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Bump torch from 1.13.1 to 2.1.1 #430

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@dependabot dependabot bot commented on behalf of github Nov 20, 2023

Bumps torch from 1.13.1 to 2.1.1.

Release notes

Sourced from torch's releases.

PyTorch 2.1.1 Release, bug fix release

This release is meant to fix the following issues (regressions / silent correctness):

  • Remove spurious warning in comparison ops (#112170)
  • Fix segfault in foreach_* operations when input list length does not match (#112349)
  • Fix cuda driver API to load the appropriate .so file (#112996)
  • Fix missing CUDA initialization when calling FFT operations (#110326)
  • Ignore beartype==0.16.0 within the onnx package as it is incompatible (#111861)
  • Fix the behavior of torch.new_zeros in onnx due to TorchScript behavior change (#111694)
  • Remove unnecessary slow code in torch.distributed.checkpoint.optimizer.load_sharded_optimizer_state_dict (#111687)
  • Add planner argument to torch.distributed.checkpoint.optimizer.load_sharded_optimizer_state_dict (#111393)
  • Continue if param not exist in sharded load in torch.distributed.FSDP (#109116)
  • Fix handling of non-contiguous bias_mask in torch.nn.functional.scaled_dot_product_attention (#112673)
  • Fix the meta device implementation for nn.functional.scaled_dot_product_attention (#110893)
  • Fix copy from mps to cpu device when storage_offset is non-zero (#109557)
  • Fix segfault in torch.sparse.mm for non-contiguous inputs (#111742)
  • Fix circular import between Dynamo and einops (#110575)
  • Verify flatbuffer module fields are initialized for mobile deserialization (#109794)

The pytorch/pytorch#110961 contains all relevant pull requests related to this release as well as links to related issues.

PyTorch 2.1: automatic dynamic shape compilation, distributed checkpointing

PyTorch 2.1 Release Notes

  • Highlights
  • Backwards Incompatible Change
  • Deprecations
  • New Features
  • Improvements
  • Bug fixes
  • Performance
  • Documentation
  • Developers
  • Security

Highlights

We are excited to announce the release of PyTorch® 2.1! PyTorch 2.1 offers automatic dynamic shape support in torch.compile, torch.distributed.checkpoint for saving/loading distributed training jobs on multiple ranks in parallel, and torch.compile support for the NumPy API.

In addition, this release offers numerous performance improvements (e.g. CPU inductor improvements, AVX512 support, scaled-dot-product-attention support) as well as a prototype release of torch.export, a sound full-graph capture mechanism, and torch.export-based quantization.

Along with 2.1, we are also releasing a series of updates to the PyTorch domain libraries. More details can be found in the library updates blog.

This release is composed of 6,682 commits and 784 contributors since 2.0. We want to sincerely thank our dedicated community for your contributions. As always, we encourage you to try these out and report any issues as we improve 2.1. More information about how to get started with the PyTorch 2-series can be found at our Getting Started page.

Summary:

  • torch.compile now includes automatic support for detecting and minimizing recompilations due to tensor shape changes using automatic dynamic shapes.
  • torch.distributed.checkpoint enables saving and loading models from multiple ranks in parallel, as well as resharding due to changes in cluster topology.
  • torch.compile can now compile NumPy operations via translating them into PyTorch-equivalent operations.
  • torch.compile now includes improved support for Python 3.11.
  • New CPU performance features include inductor improvements (e.g. bfloat16 support and dynamic shapes), AVX512 kernel support, and scaled-dot-product-attention kernels.
  • torch.export, a sound full-graph capture mechanism is introduced as a prototype feature, as well as torch.export-based quantization.

... (truncated)

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Bumps [torch](https://github.com/pytorch/pytorch) from 1.13.1 to 2.1.1.
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v1.13.1...v2.1.1)

---
updated-dependencies:
- dependency-name: torch
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Nov 20, 2023
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dependabot bot commented on behalf of github Dec 18, 2023

Superseded by #457.

@dependabot dependabot bot closed this Dec 18, 2023
@dependabot dependabot bot deleted the dependabot/pip/torch-2.1.1 branch December 18, 2023 19:54
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