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Pull request overview
This PR performs code refactoring focused on simplifying NPU operations and improving code quality in the Ascend backend implementation.
- Simplified attention mask generation and removed unnecessary type conversions
- Cleaned up function call signatures by using keyword arguments instead of excessive positional parameters
- Fixed a bug where the graph capturing flag wasn't properly reset
Reviewed changes
Copilot reviewed 2 out of 3 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| dlinfer/vendor/ascend/torch_npu_ops.py | Refactored attention operations to remove unnecessary type conversions, simplified mask generation logic, and cleaned up API calls by using keyword arguments |
| dlinfer/framework/lmdeploy_ext/cudagraph/ascend_cudagraph.py | Changed kv_start_indices buffer dtype from int64 to int32 for consistency, and fixed bug by properly resetting the capturing flag after graph capture |
| .github/workflows/main.yml | Updated CI workflow to use DeepLink-org fork and refactor_code branch for testing |
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This reverts commit 99af61b.
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related PR InternLM/lmdeploy#4176