[refactor] remove unused op_mlp (#26673)
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@@ -2114,19 +2114,6 @@ class DeepseekV2DecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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if not (
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enable_moe_dense_fully_dp()
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and (not self.is_layer_sparse)
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and hidden_states.shape[0] == 0
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):
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state.hidden_states_mlp_output = self.mlp(
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hidden_states, state.forward_batch
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)
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else:
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state.hidden_states_mlp_output = hidden_states
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def op_comm_postprocess_layer(self, state):
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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state.pop("hidden_states_mlp_output"),
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@@ -1017,19 +1017,6 @@ class Glm4MoeDecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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if not (
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enable_moe_dense_fully_dp()
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and (not self.is_layer_sparse)
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and hidden_states.shape[0] == 0
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):
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state.hidden_states_mlp_output = self.mlp(
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hidden_states, state.forward_batch
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)
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else:
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state.hidden_states_mlp_output = hidden_states
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def op_comm_postprocess_layer(self, state):
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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state.pop("hidden_states_mlp_output"),
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@@ -737,19 +737,6 @@ class Glm4MoeLiteDecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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if not (
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enable_moe_dense_fully_dp()
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and (not self.is_layer_sparse)
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and hidden_states.shape[0] == 0
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):
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state.hidden_states_mlp_output = self.mlp(
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hidden_states, state.forward_batch
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)
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else:
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state.hidden_states_mlp_output = hidden_states
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def op_comm_postprocess_layer(self, state):
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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state.pop("hidden_states_mlp_output"),
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@@ -808,10 +808,6 @@ class MiMoV2DecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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state.hidden_states_mlp_output = self.mlp(hidden_states, state.forward_batch)
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def op_comm_postprocess_layer(self, state):
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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state.pop("hidden_states_mlp_output"),
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@@ -1069,12 +1069,6 @@ class MiniMaxM2DecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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state.hidden_states_mlp_output = self.block_sparse_moe(
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hidden_states, state.forward_batch
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)
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def op_comm_postprocess_layer(self, state):
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"""Communication postprocess for layer - TBO operation"""
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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@@ -891,10 +891,6 @@ class Qwen3MoeDecoderLayer(nn.Module):
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)
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)
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def op_mlp(self, state):
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hidden_states = state.pop("hidden_states_mlp_input")
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state.hidden_states_mlp_output = self.mlp(hidden_states, state.forward_batch)
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def op_comm_postprocess_layer(self, state):
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hidden_states, residual = self.layer_communicator.postprocess_layer(
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state.pop("hidden_states_mlp_output"),
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