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update flake8 version to support pre-commit in python3.12 (#3000)

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* update flake8 version to support pre-commit in python3.12

* polish code
This commit is contained in:
Zero Rains
2025-07-24 16:43:31 +08:00
committed by GitHub
parent 5151bc92c8
commit 0fb37ab7e4
30 changed files with 324 additions and 275 deletions
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44
fastdeploy/rl/rollout_model.py
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@@ -153,14 +153,14 @@ 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"
] = f"{base_name}.{layer_idx}.mlp.gate.weight"
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.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"
] = f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.gate_correction_bias"] = (
f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
)
# MoE experts mappings
for expert_idx in range(self.fd_config.model_config.moe_num_experts):
@@ -184,7 +184,8 @@ class Ernie4_5_MoeForCausalLMRL(Ernie4_5_MoeForCausalLM, BaseRLModel):
assert isinstance(self.fd_config.model_config.moe_layer_start_index, int)
# Process MoE layers
for layer_idx in range(
self.fd_config.model_config.moe_layer_start_index, self.fd_config.model_config.num_hidden_layers
self.fd_config.model_config.moe_layer_start_index,
self.fd_config.model_config.num_hidden_layers,
):
_add_layer_mappings(layer_idx)
@@ -226,9 +227,9 @@ 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"
] = f"{base_name}.{layer_idx}.mlp.gate.weight{gate_suffix}"
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[
@@ -245,7 +246,10 @@ class Ernie4_5_VLMoeForConditionalGenerationRL(Ernie4_5_VLMoeForConditionalGener
expert_mappings = defaultdict(list)
for expert_idx in _generate_ranges(
expert_start, total_moe_num, expert_num_per_rank * 2, expert_num_per_rank
expert_start,
total_moe_num,
expert_num_per_rank * 2,
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(
@@ -323,9 +327,9 @@ class Qwen2ForCausalLMRL(Qwen2ForCausalLM, BaseRLModel):
def _add_layer_mappings(layer_idx):
# FFN mappings
for ph in place_holders:
self.infer_to_train_mapping[
f"{base_name}.{layer_idx}.mlp.up_gate_proj.{ph}"
] = f"{base_name}.{layer_idx}.mlp.gate_up_fused_proj.{ph}"
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.up_gate_proj.{ph}"] = (
f"{base_name}.{layer_idx}.mlp.gate_up_fused_proj.{ph}"
)
for layer_idx in range(self.fd_config.model_config.num_hidden_layers):
_add_layer_mappings(layer_idx)
@@ -368,14 +372,14 @@ 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"
] = 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"
] = f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
self.infer_to_train_mapping[f"{base_name}.{layer_idx}.mlp.fused_moe.gate_correction_bias"] = (
f"{base_name}.{layer_idx}.mlp.moe_statics.e_score_correction_bias"
)
# MoE experts mappings
for expert_idx in range(self.fd_config.moe_config.num_experts):