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Bump torch from 1.4.0 to 1.13.1
Bumps torch from 1.4.0 to 1.13.1.
Release notes
Sourced from torch's releases.
PyTorch 1.13.1 Release, small bug fix release
This release is meant to fix the following issues (regressions / silent correctness):
- RuntimeError by torch.nn.modules.activation.MultiheadAttention with bias=False and batch_first=True #88669
- Installation via pip on Amazon Linux 2, regression #88869
- Installation using poetry on Mac M1, failure #88049
- Missing masked tensor documentation #89734
- torch.jit.annotations.parse_type_line is not safe (command injection) #88868
- Use the Python frame safely in _pythonCallstack #88993
- Double-backward with full_backward_hook causes RuntimeError #88312
- Fix logical error in get_default_qat_qconfig #88876
- Fix cuda/cpu check on NoneType and unit test #88854 and #88970
- Onnx ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops #88504
- Onnx operator_export_type on the new registry #87735
- torchrun AttributeError caused by file_based_local_timer on Windows #85427
The release tracker should contain all relevant pull requests related to this release as well as links to related issues
PyTorch 1.13: beta versions of functorch and improved support for Apple’s new M1 chips are now available
Pytorch 1.13 Release Notes
- Highlights
- Backwards Incompatible Changes
- New Features
- Improvements
- Performance
- Documentation
- Developers
Highlights
We are excited to announce the release of PyTorch 1.13! This includes stable versions of BetterTransformer. We deprecated CUDA 10.2 and 11.3 and completed migration of CUDA 11.6 and 11.7. Beta includes improved support for Apple M1 chips and functorch, a library that offers composable vmap (vectorization) and autodiff transforms, being included in-tree with the PyTorch release. This release is composed of over 3,749 commits and 467 contributors since 1.12.1. We want to sincerely thank our dedicated community for your contributions.
Summary:
The BetterTransformer feature set supports fastpath execution for common Transformer models during Inference out-of-the-box, without the need to modify the model. Additional improvements include accelerated add+matmul linear algebra kernels for sizes commonly used in Transformer models and Nested Tensors is now enabled by default.
Timely deprecating older CUDA versions allows us to proceed with introducing the latest CUDA version as they are introduced by Nvidia®, and hence allows support for C++17 in PyTorch and new NVIDIA Open GPU Kernel Modules.
Previously, functorch was released out-of-tree in a separate package. After installing PyTorch, a user will be able to
import functorch
and use functorch without needing to install another package.PyTorch is offering native builds for Apple® silicon machines that use Apple's new M1 chip as a beta feature, providing improved support across PyTorch's APIs.
Stable Beta Prototype Better TransformerCUDA 10.2 and 11.3 CI/CD Deprecation Enable Intel® VTune™ Profiler's Instrumentation and Tracing Technology APIsExtend NNC to support channels last and bf16Functorch now in PyTorch Core LibraryBeta Support for M1 devices Arm® Compute Library backend support for AWS Graviton CUDA Sanitizer You can check the blogpost that shows the new features here.
Backwards Incompatible changes
... (truncated)
Changelog
Sourced from torch's changelog.
Releasing PyTorch
- Release Compatibility Matrix
- General Overview
- Cutting a release branch preparations
- Cutting release branches
- Drafting RCs (https://github.com/pytorch/pytorch/blob/main/Release Candidates) for PyTorch and domain libraries
- Promoting RCs to Stable
- Additional Steps to prepare for release day
- Patch Releases
- Hardware / Software Support in Binary Build Matrix
- Special Topics
Release Compatibility Matrix
Following is the Release Compatibility Matrix for PyTorch releases:
PyTorch version Python Stable CUDA Experimental CUDA 2.0 >=3.8, <=3.11 CUDA 11.7, CUDNN 8.5.0.96 CUDA 11.8, CUDNN 8.7.0.84 1.13 >=3.7, <=3.10 CUDA 11.6, CUDNN 8.3.2.44 CUDA 11.7, CUDNN 8.5.0.96 1.12 >=3.7, <=3.10 CUDA 11.3, CUDNN 8.3.2.44 CUDA 11.6, CUDNN 8.3.2.44 General Overview
... (truncated)
Commits
49444c3
[BE] Do not package caffe2 in wheel (#87986) (#90433)56de8a3
Add manual cuda deps search logic (#90411) (#90426)a4d16e0
Fix ATen Fallback for BUILD_CAFFE2=0 for ONNX-only ops (#88504) (#90104)80abad3
Handle Tensor.deepcopy via clone(), on IPU (#89129) (#89999)73a852a
[Release only change] Fix rocm5.1.1 docker image (#90321)029ec16
Add platform markers for linux only extra_install_requires (#88826) (#89924)197c5c0
Fix cuda/cpu check on NoneType (#88854) (#90068)aadbeb7
Make TorchElastic timer importable on Windows (#88522) (#90045)aa94433
Mark IPU device as not supports_as_strided (#89130) (#89998)59b4f3b
Use the Python frame safely in _pythonCallstack (#89997)- Additional commits viewable in compare view
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