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[Minor] Small pooler output processing optimization #31667

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Merged
vllm-bot merged 1 commit into from
Jan 5, 2026
Merged

[Minor] Small pooler output processing optimization #31667

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19 changes: 8 additions & 11 deletions vllm/v1/worker/gpu_model_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -263,7 +263,6 @@ def __init__(
async_output_copy_stream: torch.cuda.Stream,
):
self._model_runner_output = model_runner_output
self._finished_mask = finished_mask

# Event on the copy stream so we can synchronize the non-blocking copy.
self.async_copy_ready_event = torch.Event()
Expand All @@ -276,11 +275,15 @@ def __init__(
default_stream = torch.cuda.current_stream()
with torch.cuda.stream(async_output_copy_stream):
async_output_copy_stream.wait_stream(default_stream)
self._raw_pooler_output_cpu = json_map_leaves(
raw_pooler_output_cpu = json_map_leaves(
lambda x: None if x is None else x.to("cpu", non_blocking=True),
self._raw_pooler_output,
)
self.async_copy_ready_event.record()
self._model_runner_output.pooler_output = [
out if include else None
for out, include in zip(raw_pooler_output_cpu, finished_mask)
]

def get_output(self) -> ModelRunnerOutput:
"""Copy the device tensors to the host and return a ModelRunnerOutput.
Expand All @@ -290,11 +293,6 @@ def get_output(self) -> ModelRunnerOutput:

# Release the device tensors once the copy has completed.
del self._raw_pooler_output

self._model_runner_output.pooler_output = [
out if include else None
for out, include in zip(self._raw_pooler_output_cpu, self._finished_mask)
]
return self._model_runner_output


Expand Down Expand Up @@ -2537,8 +2535,7 @@ def _pool(

model = cast(VllmModelForPooling, self.model)
raw_pooler_output: PoolerOutput = model.pooler(
hidden_states=hidden_states,
pooling_metadata=pooling_metadata,
hidden_states=hidden_states, pooling_metadata=pooling_metadata
)

finished_mask = [
Expand Down Expand Up @@ -2568,12 +2565,12 @@ def _pool(
lambda x: None if x is None else x.to("cpu", non_blocking=True),
raw_pooler_output,
)
self._sync_device()

model_runner_output.pooler_output = [
out if include else None
for out, include in zip(raw_pooler_output, finished_mask)
]
self._sync_device()

return model_runner_output

def _pad_for_sequence_parallelism(self, num_scheduled_tokens: int) -> int:
Expand Down
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