[BugFix] fix RMSNorm rms_norm_esp (#2797)

* fix rms

* add vl

* fix

* add vl

* fix

* fix

fastdeploy/config.py

@@ -84,6 +84,7 @@ class ModelConfig(PretrainedConfig):
         head_dim: Optional[int] = None,
         tie_word_embeddings: bool = False,
         is_quantized: bool = False,
+        rms_norm_eps: float = 1e-5,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -123,6 +124,7 @@ class ModelConfig(PretrainedConfig):
         self.dtype = dtype
         self.tie_word_embeddings = tie_word_embeddings
         self.is_quantized = is_quantized
+        self.rms_norm_eps = rms_norm_eps
 
 
 @dataclass

fastdeploy/model_executor/models/ernie4_5_moe.py

@@ -288,14 +288,14 @@ class Ernie4_5_DecoderLayer(nn.Layer):
         self.input_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.input_layernorm",
         )
 
         self.post_attention_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.post_attention_layernorm",
         )
 
@@ -366,7 +366,7 @@ class Ernie4_5_Model(nn.Layer):
         self.norm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{fd_config.model_config.prefix_name}.norm",
         )
 

fastdeploy/model_executor/models/ernie4_5_mtp.py

@@ -275,14 +275,14 @@ class Ernie4_5_MTPModel(nn.Layer):
         self.enorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix="ernie.mtp_emb_norm.0",
         )
 
         self.hnorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix="ernie.mtp_hidden_norm.0",
         )
 

fastdeploy/model_executor/models/ernie4_5_vl/ernie4_5_vl_moe.py

@@ -273,14 +273,14 @@ class Ernie4_5_VLDecoderLayer(nn.Layer):
         self.input_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.input_layernorm",
         )
 
         self.post_attention_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.post_attention_layernorm",
         )
 
@@ -358,7 +358,7 @@ class Ernie4_5_VLModel(nn.Layer):
         self.norm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{fd_config.model_config.prefix_name}.norm",
         )
 

fastdeploy/model_executor/models/qwen2.py

@@ -161,14 +161,14 @@ class Qwen2DecoderLayer(nn.Layer):
         self.input_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-6,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.input_layernorm",
         )
 
         self.post_attention_layernorm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-6,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{prefix}.post_attention_layernorm",
         )
 
@@ -248,7 +248,7 @@ class Qwen2Model(nn.Layer):
         self.norm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-5,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{fd_config.model_config.prefix_name}.norm",
         )
 

fastdeploy/model_executor/models/qwen3.py

@@ -79,12 +79,12 @@ class Qwen3Attention(nn.Layer):
 
         self.q_norm = RMSNorm(fd_config=fd_config,
                               hidden_size=fd_config.model_config.head_dim,
-                              eps=1e-6,
+                              eps=fd_config.model_config.rms_norm_eps,
                               prefix=f"{prefix}.q_norm",
                               begin_norm_axis=2)
         self.k_norm = RMSNorm(fd_config=fd_config,
                               hidden_size=fd_config.model_config.head_dim,
-                              eps=1e-6,
+                              eps=fd_config.model_config.rms_norm_eps,
                               prefix=f"{prefix}.k_norm",
                               begin_norm_axis=2)
 
@@ -183,7 +183,7 @@ class Qwen3Model(nn.Layer):
         self.norm = RMSNorm(
             fd_config,
             hidden_size=fd_config.model_config.hidden_size,
-            eps=1e-6,
+            eps=fd_config.model_config.rms_norm_eps,
             prefix=f"{fd_config.model_config.prefix_name}.norm",
         )
 

fastdeploy/model_executor/models/qwen3moe.py

@@ -121,12 +121,12 @@ class Qwen3Attention(nn.Layer):
 
         self.q_norm = RMSNorm(fd_config,
                               hidden_size=self.head_dim,
-                              eps=1e-6,
+                              eps=fd_config.model_config.rms_norm_eps,
                               prefix=f"{prefix}.q_norm",
                               begin_norm_axis=2)
         self.k_norm = RMSNorm(fd_config,
                               hidden_size=self.head_dim,
-                              eps=1e-6,
+                              eps=fd_config.model_config.rms_norm_eps,
                               prefix=f"{prefix}.k_norm",
                               begin_norm_axis=2)
 

fastdeploy/worker/worker_process.py

@@ -594,7 +594,6 @@ def initialize_fd_config(config_or_args) -> FDConfig:
     model_config_dict, _ = ModelConfig.get_config_dict(config_or_args.model_name_or_path)
 
 
-
     # Handle MoE related configs
     if 'num_experts' in model_config_dict:
         model_config_dict['moe_num_experts'] = model_config_dict.pop('num_experts')