Add ModelOpt W4A16 lm_head regression tests#44671
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| {"lm_head": {"quant_algo": "W4A16_NVFP4", "group_size": 16}} | ||
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| method = config.get_quant_method(_mock_lm_head(), prefix=prefix) |
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Mock Marlin support before instantiating W4A16 method
This new parametrized test runs unconditionally, but get_quant_method() constructs ModelOptNvFp4W4A16LinearMethod, whose constructor directly instantiates MarlinNvFp4LinearKernel; that kernel asserts is_fp4_marlin_supported() (current_platform.is_cuda() and capability >= 75). In CPU-only or unsupported-GPU test jobs this fails with an AssertionError, unlike the adjacent NVFP4 tests that patch kernel selection. Patch the Marlin kernel/support check here or skip the test when FP4 Marlin is unavailable.
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Signed-off-by: MerkyorLynn <268568828+MerkyorLynn@users.noreply.github.com>
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Hi maintainers, this is ready for review. Could you please add |
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Hi maintainers, quick clarification: the failing pre-run-check/RTD status appears to be the new-contributor gate rather than a docs/build failure. DCO passes, and this PR is intentionally scoped small. Could a maintainer please review the scope and add |
Summary
Add regression coverage for ModelOpt mixed-precision checkpoints that quantize
lm_head as W4A16_NVFP4.
Why
Some official ModelOpt NVFP4 MoE checkpoints include lm_head in
hf_quant_config.json with quant_algo = "W4A16_NVFP4". The LM head is a
ParallelLMHead, not a regular LinearBase, so it is useful to keep coverage
for this path separate from the generic W4A16 linear-layer tests.
This also adds Qwen3-MoE constructor coverage to ensure the model passes
quant_config into ParallelLMHead.
This PR is regression coverage only. It does not claim an end-to-end official
checkpoint load fix.
Duplicate-work check
Searched open PRs for ModelOpt W4A16 lm_head. Related but not duplicate:
This PR is scoped to ModelOpt mixed-precision W4A16_NVFP4 dispatch for
ParallelLMHead and Qwen3-MoE constructor coverage.
Validation
Targeted pytest was not run locally because this macOS checkout does not have
the vLLM test environment (pytest/torch) installed.
AI assistance was used to prepare this patch.