Bump torch from 2.0.0 to 2.1.2

[dependabot[bot]]

Bumps torch from 2.0.0 to 2.1.2.

Release notes

Sourced from torch's releases.

PyTorch 2.1.2 Release, bug fix release

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

• Fix crashes for float16 empty tensors (pytorch/pytorch#115183)
• Fix MPS memory corruption when working with tensor slices (pytorch/pytorch#114838)
• Fix crashes during Conv backward pass on MPS devices (pytorch/pytorch#113398)
• Partially fix nn.Linear behavior on AArch64 platform (pytorch/pytorch#110150)
• Fix cosine_similarity for tensors of different sizes (pytorch/pytorch#109363)
• Package missing headers needed for extension development (pytorch/pytorch#113055)
• Improve error handling of torch.set_num_threads (pytorch/pytorch#113684)
• Fix profiling traces generation (pytorch/pytorch#113763)

The Cherry pick tracker pytorch/pytorch#113962 contains all relevant pull requests related to this release as well as links to related issues.

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

... (truncated)

Commits

• a8e7c98 Revert "Require less alignment for attn bias (#114173) (#114837)"
• 448700d Fix NULL dereference in binary CPU ops (#115241)
• 5965649 Require less alignment for attn bias (#114173) (#114837)
• 41210ea [MPS] Fix out-of-bounds fill to sliced tensor (#114958)
• 3183bcd Fix mkldnn_matmul error on AArch64 (#114851)
• b5a89bb Fix broadcasting cosine_similarity (#114795)
• 3f662b6 Package pybind11/eigen/ (#113055) (#114756)
• 614af50 [release only] Pin disabled-test-condensed and slow-tests json (#114514)
• b3b22d7 [BE] Handle errors in set_num_threads (#114420)
• 7405d70 [MPS] Fix crashes during Conv backward pass (#114419)
• Additional commits viewable in compare view

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