315>`_.
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* SageMaker Python SDK <= v2.130.0
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* PyTorch >= v1.6.0, < v2.0
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* TensorFlow >= v2.3.1, < v2.11
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With the deprecation, SageMaker Debugger discontinues support for the APIs below this note.
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See also `Amazon SageMaker Debugger Release Notes: March 16, 2023 <https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-release-notes.html#debugger-release-notes-20230315>`_.
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.. autoclass:: FrameworkProfile
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:show-inheritance:

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