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Bumps torch from 2.1.0 to 2.2.0.

Release notes

Sourced from torch's releases.

PyTorch 2.2: FlashAttention-v2, AOTInductor

PyTorch 2.2 Release Notes

  • Highlights
  • Backwards Incompatible Changes
  • Deprecations
  • New Features
  • Improvements
  • Bug fixes
  • Performance
  • Documentation

Highlights

We are excited to announce the release of PyTorch® 2.2! PyTorch 2.2 offers ~2x performance improvements to scaled_dot_product_attention via FlashAttention-v2 integration, as well as AOTInductor, a new ahead-of-time compilation and deployment tool built for non-python server-side deployments.

This release also includes improved torch.compile support for Optimizers, a number of new inductor optimizations, and a new logging mechanism called TORCH_LOGS.

Please note that we are deprecating macOS x86 support, and PyTorch 2.2.x will be the last version that supports macOS x64.

Along with 2.2, 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 3,628 commits and 521 contributors since PyTorch 2.1. 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 2.2. More information about how to get started with the PyTorch 2-series can be found at our Getting Started page.

Summary:

  • scaled_dot_product_attention (SDPA) now supports FlashAttention-2, yielding around 2x speedups compared to previous versions.
  • PyTorch 2.2 introduces a new ahead-of-time extension of TorchInductor called AOTInductor, designed to compile and deploy PyTorch programs for non-python server-side.
  • torch.distributed supports a new abstraction for initializing and representing ProcessGroups called device_mesh.
  • PyTorch 2.2 ships a standardized, configurable logging mechanism called TORCH_LOGS.
  • A number of torch.compile improvements are included in PyTorch 2.2, including improved support for compiling Optimizers and improved TorchInductor fusion and layout optimizations.
  • Please note that we are deprecating macOS x86 support, and PyTorch 2.2.x will be the last version that supports macOS x64.
  • torch.ao.quantization now offers a prototype torch.export based flow

... (truncated)

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Bumps [torch](https://github.com/pytorch/pytorch) from 2.1.0 to 2.2.0.
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v2.1.0...v2.2.0)

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

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Jul 25, 2024
choeqq pushed a commit that referenced this pull request Sep 24, 2025
* feat(apify): Show list of built tags in actor run action

* feat(apify): Allow selecting actor search source for run Actor action and change how Actor or task name is displayed

* feat(apif): Remove wait for finish prop in run Actor action

* fix(apify): Fix PR issues

* fix(apif): Fix PR issues

* fix(scrape-single-url): return the only dataset item after the run is finished (#3)

* fix(scrape-single-url): return the only dataset item after the run is finished

* fix(scrape-single-url): version up

* fix(scrape-single-url): version up

* fix(scrape-single-url): version up

* fix(scrape-single-url): introduce a job status constant, expand a list of terminal statuses to stop the loop

* fix(scrape-single-url): import constants from package, decrease delay in between calls

* Migrate to use Apify client (#6)

* feat(apify): Replace Axios with Apify client

* fix(general): adding custom headers to client()=> preserve whole config to be passed to Axios later

* feat(general): add linter script

* fix(apify-get-dataset-items): a function for getting items and parsing of a result

* fix(apify-run-actor): working sync and async, dynamic input schema injection, KVS output retrieval tested only string

* fix(general): change maxResults for limit as an input field

* fix(run-task-sync): move items retrieval to the component, add waitSecs determined by input or plan to prevent blunt timeout error, have the item retrieval logic be connected to run status, clean return value

* fix(apify-scrape-single-url): incorporate timeouts, rework the whole API interaction logic

* fix(apify-set-key-value-store-record): detection of content type, fixed API interaction

* fix(apify-scrape-single-url): remove waiting timeout, return only dataset item, remove extra input fields connected to WCC run

* fix(apify-run-actor): success message

* fix(apify-run-task-synchronously): remove waiting for run to finish timeout

* fix(app): remove paidPlan input filed config

---------

Co-authored-by: Matyas Cimbulka <[email protected]>

* fix(apify-get-dataset-items) 6: change input parameters (#8)

* chore(apify): Bump component versions

* chore: Sync upstream repo (PipedreamHQ#9)

* feat(apify): Prefill values from the input schema (#7)

* Revert "chore: Sync upstream repo (PipedreamHQ#9)"

This reverts commit cd804ba.

* Revert "chore(apify): Bump component versions"

This reverts commit 6040822 which for some reason bumped version of the wrong components.

* fix(apify): Fix build tag

* fix(apify): Address issues in run task synchronously action

* feat(apify): Add default crawler type to scrape single url

* fix(apify): Address issues from PR

* chore(apify): Change component versions

* fix(apify): Fix run Actor action

* fix(apify): Fix run get dataset items action

* fix(apify): Fix typos for PR

---------

Co-authored-by: Oleksandra Valko <[email protected]>
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