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tests: add MoE subgraph tests with require_full_compilation enforcement#4179

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yizhuoz004 wants to merge 1 commit intopytorch:mainfrom
yizhuoz004:hlo-moe-tests
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tests: add MoE subgraph tests with require_full_compilation enforcement#4179
yizhuoz004 wants to merge 1 commit intopytorch:mainfrom
yizhuoz004:hlo-moe-tests

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Description

Add tests/py/dynamo/hlo/test_moe.py covering all 7 MoE routing and dispatch variants from popular open-source LLMs (Mixtral, Qwen2, Qwen3, Llama4, DeepSeek-V2, DeepSeek-V3/R1, Nemotron-H). 50 parameterized test cases verify TRT numerical correctness against PyTorch reference.

Extend DispatchTestCase.run_test() with require_full_compilation=True support: calls TRTInterpreter.validate_conversion() before building the engine and fails immediately if any op lacks a TRT converter. All MoE tests pass this check, confirming zero PyTorch fallback for every routing/dispatch/expert-MLP combination tested.

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Type of change

Tests

Checklist:

  • [x ] My code follows the style guidelines of this project (You can use the linters)
  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas and hacks
  • I have made corresponding changes to the documentation
  • I have added tests to verify my fix or my feature
  • New and existing unit tests pass locally with my changes
  • I have added the relevant labels to my PR in so that relevant reviewers are notified

@github-actions github-actions bot added the component: tests Issues re: Tests label Apr 9, 2026
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meta-cla bot commented Apr 9, 2026

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@github-actions github-actions bot added the component: build system Issues re: Build system label Apr 9, 2026
Add tests/py/dynamo/hlo/test_moe.py covering all 7 MoE routing and
dispatch variants from popular open-source LLMs (Mixtral, Qwen2, Qwen3,
Llama4, DeepSeek-V2, DeepSeek-V3/R1, Nemotron-H).  50 parameterized
test cases verify TRT numerical correctness against PyTorch reference.

Extend DispatchTestCase.run_test() with require_full_compilation=True
support: calls TRTInterpreter.validate_conversion() before building the
engine and fails immediately if any op lacks a TRT converter.  All MoE
tests pass this check, confirming zero PyTorch fallback for every
routing/dispatch/expert-MLP combination tested.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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