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intermediate_source/transformer_building_blocks.py

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"""
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.. meta::
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:description: Learn how to optimize transformer models by replacing nn.Transformer with Nested Tensors and torch.compile() for significant performance gains in PyTorch.
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Accelerating PyTorch Transformers by replacing ``nn.Transformer`` with Nested Tensors and ``torch.compile()``
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=============================================================================================================
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**Author:** `Mikayla Gawarecki <https://github.com/mikaylagawarecki>`_

prototype_source/nestedtensor.py

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# how implement multi-head attention for transformers in a way that avoids computation on padding.
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# For more information, check out the docs for the
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# `torch.nested <https://pytorch.org/docs/stable/nested.html>`__ namespace.
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#
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# See Also
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# --------
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#
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# * `Accelerating PyTorch Transformers by replacing nn.Transformer with Nested Tensors and torch.compile() <https://docs.pytorch.org/tutorials/intermediate/transformer_building_blocks.html`__

prototype_source/prototype_index.rst

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:header: (prototype) Using GPUDirect Storage
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:card_description: Learn how to use GPUDirect Storage in PyTorch.
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:image: ../_static/img/thumbnails/cropped/generic-pytorch-logo.png
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:link: ../prototype/gpudirect_storage.html
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:link: ../prototype/gpu_direct_storage.html
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:tags: GPUDirect-Storage
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.. End of tutorial card section

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