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[CPU] fix no attribute 'can_fuse_mlp_allreduce' error (#8010)

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Chunyuan WU
2025-07-14 16:32:43 +08:00
committed by GitHub
parent a562c8a35c
commit 07452cbe8e
1 changed files with 5 additions and 3 deletions
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8
python/sglang/srt/models/deepseek_v2.py
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@@ -462,7 +462,7 @@ class DeepseekV2MoE(nn.Module):
if hasattr(self, "shared_experts") and use_intel_amx_backend( if hasattr(self, "shared_experts") and use_intel_amx_backend(
self.shared_experts.gate_up_proj self.shared_experts.gate_up_proj
): ):
return self.forward_cpu(hidden_states) return self.forward_cpu(hidden_states, can_fuse_mlp_allreduce)
shared_output = self._forward_shared_experts(hidden_states) shared_output = self._forward_shared_experts(hidden_states)
# router_logits: (num_tokens, n_experts) # router_logits: (num_tokens, n_experts)
@@ -479,7 +479,9 @@ class DeepseekV2MoE(nn.Module):
final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states) final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
return final_hidden_states return final_hidden_states
def forward_cpu(self, hidden_states: torch.Tensor) -> torch.Tensor: def forward_cpu(
self, hidden_states: torch.Tensor, can_fuse_mlp_allreduce: bool = False
) -> torch.Tensor:
# router_logits: (num_tokens, n_experts) # router_logits: (num_tokens, n_experts)
router_logits = self.gate(hidden_states) router_logits = self.gate(hidden_states)
fused_experts_out = self.experts( fused_experts_out = self.experts(
@@ -528,7 +530,7 @@ class DeepseekV2MoE(nn.Module):
None, # a2_scale None, # a2_scale
True, # is_vnni True, # is_vnni
) )
if self.tp_size > 1 and not self.can_fuse_mlp_allreduce: if self.tp_size > 1 and not can_fuse_mlp_allreduce:
final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states) final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
return final_hidden_states return final_hidden_states