support part tuner replace_key False (modelscope#2438)

swift/tuners/adapter.py

@@ -111,7 +111,7 @@ def _feed_forward_chunk(self, attention_output):
                 setattr(module, f'adapter_{adapter_name}', adapter_module)
                 logger.info(f'Adapter modules(module_key): {module_key}.adapter_{adapter_name}')
 
-        def state_dict_callback(state_dict, adapter_name: str):
+        def state_dict_callback(state_dict, adapter_name: str, **kwargs):
             return {key: value for key, value in state_dict.items() if f'adapter_{adapter_name}' in key}
 
         def mark_trainable_callback(model):

swift/tuners/llamapro.py

@@ -77,7 +77,7 @@ def prepare_model(model: nn.Module, config: LLaMAProConfig, adapter_name: str) -
         model.config.num_hidden_layers = len(new_module_list)
         LLaMAPro._set_module_list(config, model, new_module_list)
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             model_key_mapping = LLaMAPro.get_model_key_mapping(config.model_type, config)
             new_module_list = [model_key_mapping.module_list + f'.{i}' for i in new_module_idx]
             return {

swift/tuners/longlora/longlora.py

@@ -51,7 +51,7 @@ def prepare_model(model: nn.Module, config: LongLoRAConfig, adapter_name: str):
         """Prepare a model with `LongLoRAConfig`"""
         LoraModel(model, config, adapter_name)
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             _state_dict = lora_state_dict(state_dict, adapter_name, config.bias)
             for name, value in state_dict.items():
                 if isinstance(config.embedder_and_normalizer, str):

swift/tuners/lora.py

@@ -81,7 +81,7 @@ def prepare_model(model: nn.Module, config: LoRAConfig, adapter_name: str):
                 config.group_size = getattr(auto_gptq_config, 'group_size', None)
         LoraModel(model, config, adapter_name)
 
-        def state_dict_callback(state_dict, adapter_name, cfg=None):
+        def state_dict_callback(state_dict, adapter_name, cfg=None, **kwargs):
             return lora_state_dict(state_dict, adapter_name, cfg.bias if cfg else config.bias)
 
         def mark_trainable_callback(model, cfg=None):

swift/tuners/neftune.py

@@ -49,7 +49,7 @@ def neftune_hook(module, args, output):
                 sub_module.register_forward_hook(neftune_hook)
                 sub_module.nef_activated = True
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             return state_dict
 
         def mark_trainable_callback(model):

swift/tuners/part.py

@@ -70,11 +70,14 @@ def _forward(self, *args, **kwargs):
                 setattr(module, f'_part_{adapter_name}', new_module)
                 new_module.requires_grad_(True)
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             new_state_dict = {}
             for key, value in state_dict.items():
                 if f'_part_{adapter_name}.' in key:
-                    new_key = key.replace(f'_part_{adapter_name}.', '').replace('base_layer.', '')
+                    if kwargs.get('replace_key', True):
+                        new_key = key.replace(f'_part_{adapter_name}.', '').replace('base_layer.', '')
+                    else:
+                        new_key = key
                     new_state_dict[new_key] = value
 
             return new_state_dict
@@ -90,11 +93,14 @@ def load_state_dict_callback(model: nn.Module, adapter_name: str, state_dict: Di
                     for param_name in state_dict:
                         if param_name.startswith(name):
                             end = param_name[len(name):]
-                            if hasattr(module, 'base_layer'):
-                                new_state_dict[name + f'.base_layer._part_{adapter_name}'
-                                               + end] = state_dict[param_name]
+                            if '_part_' not in param_name:
+                                if hasattr(module, 'base_layer'):
+                                    new_state_dict[name + f'.base_layer._part_{adapter_name}'
+                                                   + end] = state_dict[param_name]
+                                else:
+                                    new_state_dict[name + f'._part_{adapter_name}' + end] = state_dict[param_name]
                             else:
-                                new_state_dict[name + f'._part_{adapter_name}' + end] = state_dict[param_name]
+                                new_state_dict[param_name] = state_dict[param_name]
             return new_state_dict
 
         return SwiftOutput(

swift/tuners/prompt.py

@@ -126,7 +126,7 @@ def _forward(self, *args, **kwargs):
                 logger.info(f'Prompt modules(module_key): {module_key}.prompt_{adapter_name}')
                 match_module_keys.append(module_key)
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             return {key: value for key, value in state_dict.items() if f'prompt_{adapter_name}' in key}
 
         def mark_trainable_callback(model):

swift/tuners/restuning.py

@@ -233,7 +233,7 @@ def _forward_restuning(self, origin_arg):
         if target_module_ins is None:
             raise Exception('Cannot match target modules')
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             return {key: value for key, value in state_dict.items() if f'restuning_{adapter_name}' in key}
 
         def mark_trainable_callback(model):

swift/tuners/rome/rome.py

@@ -76,7 +76,7 @@ def prepare_model(model: nn.Module, config: RomeConfig, adapter_name: str):
             hparams = ROMEHyperParams.from_name(config.model_type)
             modified_keys = apply_rome_to_model(model, config.tokenizer, config.knowledge, hparams, config.batch_first)
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             return {key: value for key, value in state_dict.items() if key in modified_keys}
 
         def mark_trainable_callback(model):

swift/tuners/scetuning/scetuning.py

@@ -176,7 +176,7 @@ def _forward_decoder_mode(self, *args, **kwargs):
             if len(hint_module_ins_list) > 0:
                 setattr(t_module, 'hint', hint_module_ins_list[tuner_id])
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             state_dict_new = {key: value for key, value in state_dict.items() if f'scetuner_{adapter_name}' in key}
             return state_dict_new
 

swift/tuners/side.py

@@ -107,7 +107,7 @@ def forward_seq(self, input, *args, **kwargs):
                 setattr(tgt_module, f'side_{adapter_name}', side_module)
                 logger.info(f'Side modules(module_key): {module_key}.side_{adapter_name}')
 
-        def state_dict_callback(state_dict, adapter_name):
+        def state_dict_callback(state_dict, adapter_name, **kwargs):
             return {key: value for key, value in state_dict.items() if f'side_{adapter_name}' in key}
 
         def mark_trainable_callback(model):