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qwen3_moe (#3084)

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bukejiyu
2025-08-06 14:45:27 +08:00
committed by GitHub
parent 91dc87f1c5
commit 20839abccf
30 changed files with 1361 additions and 1087 deletions
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32
fastdeploy/rl/rollout_model.py
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@@ -156,12 +156,12 @@ class Ernie4_5_MoeForCausalLMRL(Ernie4_5_MoeForCausalLM, BaseRLModel):
# Helper function to add layer mappings
def _add_layer_mappings(layer_idx: int):
# MoE specific mappings
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.gate_weight"] = (
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.gate.weight"] = (
f"{base_name}.{layer_idx}.mlp.gate.weight"
)
if self.fd_config.model_config.moe_use_aux_free:
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.gate_correction_bias"] = (
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.experts.gate_correction_bias"] = (
f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
)
@@ -169,7 +169,7 @@ class Ernie4_5_MoeForCausalLMRL(Ernie4_5_MoeForCausalLM, BaseRLModel):
for expert_idx in range(self.fd_config.model_config.moe_num_experts):
for ph in place_holders:
# up_gate_proj (up_gate_proj)
up_gate_proj_key = f"{base_name}.{layer_idx}.mlp.fused_moe.up_gate_proj_weight"
up_gate_proj_key = f"{base_name}.{layer_idx}.mlp.experts.up_gate_proj_weight"
if up_gate_proj_key not in self.infer_to_train_mapping:
self.infer_to_train_mapping[up_gate_proj_key] = []
self.infer_to_train_mapping[up_gate_proj_key].append(
@@ -177,7 +177,7 @@ class Ernie4_5_MoeForCausalLMRL(Ernie4_5_MoeForCausalLM, BaseRLModel):
)
# down_proj (down_proj)
down_proj_key = f"{base_name}.{layer_idx}.mlp.fused_moe.down_proj_weight"
down_proj_key = f"{base_name}.{layer_idx}.mlp.experts.down_proj_weight"
if down_proj_key not in self.infer_to_train_mapping:
self.infer_to_train_mapping[down_proj_key] = []
self.infer_to_train_mapping[down_proj_key].append(
@@ -230,13 +230,13 @@ class Ernie4_5_VLMoeForConditionalGenerationRL(Ernie4_5_VLMoeForConditionalGener
def _add_expert_mappings(layer_idx: int, moe_tag: str, expert_start: int):
# MoE specific mappings
gate_suffix = "" if moe_tag == "text" else "_1"
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.gate_weight"] = (
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.gate.weight"] = (
f"{base_name}.{layer_idx}.mlp.gate.weight{gate_suffix}"
)
if self.fd_config.model_config.moe_use_aux_free:
self.infer_to_train_mapping[
f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.gate_correction_bias"
f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.experts.gate_correction_bias"
] = f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
# Initialize defaultdict for expert weights
@@ -255,12 +255,12 @@ class Ernie4_5_VLMoeForConditionalGenerationRL(Ernie4_5_VLMoeForConditionalGener
expert_num_per_rank,
):
for ph in place_holders:
expert_mappings[f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.up_gate_proj_weight"].append(
f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.up_gate_proj.{ph}"
)
expert_mappings[f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.down_proj_weight"].append(
f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.down_proj.{ph}"
)
expert_mappings[
f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.experts.up_gate_proj_weight"
].append(f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.up_gate_proj.{ph}")
expert_mappings[
f"{base_name}.{layer_idx}.mlp.{moe_tag}_fused_moe.experts.down_proj_weight"
].append(f"{base_name}.{layer_idx}.mlp.experts.{expert_idx}.down_proj.{ph}")
self.infer_to_train_mapping.update(expert_mappings)
moe_layer_start_index = self.fd_config.model_config.moe_layer_start_index
@@ -375,12 +375,12 @@ class Qwen3MoeForCausalLMRL(Qwen3MoeForCausalLM, BaseRLModel):
# Helper function to add layer mappings
def _add_layer_mappings(layer_idx: int):
# MoE specific mappings
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.gate_weight"] = (
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.gate.weight"] = (
f"{base_name}.{layer_idx}.mlp.gate.weight"
)
if self.fd_config.moe_config.moe_use_aux_free:
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.gate_correction_bias"] = (
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.experts.gate_correction_bias"] = (
f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
)
@@ -388,7 +388,7 @@ class Qwen3MoeForCausalLMRL(Qwen3MoeForCausalLM, BaseRLModel):
for expert_idx in range(self.fd_config.moe_config.num_experts):
for ph in place_holders:
# up_gate_proj (up_gate_proj)
up_gate_proj_key = f"{base_name}.{layer_idx}.mlp.up_gate_proj_weight"
up_gate_proj_key = f"{base_name}.{layer_idx}.mlp.experts.up_gate_proj_weight"
if up_gate_proj_key not in self.infer_to_train_mapping:
self.infer_to_train_mapping[up_gate_proj_key] = []
self.infer_to_train_mapping[up_gate_proj_key].append(
@@ -396,7 +396,7 @@ class Qwen3MoeForCausalLMRL(Qwen3MoeForCausalLM, BaseRLModel):
)
# down_proj (down_proj)
down_proj_key = f"{base_name}.{layer_idx}.mlp.down_proj_weight"
down_proj_key = f"{base_name}.{layer_idx}.mlp.experts.down_proj_weight"
if down_proj_key not in self.infer_to_train_mapping:
self.infer_to_train_mapping[down_proj_key] = []
self.infer_to_train_mapping[down_proj_key].append(