[none][fix] AttributeError with return_perf_metrics on tensorrt backend #10662
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Signed-off-by: Dmitry Barsukoff <[email protected]>
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📝 WalkthroughWalkthroughA field refactoring that relocates Changes
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🤖 Fix all issues with AI agents
In `@tensorrt_llm/llmapi/llm_args.py`:
- Around line 2099-2103: The field perf_metrics_max_requests was moved to
BaseLlmArgs but its description references the wrong flag name; update the
description to reference return_perf_metrics (the actual boolean field, defined
near line 2095) instead of request_perf_metrics so it correctly reads that
return_perf_metrics must be true to get perf metrics; locate the Field for
perf_metrics_max_requests in BaseLlmArgs and replace the incorrect flag name in
the description text.
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tensorrt_llm/llmapi/llm_args.py
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**/*.py
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**/*.py: The code developed for TensorRT-LLM should conform to Python 3.8+
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Files:
tensorrt_llm/llmapi/llm_args.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/llmapi/llm_args.py
🧠 Learnings (4)
📓 Common learnings
Learnt from: jiaganc
Repo: NVIDIA/TensorRT-LLM PR: 7031
File: tensorrt_llm/bench/dataclasses/configuration.py:90-104
Timestamp: 2025-08-26T09:37:10.463Z
Learning: In TensorRT-LLM, the `get_pytorch_perf_config()` method returns `self.pytorch_config` which can contain default `cuda_graph_config` values, so `llm_args` may already have this config before the extra options processing.
📚 Learning: 2025-08-26T09:37:10.463Z
Learnt from: jiaganc
Repo: NVIDIA/TensorRT-LLM PR: 7031
File: tensorrt_llm/bench/dataclasses/configuration.py:90-104
Timestamp: 2025-08-26T09:37:10.463Z
Learning: In TensorRT-LLM, the `get_pytorch_perf_config()` method returns `self.pytorch_config` which can contain default `cuda_graph_config` values, so `llm_args` may already have this config before the extra options processing.
Applied to files:
tensorrt_llm/llmapi/llm_args.py
📚 Learning: 2025-08-14T15:38:01.771Z
Learnt from: MatthiasKohl
Repo: NVIDIA/TensorRT-LLM PR: 6904
File: cpp/tensorrt_llm/pybind/thop/bindings.cpp:55-57
Timestamp: 2025-08-14T15:38:01.771Z
Learning: In TensorRT-LLM Python bindings, tensor parameter collections like mla_tensor_params and spec_decoding_tensor_params are kept as required parameters without defaults to maintain API consistency, even when it might affect backward compatibility.
Applied to files:
tensorrt_llm/llmapi/llm_args.py
📚 Learning: 2025-08-26T09:37:10.463Z
Learnt from: jiaganc
Repo: NVIDIA/TensorRT-LLM PR: 7031
File: tensorrt_llm/bench/dataclasses/configuration.py:90-104
Timestamp: 2025-08-26T09:37:10.463Z
Learning: In TensorRT-LLM's bench configuration, the `get_pytorch_perf_config()` method returns `self.pytorch_config` which is a Dict[str, Any] that can contain default values including `cuda_graph_config`, making the fallback `llm_args["cuda_graph_config"]` safe to use.
Applied to files:
tensorrt_llm/llmapi/llm_args.py
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tensorrt_llm/llmapi/llm_args.py (1)
tensorrt_llm/builder.py (1)
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Signed-off-by: Dmitry Barsukoff <[email protected]>
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Description
Currently,
return_perf_metricsis defined in BaseLlmArgs, whileperf_metrics_max_requestsis defined in TorchLlmArgs.However, for the TensorRT backend, if return_perf_metrics is set to True, an AttributeError is raised in openai_server.py#L144
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