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doc/api/training/sdp_versions/latest.rst

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<https://docs.aws.amazon.com/sagemaker/latest/dg/data-parallel-use-api.html#data-parallel-use-python-skd-api>`_
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for more information.
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Version 1.4.0 (Latest)
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======================
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Version 1.4.0, 1.4.1 (Latest)
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=============================
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.. toctree::
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:maxdepth: 1

doc/api/training/sdp_versions/v1.2.x/smd_data_parallel_pytorch.rst

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.. note::
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The ``no_sync()`` context manager is available from smdistributed-dataparallel v1.2.2.
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To find the release note, see :ref:`sdp_1.2.2_release_note`.
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To find the release note, see :ref:`sdp_release_note`.
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**Example:**
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doc/api/training/smd_data_parallel_release_notes/smd_data_parallel_change_log.rst

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.. _sdp_1.2.2_release_note:
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.. _sdp_release_note:
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#############
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Release Notes
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New features, bug fixes, and improvements are regularly made to the SageMaker
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distributed data parallel library.
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SageMaker Distributed Data Parallel 1.4.0 Release Notes
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SageMaker Distributed Data Parallel 1.4.1 Release Notes
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=======================================================
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*Date: May. 3. 2022*
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**Currency Updates**
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* Added support for PyTorch 1.11.0
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**Known Issues**
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* The library currently does not support the PyTorch sub-process groups API (torch.distributed.new_group (https://pytorch.org/docs/stable/distributed.html#torch.distributed.new_group)).
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**Migration to AWS Deep Learning Containers**
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This version passed benchmark testing and is migrated to the following AWS Deep Learning Containers (DLC):
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- PyTorch 1.11.0 DLC
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.. code::
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763104351884.dkr.ecr.<region>.amazonaws.com/pytorch-training:1.11.0-gpu-py38-cu113-ubuntu20.04-sagemaker
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Binary file of this version of the library for custom container users:
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.. code::
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https://smdataparallel.s3.amazonaws.com/binary/pytorch/1.11.0/cu113/2022-04-14/smdistributed_dataparallel-1.4.1-cp38-cp38-linux_x86_64.whl
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----
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Release History
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===============
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SageMaker Distributed Data Parallel 1.4.0 Release Notes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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*Date: Feb. 24. 2022*
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**New Features**
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763104351884.dkr.ecr.<region>.amazonaws.com/pytorch-training:1.10.2-gpu-py38-cu113-ubuntu20.04-sagemaker
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----
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Release History
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===============
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SageMaker Distributed Data Parallel 1.2.2 Release Notes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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doc/api/training/smd_model_parallel_release_notes/smd_model_parallel_change_log.rst

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New features, bug fixes, and improvements are regularly made to the SageMaker
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distributed model parallel library.
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SageMaker Distributed Model Parallel 1.8.1 Release Notes
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SageMaker Distributed Model Parallel 1.9.0 Release Notes
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========================================================
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*Date: May. 3. 2022*
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**Currency Updates**
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* Added support for PyTorch 1.11.0
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**Migration to AWS Deep Learning Containers**
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This version passed benchmark testing and is migrated to the following AWS Deep Learning Containers (DLC):
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- PyTorch 1.11.0 DLC
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.. code::
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763104351884.dkr.ecr.<region>.amazonaws.com/pytorch-training:1.11.0-gpu-py38-cu113-ubuntu20.04-sagemaker
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Binary file of this version of the library for custom container users:
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.. code::
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https://sagemaker-distributed-model-parallel.s3.us-west-2.amazonaws.com/pytorch-1.11.0/build-artifacts/2022-04-20-17-05/smdistributed_modelparallel-1.9.0-cp38-cp38-linux_x86_64.whl
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----
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Release History
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===============
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SageMaker Distributed Model Parallel 1.8.1 Release Notes
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--------------------------------------------------------
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*Date: April. 23. 2022*
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SageMaker Distributed Model Parallel 1.8.0 Release Notes
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763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
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* The binary file of this version of the library for custom container users
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The binary file of this version of the library for custom container users:
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.. code::
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doc/api/training/smp_versions/latest.rst

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To use the library, reference the
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**Common API** documentation alongside the framework specific API documentation.
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Version 1.7.0, 1.8.0, 1.8.1 (Latest)
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====================================
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Version 1.7.0, 1.8.0, 1.8.1, 1.9.0 (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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