Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Bump torch from 1.7.1+cu110 to 1.13.1 in /Projects/ProtoRes/code #5

Open
wants to merge 1 commit into
base: main
Choose a base branch
from

Conversation

dependabot[bot]
Copy link

@dependabot dependabot bot commented on behalf of github Jan 13, 2023

Bumps torch from 1.7.1+cu110 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

General Overview

Releasing a new version of PyTorch generally entails 3 major steps:

  1. Cutting a release branch preparations
  2. Cutting a release branch and making release branch specific changes
  3. Drafting RCs (Release Candidates), and merging cherry picks
  4. Promoting RCs to stable and performing release day tasks

Cutting a release branch preparations

Following Requirements needs to be met prior to final RC Cut:

  • Resolve all outstanding issues in the milestones(for example 1.11.0)before first RC cut is completed. After RC cut is completed following script should be executed from builder repo in order to validate the presence of the fixes in the release branch :

... (truncated)

Commits

Dependabot compatibility score

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)
  • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
  • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
  • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
  • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

You can disable automated security fix PRs for this repo from the Security Alerts page.

Bumps [torch](https://github.com/pytorch/pytorch) from 1.7.1+cu110 to 1.13.1.
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/master/RELEASE.md)
- [Commits](https://github.com/pytorch/pytorch/commits/v1.13.1)

---
updated-dependencies:
- dependency-name: torch
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Jan 13, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
dependencies Pull requests that update a dependency file
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants