[None][fix] CHERRY-PICK trtllm-serve yaml loading (#7551) #7897
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Signed-off-by: Yan Chunwei <328693+Superjomn@users.noreply.github.com>
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📝 WalkthroughWalkthroughAdds post-merge override logic in llm_args processing: after merging llm_args and llm_args_dict, if build_config exists in llm_args, selected keys from llm_args_dict overwrite corresponding fields in llm_args["build_config"], with info logs per overridden key. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant Caller
participant LLMArgs as LLM Args Processor
Caller->>LLMArgs: merge(llm_args, llm_args_dict)
activate LLMArgs
Note over LLMArgs: Perform base merge of dictionaries
alt build_config present in llm_args
LLMArgs->>LLMArgs: for k in {max_batch_size, max_num_tokens,<br/>max_beam_width, max_seq_len}
alt key k exists in llm_args_dict
LLMArgs-->>LLMArgs: log info "override k"
LLMArgs->>LLMArgs: llm_args["build_config"][k] = llm_args_dict[k]
else key missing
Note over LLMArgs: skip k
end
else no build_config
Note over LLMArgs: no overrides applied
end
LLMArgs-->>Caller: merged llm_args (with possible overrides)
deactivate LLMArgs
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
✅ Passed checks (1 passed)
✨ Finishing touches
🧪 Generate unit tests
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📒 Files selected for processing (1)
tensorrt_llm/llmapi/llm_args.py(1 hunks)
🧰 Additional context used
📓 Path-based instructions (3)
**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh,py}
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
Use only spaces, no tabs; indent with 4 spaces.
Files:
tensorrt_llm/llmapi/llm_args.py
**/*.py
📄 CodeRabbit inference engine (CODING_GUIDELINES.md)
**/*.py: Python code must target Python 3.8+.
Indent Python code with 4 spaces; do not use tabs.
Maintain module namespace when importing; prefer 'from package.subpackage import foo' then 'foo.SomeClass()' instead of importing the class directly.
Python filenames should be snake_case (e.g., some_file.py).
Python classes use PascalCase names.
Functions and methods use snake_case names.
Local variables use snake_case; prefix 'k' for variables that start with a number (e.g., k_99th_percentile).
Global variables use upper SNAKE_CASE prefixed with 'G' (e.g., G_MY_GLOBAL).
Constants use upper SNAKE_CASE (e.g., MY_CONSTANT).
Avoid shadowing variables from an outer scope.
Initialize all externally visible members of a class in the constructor.
Prefer docstrings for interfaces that may be used outside a file; comments for in-function or file-local interfaces.
Use Google-style docstrings for classes and functions (Sphinx-parsable).
Document attributes and variables inline so they render under the class/function docstring.
Avoid reflection when a simpler, explicit approach suffices (e.g., avoid dict(**locals()) patterns).
In try/except, catch the most specific exceptions possible.
For duck-typing try/except, keep the try body minimal and use else for the main logic.
Files:
tensorrt_llm/llmapi/llm_args.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/llmapi/llm_args.py
🧠 Learnings (2)
📚 Learning: 2025-08-26T09:37:10.463Z
Learnt from: jiaganc
PR: NVIDIA/TensorRT-LLM#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: 2025-08-26T09:37:10.463Z
Learnt from: jiaganc
PR: NVIDIA/TensorRT-LLM#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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🔇 Additional comments (1)
tensorrt_llm/llmapi/llm_args.py (1)
2581-2581: Incompatible dict union ('|') — replace with dict unpacking to preserve declared Python supportsetup.py declares python_requires=">=3.7, <4"; the dict union operator requires Python >=3.9. Change tensorrt_llm/llmapi/llm_args.py:2581 from:
llm_args = llm_args | llm_args_dict
to:
llm_args = {**llm_args, **llm_args_dict}⛔ Skipped due to learnings
Learnt from: ixlmar PR: NVIDIA/TensorRT-LLM#7294 File: tensorrt_llm/_torch/modules/rms_norm.py:17-17 Timestamp: 2025-08-27T14:23:55.566Z Learning: The TensorRT-LLM project requires Python 3.10+ as evidenced by the use of TypeAlias from typing module, match/case statements, and union type | syntax throughout the codebase, despite some documentation still mentioning Python 3.8+.Learnt from: jiaganc PR: NVIDIA/TensorRT-LLM#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.
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Summary by CodeRabbit
Description
Test Coverage
PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
The reviewers assigned automatically/manually are appropriate for the PR.
Please check this after reviewing the above items as appropriate for this PR.
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