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Documentation: sm distributed model parallel doc versioning updating (#2097)
* documentation: adding docs dedicated to SageMaker distributed versions * documentation: updating section names * documentation: reverting makefile and sdp toc depth Co-authored-by: Ahsan Khan <[email protected]>
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‎doc/api/training/smd_data_parallel_pytorch.rst renamed to ‎doc/api/training/sdp_versions/smd_data_parallel_pytorch.rst

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‎doc/api/training/smd_data_parallel_tensorflow.rst renamed to ‎doc/api/training/sdp_versions/smd_data_parallel_tensorflow.rst

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‎doc/api/training/smd_data_parallel.rst

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###################################
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##########################
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Distributed data parallel
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###################################
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##########################
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SageMaker's distributed data parallel library extends SageMaker’s training
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capabilities on deep learning models with near-linear scaling efficiency,
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.. toctree::
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:maxdepth: 2
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smd_data_parallel_pytorch
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smd_data_parallel_tensorflow
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sdp_versions/smd_data_parallel_pytorch
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sdp_versions/smd_data_parallel_tensorflow

‎doc/api/training/smd_model_parallel.rst

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<https://integ-docs-aws.amazon.com/sagemaker/latest/dg/model-parallel-use-api.html#model-parallel-customize-container>`__
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for more information.
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How to Use this Guide
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=====================
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Use with the SageMaker Python SDK
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=================================
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Use the following page to learn how to configure and enable distributed model parallel
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when you configure an Amazon SageMaker Python SDK `Estimator`.
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.. toctree::
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:maxdepth: 1
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smd_model_parallel_general
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API Documentation
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=================
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The library contains a Common API that is shared across frameworks, as well as APIs
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that are specific to supported frameworks, TensorFlow and PyTorch. To use the library, reference the
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that are specific to supported frameworks, TensorFlow and PyTorch.
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Select a version to see the API documentation for version. To use the library, reference the
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**Common API** documentation alongside the framework specific API documentation.
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.. toctree::
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:maxdepth: 1
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smd_model_parallel_general
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smd_model_parallel_common_api
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smd_model_parallel_pytorch
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smd_model_parallel_tensorflow
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smp_versions/v1_1_0.rst
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It is recommended to use this documentation alongside `SageMaker Distributed Model Parallel
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<http://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel.html>`__ in the Amazon SageMaker
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- `Configuration tips and pitfalls
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-customize-tips-pitfalls.html>`__
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Latest Updates
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==============
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New features, bug fixes, and improvements are regularly made to the SageMaker distributed model parallel library.
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Release Notes
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=============
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New features, bug fixes, and improvements are regularly made to the SageMaker distributed model parallel library.
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To see the the latest changes made to the library, refer to the library
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`Release Notes
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<https://github.com/aws/sagemaker-python-sdk/blob/master/doc/api/training/smd_model_parallel_release_notes/>`_.

‎doc/api/training/smd_model_parallel_general.rst

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.. _sm-sdk-modelparallel-params:
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SageMaker Python SDK ``modelparallel`` parameters
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-------------------------------------------------
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=================================================
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The TensorFlow and PyTorch ``Estimator`` objects contains a ``distribution`` parameter,
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which is used to enable and specify parameters for the
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.. _ranking-basics:
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Ranking Basics
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--------------
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==============
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The library maintains a one-to-one mapping between processes and available GPUs:
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for each GPU, there is a corresponding CPU process. Each CPU process

‎doc/api/training/smd_model_parallel_common_api.rst renamed to ‎doc/api/training/smp_versions/v1.1.0/smd_model_parallel_common_api.rst

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Common SageMaker distributed model parallel library APIs
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--------------------------------------------------------
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.. admonition:: Contents
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The following APIs are common across all frameworks.
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- :ref:`communication_api`
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- :ref:`mpi_basics`
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Common API
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==========
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The following SageMaker distribute model parallel APIs are common across all frameworks.
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**Important**: This API document assumes you use the following import statement in your training scripts.
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variable. If ``method`` is not ``"variable"``, this argument is
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ignored.
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.. _mpi_basics:
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MPI Basics
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^^^^^^^^^^
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- ``smp.get_dp_group()``: The list of ranks that hold different
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replicas of the same model partition.
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.. _communication_api:
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Communication API
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=================
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^^^^^^^^^^^^^^^^^
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The library provides a few communication primitives which can be helpful while
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developing the training script. These primitives use the following

‎doc/api/training/smd_model_parallel_pytorch.rst renamed to ‎doc/api/training/smp_versions/v1.1.0/smd_model_parallel_pytorch.rst

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.. admonition:: Contents
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- :ref:`pytorch_saving_loading`
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- :ref:`pytorch_saving_loading_instructions`
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PyTorch API
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===========
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import smdistributed.modelparallel.torch as smp
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.. tip::
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Refer to
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`Modify a PyTorch Training Script
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-customize-training-script.html#model-parallel-customize-training-script-pt>`_
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to learn how to use the following API in your PyTorch training script.
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.. class:: smp.DistributedModel
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A sub-class of ``torch.nn.Module`` which specifies the model to be
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currently doesn’t work with the library. ``smp.amp.GradScaler`` replaces
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``torch.amp.GradScaler`` and provides the same functionality.
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.. _pytorch_saving_loading:
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APIs for Saving and Loading
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^^^^^^^^^^^^^^^^^^^^^^^^^^^
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``mp_rank`` loads the checkpoint corresponding to the ``mp_rank``.
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Should be used when loading a model trained with the library.
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.. _pytorch_saving_loading_instructions:
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General Instruction For Saving and Loading
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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‎doc/api/training/smd_model_parallel_tensorflow.rst renamed to ‎doc/api/training/smp_versions/v1.1.0/smd_model_parallel_tensorflow.rst

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import smdistributed.modelparallel.tensorflow as smp
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.. tip::
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Refer to
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`Modify a TensorFlow Training Script
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<https://docs.aws.amazon.com/sagemaker/latest/dg/model-parallel-customize-training-script.html#model-parallel-customize-training-script-tf>`_
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to learn how to use the following API in your TensorFlow training script.
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.. class:: smp.DistributedModel
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:noindex:

‎doc/api/training/smp_versions/v1_1_0.rst

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Version 1.1.0 (Latest)
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======================
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To use the library, reference the Common API documentation alongside the framework specific API documentation.
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.. toctree::
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:maxdepth: 1
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v1.1.0/smd_model_parallel_common_api
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v1.1.0/smd_model_parallel_pytorch
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v1.1.0/smd_model_parallel_tensorflow

‎doc/conf.py

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html_theme_options = {
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"collapse_navigation": True,
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"sticky_navigation": True,
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"navigation_depth": 6,
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"includehidden": True,
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"titles_only": False,
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}
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htmlhelp_basename = "%sdoc" % project

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