ms-swift 书生26B合并dpo后的适配器失败

合并脚本：

CUDA_VISIBLE_DEVICES=0 swift export \
    --model_type  internvl2-26b \
    --model_id_or_path  /root/f_data_1/InternVL2-26B \
    --ckpt_dir "/root/visual_model/fine_tune/output/internvl2-26b/v1-20240810-171452/checkpoint-185" \
    --merge_lora true

dpo使用lora训练后的检查点：截屏2024-08-11 21 49 21

sft是能正常合并的。dpo在上周也能正常合并，这周新配置的环境，出现这个bug，我用peft自己合并也是这个报错。

报错：

Traceback (most recent call last):
  File "/root/visual_model/swift/swift/cli/export.py", line 5, in <module>
    export_main()
  File "/root/visual_model/swift/swift/utils/run_utils.py", line 32, in x_main
    result = llm_x(args, **kwargs)
  File "/root/visual_model/swift/swift/llm/export.py", line 190, in llm_export
    merge_lora(args, device_map=args.merge_device_map)
  File "/root/visual_model/swift/swift/llm/infer.py", line 113, in merge_lora
    model, template = prepare_model_template(args, device_map=device_map, verbose=False)
  File "/root/visual_model/swift/swift/llm/infer.py", line 230, in prepare_model_template
    model = Swift.from_pretrained(model, args.ckpt_dir, inference_mode=True)
  File "/root/visual_model/swift/swift/tuners/base.py", line 878, in from_pretrained
    peft_model = load_peft_model(model, 'default')
  File "/root/visual_model/swift/swift/tuners/base.py", line 864, in load_peft_model
    return PeftModel.from_pretrained(
  File "/root/visual_model/swift/swift/tuners/peft.py", line 367, in from_pretrained
    return module_class.from_pretrained(model, model_id, *args, **kwargs)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/peft_model.py", line 541, in from_pretrained
    model = MODEL_TYPE_TO_PEFT_MODEL_MAPPING[config.task_type](
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/peft_model.py", line 1542, in __init__
    super().__init__(model, peft_config, adapter_name, **kwargs)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/peft_model.py", line 155, in __init__
    self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)
  File "/root/visual_model/swift/swift/tuners/peft.py", line 315, in init
    self.__init_origin__(model, config, adapter_name)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/tuners/lora/model.py", line 139, in __init__
    super().__init__(model, config, adapter_name)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 175, in __init__
    self.inject_adapter(self.model, adapter_name)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 431, in inject_adapter
    self._create_and_replace(peft_config, adapter_name, target, target_name, parent, current_key=key)
  File "/root/visual_model/swift/swift/tuners/peft.py", line 97, in _create_and_replace_hook
    return self._create_and_replace_origin(*args, **kwargs)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/tuners/lora/model.py", line 224, in _create_and_replace
    new_module = self._create_new_module(lora_config, adapter_name, target, **kwargs)
  File "/root/visual_model/py_env/swift/lib/python3.10/site-packages/peft/tuners/lora/model.py", line 346, in _create_new_module
    raise ValueError(
ValueError: Target module InternLM2ForCausalLM(
  (model): InternLM2Model(
    (tok_embeddings): Embedding(92553, 6144, padding_idx=2)
    (layers): ModuleList(
      (0-47): 48 x InternLM2DecoderLayer(
        (attention): InternLM2Attention(
          (wqkv): Linear(in_features=6144, out_features=8192, bias=False)
          (wo): Linear(in_features=6144, out_features=6144, bias=False)
          (rotary_emb): InternLM2DynamicNTKScalingRotaryEmbedding()
        )
        (feed_forward): InternLM2MLP(
          (w1): Linear(in_features=6144, out_features=16384, bias=False)
          (w3): Linear(in_features=6144, out_features=16384, bias=False)
          (w2): Linear(in_features=16384, out_features=6144, bias=False)
          (act_fn): SiLU()
        )
        (attention_norm): InternLM2RMSNorm()
        (ffn_norm): InternLM2RMSNorm()
      )
    )
    (norm): InternLM2RMSNorm()
  )
  (output): Linear(in_features=6144, out_features=92553, bias=False)
) is not supported. Currently, only the following modules are supported: `torch.nn.Linear`, `torch.nn.Embedding`, `torch.nn.Conv2d`, `transformers.pytorch_utils.Conv1D`.