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[v0.11.0] [P/D] force with_prefill true after allreduce in kv producer #3835

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Merged
MengqingCao merged 3 commits into from
Oct 29, 2025
Merged

[v0.11.0] [P/D] force with_prefill true after allreduce in kv producer #3835

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94596bb
fix prefill
liziyu179 Oct 28, 2025
2a821ff
fix layerwise connector
liziyu179 Oct 28, 2025
f7b64f8
fix mooncake layerwise connector
liziyu179 Oct 29, 2025
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2 changes: 1 addition & 1 deletion vllm_ascend/distributed/mooncake_layerwise_connector.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1145,7 +1145,7 @@ def save_kv_layer(self, layer_name: str, kv_layer: Tuple[torch.Tensor,
connector_metadata: MooncakeLayerwiseConnectorMetadata,
**kwargs) -> None:
"""MooncakeLayerwiseConnector does not save explicitly."""
if self.kv_role == 'kv_producer':
if self.kv_role == 'kv_producer' and connector_metadata.request.keys():
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@gemini-code-assist gemini-code-assist bot Oct 28, 2025

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critical

There's a typo in the attribute name. The MooncakeLayerwiseConnectorMetadata object has an attribute requests (plural), not request. This will raise an AttributeError at runtime.

Additionally, to check if the dictionary is not empty, you can use the dictionary directly in a boolean context, which is more Pythonic.

Suggested change
if self.kv_role == 'kv_producer' and connector_metadata.request.keys():
if self.kv_role == 'kv_producer' and connector_metadata.requests:

if self.pd_head_ratio != 1:
if self.current_layer != 0:
self.completion_event.wait()
Expand Down
8 changes: 4 additions & 4 deletions vllm_ascend/worker/model_runner_v1.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2370,6 +2370,10 @@ def _dummy_run(
tp_size = self.vllm_config.parallel_config.tensor_parallel_size
num_tokens = math.ceil(num_tokens / tp_size) * tp_size

# Force dummy run on prefill stage when this node is deemed as kv producer.
if self.is_kv_producer and not self.is_kv_consumer:
with_prefill = True

# Padding for DP
(num_tokens, num_tokens_across_dp, with_prefill,
_) = self._sync_metadata_across_dp(num_tokens, with_prefill, False)
Expand Down Expand Up @@ -2417,10 +2421,6 @@ def _dummy_run(
num_scheduled_tokens = np.array(num_scheduled_tokens_list,
dtype=np.int32)

# Force dummy run on prefill stage when this node is deemed as kv producer.
if self.is_kv_producer and not self.is_kv_consumer:
with_prefill = True

if not self.in_profile_run and self.dynamic_eplb:
self.eplb_updator.forward_before()

Expand Down