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PyTorch 2.3.1 Release, bug fix release

Updated September 26, 2026 · 2:46 PM · source date June 5, 2024

Summary

PyTorch 2.3.1 Release, bug fix release pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k PyTorch 2.3.1 Release, bug fix release atalman released this 05 Jun 19:16 · 40946 commits to main since this release v2.3.1 63d5e92 This commit was created on GitHub.com and signed with GitHub’s verified signature . GPG key ID: B5690EEEBB952194 Verified Learn about vigilant mode .

Why it matters

This Other is relevant to the technology intelligence record because it involves GitHub, Docker. The source article should remain the factual reference for follow-up coverage.

Key facts
  • pytorch / pytorch Public Notifications You must be signed in to change notification settings Fork 30.5k Star 103k PyTorch 2.3.1 Release, bug fix release atalman released this 05 Jun 19:16 · 40946 commits to main since this release v2.3.1 63d5e92 This commit was created on GitHub.com and signed with GitHub’s verified signature .
  • GPG key ID: B5690EEEBB952194 Verified Learn about vigilant mode .
  • This release is meant to fix the following issues (regressions / silent correctness): Torch.compile: Remove runtime dependency on JAX/XLA, when importing torch.__dynamo ( #124634 ) Hide Plan failed with a cudnnException warning ( #125790 ) Fix CUDA memory leak ( #124238 ) ( #120756 ) Distributed: Fix format_utils executable , which was causing it to run as a no-op ( #123407 ) Fix regression with device_mesh in 2.3.0 during initialization causing memory spikes ( #124780 ) Fix crash of FSDP + DTensor with ShardingStrategy.SHARD_GRAD_OP ( #123617 ) Fix failure with distributed checkpointing + FSDP if at least 1 forward/backward pass has not been run.
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