[CPU] fix no attribute 'can_fuse_mlp_allreduce' error (#8010)
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@@ -462,7 +462,7 @@ class DeepseekV2MoE(nn.Module):
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if hasattr(self, "shared_experts") and use_intel_amx_backend(
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self.shared_experts.gate_up_proj
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):
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return self.forward_cpu(hidden_states)
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return self.forward_cpu(hidden_states, can_fuse_mlp_allreduce)
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shared_output = self._forward_shared_experts(hidden_states)
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# router_logits: (num_tokens, n_experts)
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@@ -479,7 +479,9 @@ class DeepseekV2MoE(nn.Module):
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final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
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return final_hidden_states
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def forward_cpu(self, hidden_states: torch.Tensor) -> torch.Tensor:
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def forward_cpu(
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self, hidden_states: torch.Tensor, can_fuse_mlp_allreduce: bool = False
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) -> torch.Tensor:
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# router_logits: (num_tokens, n_experts)
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router_logits = self.gate(hidden_states)
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fused_experts_out = self.experts(
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@@ -528,7 +530,7 @@ class DeepseekV2MoE(nn.Module):
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None, # a2_scale
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True, # is_vnni
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)
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if self.tp_size > 1 and not self.can_fuse_mlp_allreduce:
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if self.tp_size > 1 and not can_fuse_mlp_allreduce:
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final_hidden_states = tensor_model_parallel_all_reduce(final_hidden_states)
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return final_hidden_states
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