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Reduce logs in CLI scripts and plugin loader (#18970)

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Signed-off-by: mgoin <mgoin64@gmail.com>
This commit is contained in:
Michael Goin 2025-06-03 02:00:45 -04:00 committed by GitHub
parent 17430e3653
commit cc977286e7
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5 changed files with 19 additions and 15 deletions
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6
vllm/benchmarks/datasets.py
View File

@ -328,9 +328,9 @@ class RandomDataset(BenchmarkDataset):
output_high = int(output_len * (1 + range_ratio)) output_high = int(output_len * (1 + range_ratio))
# Add logging for debugging # Add logging for debugging
logger.info("Sampling input_len from [%s, %s]", input_low, input_high) logger.info(
logger.info("Sampling output_len from [%s, %s]", output_low, "Sampling input_len from [%s, %s] and output_len from [%s, %s]",
output_high) input_low, input_high, output_low, output_high)
input_lens = np.random.randint(input_low, input_lens = np.random.randint(input_low,
input_high + 1, input_high + 1,

2
vllm/benchmarks/latency.py
View File

@ -78,7 +78,6 @@ def add_cli_args(parser: argparse.ArgumentParser):
def main(args: argparse.Namespace): def main(args: argparse.Namespace):
print(args)
if args.profile and not envs.VLLM_TORCH_PROFILER_DIR: if args.profile and not envs.VLLM_TORCH_PROFILER_DIR:
raise OSError( raise OSError(
"The environment variable 'VLLM_TORCH_PROFILER_DIR' is not set. " "The environment variable 'VLLM_TORCH_PROFILER_DIR' is not set. "
@ -101,7 +100,6 @@ def main(args: argparse.Namespace):
max_tokens=args.output_len, max_tokens=args.output_len,
detokenize=not args.disable_detokenize, detokenize=not args.disable_detokenize,
) )
print(sampling_params)
dummy_prompt_token_ids = np.random.randint(10000, dummy_prompt_token_ids = np.random.randint(10000,
size=(args.batch_size, size=(args.batch_size,
args.input_len)) args.input_len))

1
vllm/benchmarks/throughput.py
View File

@ -527,7 +527,6 @@ def main(args: argparse.Namespace):
validate_args(args) validate_args(args)
if args.seed is None: if args.seed is None:
args.seed = 0 args.seed = 0
print(args)
random.seed(args.seed) random.seed(args.seed)
# Sample the requests. # Sample the requests.
tokenizer = AutoTokenizer.from_pretrained( tokenizer = AutoTokenizer.from_pretrained(

6
vllm/compilation/backends.py
View File

@ -31,13 +31,13 @@ def make_compiler(compilation_config: CompilationConfig) -> CompilerInterface:
if compilation_config.use_inductor: if compilation_config.use_inductor:
if envs.VLLM_USE_STANDALONE_COMPILE and is_torch_equal_or_newer( if envs.VLLM_USE_STANDALONE_COMPILE and is_torch_equal_or_newer(
"2.8.0"): "2.8.0"):
logger.info("Using InductorStandaloneAdaptor") logger.debug("Using InductorStandaloneAdaptor")
return InductorStandaloneAdaptor() return InductorStandaloneAdaptor()
else: else:
logger.info("Using InductorAdaptor") logger.debug("Using InductorAdaptor")
return InductorAdaptor() return InductorAdaptor()
else: else:
logger.info("Using EagerAdaptor") logger.debug("Using EagerAdaptor")
return EagerAdaptor() return EagerAdaptor()

19
vllm/plugins/__init__.py
View File

@ -10,6 +10,8 @@ import vllm.envs as envs
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
DEFAULT_PLUGINS_GROUP = 'vllm.general_plugins'
# make sure one process only loads plugins once # make sure one process only loads plugins once
plugins_loaded = False plugins_loaded = False
@ -28,19 +30,24 @@ def load_plugins_by_group(group: str) -> dict[str, Callable[[], Any]]:
logger.debug("No plugins for group %s found.", group) logger.debug("No plugins for group %s found.", group)
return {} return {}
logger.info("Available plugins for group %s:", group) # Check if the only discovered plugin is the default one
is_default_group = (group == DEFAULT_PLUGINS_GROUP)
# Use INFO for non-default groups and DEBUG for the default group
log_level = logger.debug if is_default_group else logger.info
log_level("Available plugins for group %s:", group)
for plugin in discovered_plugins: for plugin in discovered_plugins:
logger.info("- %s -> %s", plugin.name, plugin.value) log_level("- %s -> %s", plugin.name, plugin.value)
if allowed_plugins is None: if allowed_plugins is None:
logger.info("All plugins in this group will be loaded. " log_level("All plugins in this group will be loaded. "
"Set `VLLM_PLUGINS` to control which plugins to load.") "Set `VLLM_PLUGINS` to control which plugins to load.")
plugins = dict[str, Callable[[], Any]]() plugins = dict[str, Callable[[], Any]]()
for plugin in discovered_plugins: for plugin in discovered_plugins:
if allowed_plugins is None or plugin.name in allowed_plugins: if allowed_plugins is None or plugin.name in allowed_plugins:
if allowed_plugins is not None: if allowed_plugins is not None:
logger.info("Loading plugin %s", plugin.name) log_level("Loading plugin %s", plugin.name)
try: try:
func = plugin.load() func = plugin.load()
@ -80,7 +87,7 @@ def load_general_plugins():
# see https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_HPU_Graphs.html # noqa: E501 # see https://docs.habana.ai/en/latest/PyTorch/Inference_on_PyTorch/Inference_Using_HPU_Graphs.html # noqa: E501
os.environ['PT_HPU_ENABLE_LAZY_COLLECTIVES'] = 'true' os.environ['PT_HPU_ENABLE_LAZY_COLLECTIVES'] = 'true'
plugins = load_plugins_by_group(group='vllm.general_plugins') plugins = load_plugins_by_group(group=DEFAULT_PLUGINS_GROUP)
# general plugins, we only need to execute the loaded functions # general plugins, we only need to execute the loaded functions
for func in plugins.values(): for func in plugins.values():
func() func()