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[Perf] Dont create unnecessary pooling params #22876

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Merged
merged 1 commit into from
Aug 14, 2025
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[Perf] Dont create unnecessary pooling params #22876

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6 changes: 3 additions & 3 deletions vllm/v1/worker/gpu_model_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -341,13 +341,13 @@ def _init_model_kwargs(self, num_tokens: int):
model_kwargs = dict[str, Any]()
num_reqs = self.input_batch.num_reqs

pooling_params = self.input_batch.pooling_metadata.pooling_params

num_pooling_reqs = len(pooling_params)
num_pooling_reqs = len(self.input_batch.pooling_params)

if num_pooling_reqs == 0:
return model_kwargs

pooling_params = self.input_batch.pooling_metadata.pooling_params

assert num_pooling_reqs == num_reqs
Comment on lines +344 to 351
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high

While the optimization is correct, this implementation introduces a potential for future bugs. num_pooling_reqs is derived from self.input_batch.pooling_params, but the pooling_params variable that is used in the rest of the function is derived from self.input_batch.pooling_metadata. If the logic inside the pooling_metadata property changes in the future (e.g., to filter some requests), len(pooling_params) might no longer be equal to the originally computed num_pooling_reqs, which could lead to subtle issues.

To make the code more robust, it's better to derive num_pooling_reqs directly from the pooling_params list after it has been created. The initial check can be simplified to check if self.input_batch.pooling_params is empty.

Suggested change
num_pooling_reqs = len(self.input_batch.pooling_params)
if num_pooling_reqs == 0:
return model_kwargs
pooling_params = self.input_batch.pooling_metadata.pooling_params
assert num_pooling_reqs == num_reqs
if not self.input_batch.pooling_params:
return model_kwargs
pooling_params = self.input_batch.pooling_metadata.pooling_params
num_pooling_reqs = len(pooling_params)
assert num_pooling_reqs == num_reqs


token_type_id_requests = dict[int, Any]()
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