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Skip MM Encoder for non-first PP ranks (#24387)

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Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
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Woosuk Kwon 2025-09-07 09:38:35 -07:00 committed by GitHub
parent 0661cb9df3
commit 2e5d21378d
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1 changed files with 1 additions and 4 deletions
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vllm/v1/worker/gpu_model_runner.py
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@ -1620,14 +1620,11 @@ class GPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
# _prepare_inputs may reorder the batch, so we must gather multi # _prepare_inputs may reorder the batch, so we must gather multi
# modal outputs after that to ensure the correct order # modal outputs after that to ensure the correct order
if self.supports_mm_inputs: if self.supports_mm_inputs and get_pp_group().is_first_rank:
# Run the multimodal encoder if any. # Run the multimodal encoder if any.
self._execute_mm_encoder(scheduler_output) self._execute_mm_encoder(scheduler_output)
mm_embeds = self._gather_mm_embeddings(scheduler_output) mm_embeds = self._gather_mm_embeddings(scheduler_output)
else:
mm_embeds = []
if self.supports_mm_inputs and get_pp_group().is_first_rank:
# NOTE(woosuk): To unify token ids and soft tokens (vision # NOTE(woosuk): To unify token ids and soft tokens (vision
# embeddings), we always use embeddings (rather than token ids) # embeddings), we always use embeddings (rather than token ids)
# as input to the multimodal model, even when the input is text. # as input to the multimodal model, even when the input is text.