fix bug

Signed-off-by: xin3he <[email protected]>

Author: xin3he

neural_compressor/common/base_config.py

@@ -198,10 +198,16 @@ def local_config(self):
     def local_config(self, config):
         self._local_config = config
 
-    def set_local(self, operator_name: Union[str, Callable], config: BaseConfig) -> BaseConfig:
-        if operator_name in self.local_config:
-            logger.warning("The configuration for %s has already been set, update it.", operator_name)
-        self.local_config[operator_name] = config
+    def set_local(self, operator_name_or_list: Union[List, str, Callable], config: BaseConfig) -> BaseConfig:
+        if hasattr(operator_name_or_list, "__iter__"):
+            for operator_name in operator_name_or_list:
+                if operator_name in self.local_config:
+                    logger.warning("The configuration for %s has already been set, update it.", operator_name)
+                self.local_config[operator_name] = config
+        else:
+            if operator_name_or_list in self.local_config:
+                logger.warning("The configuration for %s has already been set, update it.", operator_name)
+            self.local_config[operator_name_or_list] = config
         return self
 
     def to_dict(self):

neural_compressor/torch/quantization/config.py

@@ -169,10 +169,6 @@ def __init__(
         self.double_quant_group_size = double_quant_group_size
         self.quant_lm_head = quant_lm_head
         self._post_init()  # initialize global & local configuration
-        if not self.quant_lm_head:
-            # use .* for re.match
-            usual_lm_head_names = [".*lm_head", ".*output_layer", ".*embed_out"]
-            self.set_local(usual_lm_head_names, RTNConfig(dtype="fp32"))
 
     @classmethod
     def register_supported_configs(cls) -> List[OperatorConfig]:
@@ -209,6 +205,15 @@ def register_supported_configs(cls) -> List[OperatorConfig]:
         supported_configs.append(OperatorConfig(config=linear_rtn_config, operators=operators))
         cls.supported_configs = supported_configs
 
+    def to_config_mapping(
+        self, config_list: List[BaseConfig] = None, model_info: List[Tuple[str, str]] = None
+    ) -> OrderedDictType[Union[str, str], OrderedDictType[str, BaseConfig]]:
+        if not self.quant_lm_head:
+            usual_lm_head_names = [".*lm_head", ".*output_layer", ".*embed_out"]
+            self.set_local(usual_lm_head_names, RTNConfig(dtype="fp32"))
+        config_mapping = super().to_config_mapping(config_list, model_info)
+        return config_mapping
+
     @staticmethod
     def get_model_info(model: torch.nn.Module) -> List[Tuple[str, Callable]]:
         filter_result = []

neural_compressor/torch/utils/utility.py

@@ -225,7 +225,6 @@ def dump_model_op_stats(mode, tune_cfg):
     for op, config in tune_cfg.items():
         op_type = op[1]
         config = config.to_dict()
-        # import pdb; pdb.set_trace()
         if not config["dtype"] == "fp32":
             num_bits = config["bits"]
             group_size = config["group_size"]