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Lightning-AI / tutorials

Collection of Pytorch lightning tutorial form as rich scripts automatically transformed to ipython notebooks.
https://lightning-ai.github.io/tutorials
Apache License 2.0
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Update torch requirement from <2.1.0,>=1.8.1 to >=1.8.1,<2.2.0 in /_requirements #291

Closed dependabot[bot] closed 10 months ago

dependabot[bot] commented 1 year ago

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

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.
  • torch.sparse now includes prototype support for semi-structured (2:4) sparsity on NVIDIA® GPUs.

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

PyTorch version Python Stable CUDA Experimental CUDA
2.1 >=3.8, <=3.11 CUDA 11.8, CUDNN 8.7.0.84 CUDA 12.1, CUDNN 8.9.2.26

... (truncated)

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dependabot[bot] commented 1 year ago

Dependabot tried to add @Lightning-AI/core-lightning as a reviewer to this PR, but received the following error from GitHub:

POST https://api.github.com/repos/Lightning-AI/tutorials/pulls/291/requested_reviewers: 422 - Reviews may only be requested from collaborators. One or more of the teams you specified is not a collaborator of the Lightning-AI/tutorials repository. // See: https://docs.github.com/rest/pulls/review-requests#request-reviewers-for-a-pull-request
codecov[bot] commented 1 year ago

Codecov Report

Merging #291 (a57889e) into main (3b4e9a0) will not change coverage. The diff coverage is n/a.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #291 +/- ## =================================== Coverage 71% 71% =================================== Files 2 2 Lines 399 399 =================================== Hits 285 285 Misses 114 114 ```
dependabot[bot] commented 10 months ago

Superseded by #310.