reformat

Author: shihaobai

lightllm/common/basemodel/layer_weights/meta_weights/fused_moe_weight_ep.py

@@ -23,7 +23,7 @@ def __init__(
         data_type: torch.dtype,
         network_config: Dict[str, Any],
         layer_num: int,
-        quant_cfg = None,
+        quant_cfg=None,
     ) -> None:
         super().__init__(
             gate_proj_name,

lightllm/common/basemodel/layer_weights/meta_weights/fused_moe_weight_tp.py

@@ -26,7 +26,6 @@ def __init__(
         quant_cfg: Quantcfg = None,
     ) -> None:
         super().__init__()
-        
         self.quant_method = quant_cfg.get_quant_method(layer_num, "fused_moe")
         self.quantized_weight = quant_cfg.quantized_weight
         if self.quant_method is not None:

lightllm/common/quantization/__init__.py

@@ -64,4 +64,4 @@ def get_quant_type(self, layer_num, name):
 
     def get_quant_method(self, layer_num, name):
         quant_type = self.get_quant_type(layer_num, name)
-        return QUANTMETHODS.get(quant_type)
+        return QUANTMETHODS.get(quant_type)

lightllm/models/deepseek2/model.py

@@ -114,12 +114,8 @@ def _init_weights(self):
         return
 
     def _init_infer_layer(self):
-        self.pre_infer = self.pre_layer_infer_class(
-            network_config=self.config, mode=self.mode
-        )
-        self.post_infer = self.post_layer_infer_class(
-            network_config=self.config, mode=self.mode
-        )
+        self.pre_infer = self.pre_layer_infer_class(network_config=self.config, mode=self.mode)
+        self.post_infer = self.post_layer_infer_class(network_config=self.config, mode=self.mode)
         self.layers_infer = [
             self.transformer_layer_infer_class(
                 i,