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.
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Bumps torch from 1.8.1 to 1.13.1.
Release notes
Sourced from torch's releases.
... (truncated)
Changelog
Sourced from torch's changelog.
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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)Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
@dependabot rebase
.Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/amzn/trans-encoder/network/alerts).