[None][chore] enable EPLB for DEEPGEMM#10617
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📝 WalkthroughWalkthroughThe MoE load-balancer support was expanded to include Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes 🚥 Pre-merge checks | ✅ 2 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
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⚠️ Outside diff range comments (1)
tensorrt_llm/_torch/modules/fused_moe/create_moe.py (1)
245-258: Missinginit_load_balancerparameter forDeepGemmFusedMoEinstantiation.For EPLB to actually work with
DeepGemmFusedMoE, theinit_load_balancerparameter must be passed to the constructor. The relevant code snippet confirmsDeepGemmFusedMoE.__init__acceptsinit_load_balancerandwithout_commflags. Compare toCutlassFusedMoE(line 197),TRTLLMGenFusedMoE(line 177), andCuteDslFusedMoE(line 242) which all pass these parameters.🐛 Proposed fix
elif moe_cls == DeepGemmFusedMoE: return moe_cls( routing_method=routing_method, num_experts=num_experts, hidden_size=hidden_size, intermediate_size=intermediate_size, dtype=dtype, reduce_results=reduce_results, model_config=model_config, aux_stream_dict=aux_stream_dict, weight_loading_mode=weight_loading_mode, apply_router_weight_on_input=apply_router_weight_on_input, layer_idx=layer_idx, + init_load_balancer=init_load_balancer, + without_comm=without_comm, )
🤖 Fix all issues with AI agents
In @tensorrt_llm/_torch/modules/fused_moe/create_moe.py:
- Around line 140-143: The assertion message is out of sync with the asserted
classes: update the error string in the assert inside create_moe.py so it
mentions DeepGemmFusedMoE as well; modify the message associated with the assert
that references WideEPMoE, CutlassFusedMoE, TRTLLMGenFusedMoE and
CuteDslFusedMoE to include DeepGemmFusedMoE (or reword to “...supported in
WideEPMoE, CutlassFusedMoE, TRTLLMGenFusedMoE, CuteDslFusedMoE and
DeepGemmFusedMoE.”) so the text matches the list used in the assertion.
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📒 Files selected for processing (1)
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
🧰 Additional context used
📓 Path-based instructions (2)
**/*.py
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
**/*.py: The code developed for TensorRT-LLM should conform to Python 3.8+
Indent Python code with 4 spaces. Do not use tabs
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Avoid shadowing variables declared in an outer scope in Python
Initialize all externally visible members of a Python class in the constructor
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Files:
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
**/*.{cpp,cc,cxx,h,hpp,hxx,cu,cuh,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
All TensorRT-LLM source files (.cpp, .h, .cu, .py, and other source files) should contain an NVIDIA copyright header with the year of latest meaningful modification
Files:
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
🧠 Learnings (4)
📓 Common learnings
Learnt from: sklevtsov-nvidia
Repo: NVIDIA/TensorRT-LLM PR: 3294
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:1198-1209
Timestamp: 2025-08-08T22:03:40.707Z
Learning: In the CUTLASS MoE kernels (cpp/tensorrt_llm/cutlass_extensions), when `layout_info.fusion` is set to `TmaWarpSpecializedGroupedGemmInput::EpilogueFusion::FINALIZE`, the `router_scales` parameter must be non-null by design. The fused finalize kernel epilogue does not perform nullptr checks and requires valid router scales to function correctly. This is an implicit contract that callers must satisfy when enabling the FINALIZE fusion mode.
Learnt from: djns99
Repo: NVIDIA/TensorRT-LLM PR: 6915
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:4010-4012
Timestamp: 2025-08-14T23:23:27.449Z
Learning: For MOE (Mixture of Experts) code reviews in TensorRT-LLM, avoid repeatedly suggesting finalize fusion validation checks and safety assertions. The user djns99 has indicated these suggestions are repetitive and unwanted across multiple MOE-related changes.
📚 Learning: 2025-08-14T23:23:27.449Z
Learnt from: djns99
Repo: NVIDIA/TensorRT-LLM PR: 6915
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:4010-4012
Timestamp: 2025-08-14T23:23:27.449Z
Learning: For MOE (Mixture of Experts) code reviews in TensorRT-LLM, avoid repeatedly suggesting finalize fusion validation checks and safety assertions. The user djns99 has indicated these suggestions are repetitive and unwanted across multiple MOE-related changes.
Applied to files:
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
📚 Learning: 2025-08-21T02:39:12.009Z
Learnt from: djns99
Repo: NVIDIA/TensorRT-LLM PR: 7104
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu:1475-1480
Timestamp: 2025-08-21T02:39:12.009Z
Learning: The min latency mode functionality in TensorRT-LLM MOE kernels (cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_kernels.cu) is deprecated and no longer being maintained/updated, as confirmed by djns99. Bug reports and optimization suggestions for the computeStridesTmaWarpSpecializedLowLatencyKernel and related min latency code paths should be deprioritized.
Applied to files:
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
📚 Learning: 2025-08-09T20:57:04.084Z
Learnt from: sklevtsov-nvidia
Repo: NVIDIA/TensorRT-LLM PR: 3294
File: cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_gemm_tma_warp_specialized_input.cu:118-127
Timestamp: 2025-08-09T20:57:04.084Z
Learning: In the CUTLASS MoE finalize fusion implementation (cpp/tensorrt_llm/kernels/cutlass_kernels/moe_gemm/moe_gemm_tma_warp_specialized_input.cu), when setting `fused_finalize_epilogue.stride_final_output` with shape `(hidden_size, num_output_tokens, 1)`, the `num_rows_in_final_output` should be set to `num_output_tokens` (not `hidden_size`) because of a swap+transpose operation that maps rows of the output tensor to `hidden_size` and columns to `num_output_tokens`.
Applied to files:
tensorrt_llm/_torch/modules/fused_moe/create_moe.py
🧬 Code graph analysis (1)
tensorrt_llm/_torch/modules/fused_moe/create_moe.py (1)
tensorrt_llm/_torch/modules/fused_moe/fused_moe_deepgemm.py (1)
DeepGemmFusedMoE(350-880)
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