[https://nvbugs/6564714][fix] Fix the FP8BlockScaleMoERunner get_fallback_tactic - #17328
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WalkthroughThe FP8 MoE autotuner and fallback-tactic cache now include ChangesFP8 MoE tactic selection
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Inline comments:
In `@tensorrt_llm/_torch/custom_ops/trtllm_gen_custom_ops.py`:
- Around line 925-926: Update FP8BlockScaleMoERunner.unique_id() to include
num_fused_shared_experts, matching the fallback cache key and
get_valid_configs() inputs. Add a regression test that creates configurations
with different fused shared-expert counts and verifies their unique
IDs/autotuner cache entries remain distinct.
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brnguyen2
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Approving — the comments below are optional touch-ups, not blockers.
Fix looks right: the key order now matches FP8BlockScaleMoeRunner::getValidConfigs in cpp/tensorrt_llm/thop/fp8BlockScaleMoe.cpp:395 and get_valid_tactics at [tensorrt_llm/_torch/custom_ops/trtllm_gen_custom_ops.py:967](https://github.com/NVIDIA/TensorRT-LLM/pull/17328/files#diff-fe56cea5ab264b0896bbabd0288bbc3f6ffc18469c8c7fe771142be2bce8d022R967). Including it in unique_id() is also needed on its own, since the C++ side restricts tileN when fused shared experts are present — tactic validity genuinely depends on it.
Please confirm the two re-enabled AutoDeploy tests actually pass in this PR's B200 stage before merging, rather than only inferring it from the mechanism.
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…back_tactic Signed-off-by: leslief <leslief@nvidia.com>
Signed-off-by: leslief <leslief@nvidia.com>
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Dev Engineer Review
num_fused_shared_experts.nvbugs/6564714.nvbugs/6566730.QA Engineer Review
test-db/orqa/files were modified.Verdict: needs follow-up.
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