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[Bugfix] Fix for 24530. Fix naive all2all shared expert overlap. #24538

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Merged
merged 1 commit into from
Sep 10, 2025
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[Bugfix] Fix for 24530. Fix naive all2all shared expert overlap. #24538

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15 changes: 9 additions & 6 deletions vllm/model_executor/layers/fused_moe/layer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1755,9 +1755,6 @@ def forward_impl(
self.dp_size > 1
and not self.moe_parallel_config.use_deepep_ht_kernels
and not self.moe_config.use_flashinfer_cutlass_kernels)
if do_naive_dispatch_combine:
hidden_states, router_logits = get_ep_group().dispatch(
hidden_states, router_logits)

# If there are shared experts but we are not using a modular kernel, the
# shared experts must be called here
Expand All @@ -1768,6 +1765,10 @@ def forward_impl(
else:
shared_output = None

if do_naive_dispatch_combine:
hidden_states, router_logits = get_ep_group().dispatch(
hidden_states, router_logits)

# Matrix multiply.
final_hidden_states = self.quant_method.apply(
layer=self,
Expand Down Expand Up @@ -1800,8 +1801,9 @@ def forward_impl(
final_hidden_states,
)

def reduce_output(states: torch.Tensor) -> torch.Tensor:
if do_naive_dispatch_combine:
def reduce_output(states: torch.Tensor,
do_combine: bool = True) -> torch.Tensor:
if do_naive_dispatch_combine and do_combine:
states = get_ep_group().combine(states)

if self.reduce_results and (self.tp_size > 1 or self.ep_size > 1):
Expand All @@ -1810,10 +1812,11 @@ def reduce_output(states: torch.Tensor) -> torch.Tensor:
return states

if self.shared_experts is None:
assert not isinstance(final_hidden_states, tuple)
return reduce_output(final_hidden_states)
else:
return (
reduce_output(final_hidden_states[0]),
reduce_output(final_hidden_states[0], do_combine=False),
reduce_output(final_hidden_states[1]),
)

Expand Down