[None][fix] Accommodate Phi3/4 to work with ModelOpt's FP8 ckpts in Torch #6761
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Signed-off-by: Michal Guzek <[email protected]>
📝 WalkthroughWalkthroughThe weight loading process in the modeling_phi3.py module was updated to include optional scale factors for fused QKV and gated MLP projections. When a Changes
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tensorrt_llm/_torch/models/modeling_phi3.py (1)
1-1: Add NVIDIA Apache license header to modeling_phi3.pyThe new file
tensorrt_llm/_torch/models/modeling_phi3.pyis missing the standard NVIDIA Apache 2.0 license header required for all.pysource files. Please insert the following block at the very top (using the current year 2025):--- a/tensorrt_llm/_torch/models/modeling_phi3.py +++ b/tensorrt_llm/_torch/models/modeling_phi3.py @@ -0,0 +1,13 +# Copyright 2025 NVIDIA CORPORATION & AFFILIATES +# +# 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. + from typing import Optional, Tuple• File needing update:
- tensorrt_llm/_torch/models/modeling_phi3.py
🧹 Nitpick comments (1)
tensorrt_llm/_torch/models/modeling_phi3.py (1)
193-193: Remove no-op statement.
self.model_config.mapping.tp_sizeon its own has no effect. Drop it or assign to a variable if needed later.- self.model_config.mapping.tp_size + # tp_size available via self.model_config.mapping.tp_size if needed
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tensorrt_llm/_torch/models/modeling_phi3.py(1 hunks)
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Learnt from: moraxu
PR: NVIDIA/TensorRT-LLM#6303
File: tests/integration/test_lists/qa/examples_test_list.txt:494-494
Timestamp: 2025-07-28T17:06:08.621Z
Learning: In TensorRT-LLM testing, it's common to have both CLI flow tests (test_cli_flow.py) and PyTorch API tests (test_llm_api_pytorch.py) for the same model. These serve different purposes: CLI flow tests validate the traditional command-line workflow, while PyTorch API tests validate the newer LLM API backend. Both are legitimate and should coexist.
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Description
fix: Accommodate Phi3/4 to work with ModelOpt's FP8 ckpts in Torch, given the models use a fused
qkv_projandgateup_proj.Test Coverage
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