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[V1][PP] Fix memory profiling in PP (#13315)

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Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
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Woosuk Kwon 2025-02-14 20:17:25 -08:00 committed by GitHub
parent 6a854c7a2b
commit 0c73026844
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1 changed files with 6 additions and 5 deletions
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vllm/v1/worker/gpu_model_runner.py
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@ -1158,11 +1158,12 @@ class GPUModelRunner(LoRAModelRunnerMixin):
# Trigger compilation for general shape. # Trigger compilation for general shape.
hidden_states = self._dummy_run(self.max_num_tokens, hidden_states = self._dummy_run(self.max_num_tokens,
dummy_kv_caches) dummy_kv_caches)
if not get_pp_group().is_last_rank: if get_pp_group().is_last_rank:
return hidden_states
hidden_states = hidden_states[logit_indices] hidden_states = hidden_states[logit_indices]
logits = self.model.compute_logits(hidden_states, None) logits = self.model.compute_logits(hidden_states, None)
# TODO(woosuk): Consider the memory usage of the sampler. # TODO(woosuk): Consider the memory usage of the sampler.
else:
logits = None
torch.cuda.synchronize() torch.cuda.synchronize()
del hidden_states, logits del hidden_states, logits
self.encoder_cache.clear() self.encoder_cache.clear()