[https://nvbugs/5766986][fix] fixed the shard_all_unprocessed default value to align with the default.yml #10271
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📝 WalkthroughWalkthroughModified the default value of Changes
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tensorrt_llm/_torch/auto_deploy/transform/library/sharding.py (1)
138-142: Alignment with default.yaml is confirmed; consider adding explicit test coverage for the new default behavior.The change of
default=Falsetodefault=Truecorrectly aligns with the configuration indefault.yaml, which specifiesshard_all_unprocessed: truein the detect_sharding transform. This behavioral change ensures unprocessed linear nodes are automatically sharded using simple sharding (column split + all_gather), expanding the coverage of sharding optimizations.The test files (test_bmm_sharding.py, test_ep_sharding.py, test_tp_sharding.py) do not currently include explicit tests for the
shard_all_unprocessedparameter with different values. Consider adding test cases that verify the new default behavior to prevent regression.
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Signed-off-by: Eran Geva <[email protected]>
Signed-off-by: Eran Geva <[email protected]>
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this PR fixes also https://nvbugs/5766982 and https://nvbugs/5766974
this regression entered in #10087
the bug was that the simple sharding was disabled when working in headless mode (not using trtllm-bench or any other executable, e.g. in tests), causing unit tests that expect sharding to happen to fail
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