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Add MoE Integration Tests For CUTLASS Coverage #16280
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Summary of ChangesHello @Jonahcb, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the testing infrastructure for Mixture-of-Experts (MoE) operations by introducing new integration tests. The primary goal is to achieve complete path coverage for all relevant CUTLASS kernels, thereby improving the reliability and robustness of MoE implementations within the system. Highlights
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Code Review
This pull request adds four new integration tests for MoE with CUTLASS kernels, improving test coverage for cutlass_fused_experts_fp8, cutlass_w4a8_moe, cutlass_w4a8_moe_deepep_normal, and cutlass_w4a8_moe_deepep_ll. The changes are straightforward and align with the goal of complete CUTLASS path coverage. My main feedback is regarding code duplication in the test configurations, which could be refactored for better maintainability.
Motivation
Add 4 more MoE integration tests to achieve complete CUTLASS path coverage.
Modifications
Adds coverage for these 4 CUTLASS kernels:
cutlass_fused_experts_fp8,cutlass_w4a8_moe,cutlass_w4a8_moe_deepep_normal,cutlass_w4a8_moe_deepep_ll.cutlass_moe_fp4is already covered by an existing test case. Thus, all 5 CUTLASS paths are tested.Accuracy Tests
moe_runner_cutlass_fp8:Score: 0.600 Writing report to /tmp/mmlu_gaunernst_DeepSeek-V2-Lite-Chat-FP8.html {'other': np.float64(0.5), 'other:std': np.float64(0.5), 'score:std': np.float64(0.48989794855663565), 'stem': np.float64(1.0), 'stem:std': np.float64(0.0), 'score': np.float64(0.6)}moe_runner_cutlass_w4a8:Total latency: 18.074 s Score: 0.600 Writing report to /tmp/mmlu_tencent_DeepSeek-V3.1-Terminus-W4AFP8.html {'other': np.float64(0.5), 'other:std': np.float64(0.5), 'score:std': np.float64(0.48989794855663565), 'stem': np.float64(1.0), 'stem:std': np.float64(0.0), 'score': np.float64(0.6)}moe_runner_cutlass_w4a8_deepep_normal:Score: 0.800 Writing report to /tmp/mmlu_tencent_DeepSeek-V3.1-Terminus-W4AFP8.html {'other': np.float64(0.75), 'other:std': np.float64(0.4330127018922193), 'score:std': np.float64(0.4000000000000001), 'stem': np.float64(1.0), 'stem:std': np.float64(0.0), 'score': np.float64(0.8)}moe_runner_cutlass_w4a8_deepep_ll:Total latency: 15.509 s Score: 0.600 Writing report to /tmp/mmlu_tencent_DeepSeek-V3.1-Terminus-W4AFP8.html {'other': np.float64(0.5), 'other:std': np.float64(0.5), 'score:std': np.float64(0.48989794855663565), 'stem': np.float64(1.0), 'stem:std': np.float64(0.0), 'score': np.float64(0.6)}Benchmarking and Profiling
Checklist
Review Process
/tag-run-ci-label,/rerun-failed-ci,/tag-and-rerun-ci) or contact authorized users to do so.