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[RLlib](deps): Bump torch from 1.8.1 to 1.9.0 in /python/requirements/rllib#29

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[RLlib](deps): Bump torch from 1.8.1 to 1.9.0 in /python/requirements/rllib#29
dependabot[bot] wants to merge 1 commit intomasterfrom
dependabot/pip/python/requirements/rllib/torch-1.9.0

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@dependabot dependabot bot commented on behalf of github Jul 16, 2021

Bumps torch from 1.8.1 to 1.9.0.

Release notes

Sourced from torch's releases.

PyTorch 1.9 Release, including Torch.Linalg and Mobile Interpreter

PyTorch 1.9 Release Notes

  • Highlights
  • Backwards Incompatible Change
  • Deprecations
  • New Features
  • Improvements
  • Bug Fixes
  • Performance
  • Documentation

Highlights

We are excited to announce the release of PyTorch 1.9. The release is composed of more than 3,400 commits since 1.8, made by 398 contributors. Highlights include:

  • Major improvements to support scientific computing, including torch.linalg, torch.special, and Complex Autograd
  • Major improvements in on-device binary size with Mobile Interpreter
  • Native support for elastic-fault tolerance training through the upstreaming of TorchElastic into PyTorch Core
  • Major updates to the PyTorch RPC framework to support large scale distributed training with GPU support
  • New APIs to optimize performance and packaging for model inference deployment
  • Support for Distributed training, GPU utilization and SM efficiency in the PyTorch Profiler

We’d like to thank the community for their support and work on this latest release. We’d especially like to thank Quansight and Microsoft for their contributions.

You can find more details on all the highlighted features in the PyTorch 1.9 Release blogpost.

Backwards Incompatible changes

Python API

  • torch.divide with rounding_mode='floor' now returns infinity when a non-zero number is divided by zero ([#56893](pytorch/pytorch#56893)). This fixes the rounding_mode='floor' behavior to return the same non-finite values as other rounding modes when there is a division by zero. Previously it would always result in a NaN value, but a non-zero number divided by zero should return +/- infinity in IEEE floating point arithmetic. Note this does not effect torch.floor_divide or the floor division operator, which currently use rounding_mode='trunc' (and are also deprecated for that reason).

... (truncated)

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Bumps [torch](https://github.com/pytorch/pytorch) from 1.8.1 to 1.9.0.
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/master/RELEASE.md)
- [Commits](pytorch/pytorch@v1.8.1...v1.9.0)

---
updated-dependencies:
- dependency-name: torch
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Jul 16, 2021
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dependabot bot commented on behalf of github Sep 25, 2021

Superseded by #63.

@dependabot dependabot bot closed this Sep 25, 2021
@dependabot dependabot bot deleted the dependabot/pip/python/requirements/rllib/torch-1.9.0 branch September 25, 2021 07:10
architkulkarni pushed a commit that referenced this pull request Nov 3, 2022
…9164)" (#29… (ray-project#29196)

This reverts the PR and fixes the test failures

This also fixes a bug around _monitor_jobs API. the monitor job can be called on the same job twice now, which will break the event (because at the end of monitor job, we record the event that job is completed). The same completed event can be reported twice without the fix
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