A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 5, 21:00 UTC
[Misc]: clean up non-core lint issues (#37049)
Signed-off-by: whyiug <whyiug@hotmail.com>
whyiug committed
Mar 28, 2026 at 22:28 UTC
58c959a767c1c1883d6be8ba12e752902afb9fac
2 files changed
+3
-9
benchmarks/attention_benchmarks/benchmark.py
+2
-8
@@ -546,10 +546,7 @@ def main():
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args.prefill_backends = yaml_config.get("prefill_backends", None)
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# Check for special modes
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- if "mode" in yaml_config:
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- args.mode = yaml_config["mode"]
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- else:
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- args.mode = None
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+ args.mode = yaml_config.get("mode", None)
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# Batch specs and sizes
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# Support both explicit batch_specs and generated batch_spec_ranges
@@ -572,10 +569,7 @@ def main():
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elif "batch_specs" in yaml_config:
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args.batch_specs = yaml_config["batch_specs"]
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- if "batch_sizes" in yaml_config:
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- args.batch_sizes = yaml_config["batch_sizes"]
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- else:
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- args.batch_sizes = None
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+ args.batch_sizes = yaml_config.get("batch_sizes", None)
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# Model config
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if "model" in yaml_config:
docs/mkdocs/hooks/generate_argparse.py
+1
-1
@@ -153,7 +153,7 @@ class MarkdownFormatter(HelpFormatter):
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heading_md = f"{self._argument_heading_prefix} {option_strings}\n\n"
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self._markdown_output.append(heading_md)
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- if action.choices or isinstance(action.metavar, (list, tuple)):
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+ if action.choices or isinstance(action.metavar, list | tuple):
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choices_iterable = action.choices or action.metavar
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choices = f"`{'`, `'.join(str(c) for c in choices_iterable)}`"
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self._markdown_output.append(f": Possible choices: {choices}\n\n")