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Add FlexAttention examples to SDPA tutorial #3674

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@dorbittonn dorbittonn commented Nov 29, 2025
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Summary

  • Add new section demonstrating flex_attention from PyTorch 2.5
  • Include score_mod examples: relative position bias and ALiBi
  • Show block_mask for sparse attention patterns (causal masking)
  • Demonstrate combining score_mod and block_mask
  • Add performance comparison with standard SDPA

Test plan

  • All FlexAttention code tested with PyTorch 2.7.1
  • Verified output shapes are correct
  • Compilation with torch.compile works as expected

Checklist

  • The issue that is being fixed is referred in the description
  • Only one issue is addressed in this pull request
  • Labels from the issue that this PR is fixing are added to this pull request
  • No unnecessary issues are included into this pull request

Add a new section demonstrating flex_attention from PyTorch 2.5:
- Custom score_mod functions (relative position bias, ALiBi)
- block_mask for sparse attention patterns (causal masking)
- Combining score_mod and block_mask
- Performance comparison with standard SDPA
This extends the existing SDPA tutorial with practical examples
of the flexible attention API for custom attention patterns.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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pytorch-bot bot commented Nov 29, 2025
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/tutorials/3674

Note: Links to docs will display an error until the docs builds have been completed.

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