[None][chore] Make use_low_precision_moe_combine as a llm arg #7598
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⚠️ Outside diff range comments (6)
tensorrt_llm/_torch/model_config.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Per repo guidelines, prepend the 2025 header.
Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0tensorrt_llm/_torch/pyexecutor/config.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0tensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0tensorrt_llm/_torch/pyexecutor/model_engine.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0examples/llm-api/quickstart_advanced.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0tensorrt_llm/llmapi/llm_args.py (1)
1-1: Add required NVIDIA Apache-2.0 header.Apply:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# http://www.apache.org/licenses/LICENSE-2.0 +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# SPDX-License-Identifier: Apache-2.0
🧹 Nitpick comments (3)
tensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.py (2)
192-193: Warn when the flag is ignored (non-NVFP4).Currently silently no-ops if NVFP4 isn’t present; surface a one-time info to aid debugging.
Apply:
- self.use_low_precision_combine = model_config.moe_low_precision_combine and qm.has_nvfp4( - ) + self.use_low_precision_combine = ( + model_config.moe_low_precision_combine and qm.has_nvfp4() + ) + if model_config.moe_low_precision_combine and not qm.has_nvfp4(): + logger.info_once( + "moe_low_precision_combine is set but ignored because NVFP4 quantization is not enabled.", + key="moe_lp_combine_ignored", + )
58-75: Avoid dataclass instance as default argument.model_config=ModelConfig() creates a shared instance across layers.
Apply:
- model_config: ModelConfig = ModelConfig(), + model_config: ModelConfig = None, @@ - super().__init__( + model_config = model_config or ModelConfig() + super().__init__(tensorrt_llm/llmapi/llm_args.py (1)
194-199: MoeConfig knob: LGTM; consider marking status.Marking as beta clarifies maturity in generated docs.
Apply:
- low_precision_combine: bool = Field( - default=False, - description= - "Use low precision combine in MoE operations (only for NVFP4 quantization). When enabled, uses lower precision for combining expert outputs to improve performance." - ) + low_precision_combine: bool = Field( + default=False, + description="Use low precision combine in MoE operations (only for NVFP4 quantization). When enabled, uses lower precision for combining expert outputs to improve performance.", + status="beta", + )
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examples/llm-api/quickstart_advanced.py(2 hunks)tensorrt_llm/_torch/model_config.py(1 hunks)tensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.py(1 hunks)tensorrt_llm/_torch/pyexecutor/config.py(1 hunks)tensorrt_llm/_torch/pyexecutor/model_engine.py(1 hunks)tensorrt_llm/llmapi/llm_args.py(2 hunks)
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tensorrt_llm/_torch/model_config.pytensorrt_llm/_torch/pyexecutor/config.pytensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.pytensorrt_llm/_torch/pyexecutor/model_engine.pytensorrt_llm/llmapi/llm_args.pyexamples/llm-api/quickstart_advanced.py
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Files:
tensorrt_llm/_torch/model_config.pytensorrt_llm/_torch/pyexecutor/config.pytensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.pytensorrt_llm/_torch/pyexecutor/model_engine.pytensorrt_llm/llmapi/llm_args.pyexamples/llm-api/quickstart_advanced.py
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
Prepend the NVIDIA Apache-2.0 copyright header with current year to the top of all source files (e.g., .cpp, .h, .cu, .py).
Files:
tensorrt_llm/_torch/model_config.pytensorrt_llm/_torch/pyexecutor/config.pytensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.pytensorrt_llm/_torch/pyexecutor/model_engine.pytensorrt_llm/llmapi/llm_args.pyexamples/llm-api/quickstart_advanced.py
🧬 Code graph analysis (3)
tensorrt_llm/_torch/modules/fused_moe/fused_moe_wide_ep.py (2)
tensorrt_llm/_torch/modules/linear.py (1)
has_nvfp4(1610-1613)tensorrt_llm/_torch/modules/fused_moe/interface.py (1)
has_nvfp4(133-136)
tensorrt_llm/llmapi/llm_args.py (1)
tensorrt_llm/builder.py (1)
default(50-58)
examples/llm-api/quickstart_advanced.py (1)
tensorrt_llm/llmapi/llm_args.py (1)
MoeConfig(168-202)
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🔇 Additional comments (6)
tensorrt_llm/_torch/model_config.py (1)
120-121: Add MoE flag: LGTM.Name and default make sense; kw-only placement is consistent. No functional concerns.
tensorrt_llm/_torch/pyexecutor/config.py (1)
63-63: Wire-through config: LGTM.Field naming matches ModelConfig and LLM args.
tensorrt_llm/_torch/pyexecutor/model_engine.py (1)
310-311: LGTM
load_config accepts kwargs andModelConfigdefinesmoe_low_precision_combine, so the flag is forwarded correctly.examples/llm-api/quickstart_advanced.py (2)
76-81: CLI flag: LGTM.Help text clearly scopes NVFP4-only behavior.
237-238: Wiring to MoeConfig: LGTM.Correct field name and default behavior.
tensorrt_llm/llmapi/llm_args.py (1)
2595-2596: Propagate to PyTorchConfig: LGTM.Field name aligns with PyTorchConfig.
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Signed-off-by: Zongfei Jing <20381269+zongfeijing@users.noreply.github.com>
…a llm arg (#7898) Signed-off-by: Zongfei Jing <20381269+zongfeijing@users.noreply.github.com>
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