test:[nvbug 5415268] add kv_cache_free_gpu_mem_fraction param and llama4 rcca cases #6432
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WalkthroughThe changes introduce a new configuration parameter, Changes
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🧹 Nitpick comments (1)
tests/integration/defs/perf/test_perf.py (1)
1247-1248: Use 'is not None' for None comparison.Per Python best practices, use
is not Noneinstead of!= Nonefor None comparisons.- if self._config.ep_size != None: + if self._config.ep_size is not None:
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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.
🪛 Ruff (0.12.2)
tests/integration/defs/perf/test_perf.py
1232-1232: Comparison to None should be cond is not None
Replace with cond is not None
(E711)
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🔇 Additional comments (2)
tests/integration/defs/perf/test_perf.py (2)
74-74: LGTM: Model path update.The addition of the "nvidia/" prefix to the model path is consistent with the organizational structure.
1231-1238: LGTM: Parameter correctly added to benchmark command.The
kv_cache_free_gpu_mem_fractionparameter is properly passed to the trtllm-bench command.
| # Add kv cache free gpu mem fraction. | ||
| if self.kv_cache_free_gpu_mem_fraction != 0.9: | ||
| entries.append(f"kv_frac:{self.kv_cache_free_gpu_mem_fraction}") | ||
|
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Remove duplicate string representation logic.
The kv_cache_free_gpu_mem_fraction parameter is added to the string representation twice (lines 453-456 and 527-530), which will create duplicate entries.
Remove the duplicate logic:
# Add number of GPUs.
if self.num_gpus > 1:
entries.append(f"gpus:{self.num_gpus}")
- # Add kv cache free gpu mem fraction.
- if self.kv_cache_free_gpu_mem_fraction != 0.9:
- entries.append(f"kv_frac:{self.kv_cache_free_gpu_mem_fraction}")
-
# Concatenate labels with "-".
return "-".join(entries)Also applies to: 527-530
🤖 Prompt for AI Agents
In tests/integration/defs/perf/test_perf.py around lines 453 to 456, the code
appends the string representation of kv_cache_free_gpu_mem_fraction to entries,
but this is duplicated again at lines 527 to 530. To fix this, remove the block
at lines 453 to 456 that adds kv_cache_free_gpu_mem_fraction to entries,
ensuring it only appears once in the string representation logic at lines 527 to
530.
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Actionable comments posted: 0
♻️ Duplicate comments (3)
tests/integration/defs/perf/test_perf.py (3)
450-453: Verify duplicate string representation logic was resolved.This appears to add the kv_cache_free_gpu_mem_fraction to the string representation, but past review comments indicated this logic was duplicated at lines 527-530. Please confirm the duplicate was properly removed.
524-527: Remove duplicate string representation logic.This block duplicates the kv_cache_free_gpu_mem_fraction string representation logic from lines 450-453. Based on past review comments, this duplicate should have been removed but appears to still be present.
Apply this diff to remove the duplicate:
- # Add kv cache free gpu mem fraction. - if self.kv_cache_free_gpu_mem_fraction != 0.9: - entries.append(f"kv_frac:{self.kv_cache_free_gpu_mem_fraction}") -
639-643: Remove duplicate parameter parsing logic.This parsing logic for
kv_fracduplicates the implementation at lines 567-570. Based on past review comments, this duplicate should have been removed but appears to still be present.Apply this diff to remove the duplicate:
- if len(labels) > 0: - self.kv_cache_free_gpu_mem_fraction = 0.9 if not labels[ - 0].startswith("kv_frac:") else float( - labels.pop(0).replace("kv_frac:", "")) -
🧹 Nitpick comments (1)
tests/integration/defs/perf/test_perf.py (1)
1228-1235: LGTM! Benchmark command integration is correct, but fix None comparison.The integration of
kv_cache_free_gpu_mem_fractioninto the benchmark command is properly implemented and follows the existing pattern.However, address the static analysis hint about None comparison:
Apply this diff to fix the None comparison:
- if self._config.ep_size != None: + if self._config.ep_size is not None:
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📒 Files selected for processing (3)
tests/integration/defs/perf/pytorch_model_config.py(1 hunks)tests/integration/defs/perf/test_perf.py(9 hunks)tests/integration/test_lists/qa/trt_llm_release_perf_test.yml(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
- tests/integration/test_lists/qa/trt_llm_release_perf_test.yml
- tests/integration/defs/perf/pytorch_model_config.py
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📓 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.
Always maintain the namespace when importing in Python, even if only one class or function from a module is used.
Python filenames should use snake_case (e.g., some_file.py).
Python classes should use PascalCase (e.g., class SomeClass).
Python functions and methods should use snake_case (e.g., def my_awesome_function():).
Python local variables should use snake_case. Prefix k for variable names that start with a number (e.g., k_99th_percentile = ...).
Python global variables should use upper snake_case and prefix G (e.g., G_MY_GLOBAL = ...).
Python constants should use upper snake_case (e.g., MY_CONSTANT = ...).
Avoid shadowing variables declared in an outer scope in Python.
Initialize all externally visible members of a Python class in the constructor.
For interfaces that may be used outside a Python file, prefer docstrings over comments.
Comments in Python should be reserved for code within a function, or interfaces that are local to a file.
Use Google style docstrings for Python classes and functions, which can be parsed by Sphinx.
Attributes and variables in Python can be documented inline; attribute docstrings will be rendered under the docstring for the class.
Avoid using reflection in Python when functionality can be easily achieved without it.
When using try-except blocks in Python, limit the except to the smallest set of errors possible.
When using try-except blocks to handle multiple possible variable types in Python, keep the body of the try as small as possible, using the else block to implement the logic.
Files:
tests/integration/defs/perf/test_perf.py
**/*.{cpp,h,hpp,cc,cxx,cu,cuh,py}
📄 CodeRabbit Inference Engine (CODING_GUIDELINES.md)
All TensorRT-LLM Open Source Software code should contain an NVIDIA copyright header that includes the current year. This includes .cpp, .h, .cu, .py, and any other source files which are compiled or interpreted.
Files:
tests/integration/defs/perf/test_perf.py
🧠 Learnings (1)
📓 Common learnings
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.
🪛 Ruff (0.12.2)
tests/integration/defs/perf/test_perf.py
1229-1229: Comparison to None should be cond is not None
Replace with cond is not None
(E711)
🔇 Additional comments (4)
tests/integration/defs/perf/test_perf.py (4)
74-74: LGTM! Model path update looks correct.The addition of the "nvidia/" prefix to the model path aligns with the PR objectives for llama4 rcca cases and likely reflects the actual directory structure.
324-350: LGTM! Constructor parameter properly added.The
kv_cache_free_gpu_mem_fractionparameter is correctly added to the constructor with an appropriate default value of 0.9.
373-374: LGTM! Instance variable assignment is correct.The assignment of
kv_cache_free_gpu_mem_fractionto the instance variable is properly placed and follows the existing pattern.
567-570: LGTM! Parameter parsing logic is correct.The parsing logic for
kv_fracparameter is properly implemented, correctly extracting the float value from the test name labels.
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Actionable comments posted: 0
♻️ Duplicate comments (2)
tests/integration/defs/perf/test_perf.py (2)
450-453: Remove duplicate string representation logic.The
kv_cache_free_gpu_mem_fractionparameter is added to the string representation here and again at lines 524-527, which creates duplicate entries in the output string.Remove one of these duplicate blocks:
- # Add kv cache free gpu mem fraction. - if self.kv_cache_free_gpu_mem_fraction != 0.9: - entries.append(f"kv_frac:{self.kv_cache_free_gpu_mem_fraction}") -
567-570: Remove duplicate parameter parsing logic.The
kv_fracparameter parsing is implemented here and again at lines 639-643, which is redundant and could cause parsing inconsistencies.Remove one of these duplicate parsing blocks:
- if labels[0].startswith("kv_frac:"): - self.kv_cache_free_gpu_mem_fraction = float( - labels.pop(0).replace("kv_frac:", "")) -
🧹 Nitpick comments (1)
tests/integration/defs/perf/test_perf.py (1)
1244-1244: Useis not Nonefor None comparison.Following Python best practices, use
is not Noneinstead of!= Nonefor None comparisons.Apply this diff:
- if self._config.ep_size != None: + if self._config.ep_size is not None:
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (3)
tests/integration/defs/perf/pytorch_model_config.py(1 hunks)tests/integration/defs/perf/test_perf.py(9 hunks)tests/integration/test_lists/qa/trt_llm_release_perf_test.yml(1 hunks)
🚧 Files skipped from review as they are similar to previous changes (2)
- tests/integration/defs/perf/pytorch_model_config.py
- tests/integration/test_lists/qa/trt_llm_release_perf_test.yml
🧰 Additional context used
🧠 Learnings (1)
📓 Common learnings
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.
🪛 Ruff (0.12.2)
tests/integration/defs/perf/test_perf.py
1229-1229: Comparison to None should be cond is not None
Replace with cond is not None
(E711)
🔇 Additional comments (4)
tests/integration/defs/perf/test_perf.py (4)
74-74: LGTM! Model path update aligns with new organization.The addition of the "nvidia/" prefix to the FP8 model path is consistent with the model configuration updates mentioned in the PR summary.
324-350: LGTM! Parameter addition to constructor is correct.The
kv_cache_free_gpu_mem_fractionparameter is properly added to the constructor with an appropriate default value of 0.9. The previous duplicate definition issue appears to have been resolved.
373-374: LGTM! Instance variable assignment is correct.The
kv_cache_free_gpu_mem_fractionparameter is properly assigned to the instance variable. The previous duplicate assignment issue appears to have been resolved.
1228-1235: LGTM! Benchmark command integration is correct.The
kv_cache_free_gpu_mem_fractionparameter is properly integrated into the trtllm-bench command, completing the end-to-end implementation of this new configuration option.
Signed-off-by: ruodil <[email protected]>
…ma4 rcca cases (NVIDIA#6430) Signed-off-by: ruodil <[email protected]>
Signed-off-by: ruodil <[email protected]>
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Signed-off-by: ruodil <[email protected]>
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@ruodil , please close and merge to |
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