cls._get_model_file cannot use

[LukeLIN-web]

https://github.com/guoyww/AnimateDiff/blob/main/animatediff/models/unet.py

diffusers 0.11 has code

class UNet3DConditionModel(ModelMixin, ConfigMixin): 
    @classmethod
    def from_pretrained_2d(cls, pretrained_model_name_or_path, unet_additional_kwargs={}, **kwargs):
                model_file = cls._get_model_file(
                    pretrained_model_name_or_path,
                    weights_name=SAFETENSORS_WEIGHTS_NAME,
                    cache_dir=cache_dir,

But now diffusers 0.32 it shows

Traceback (most recent call last):
  File "/homeAnimateDiff/scripts/animate.py", line 383, in <module>
    main(args)
  File "/home/.conda/envs/animatediff/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/lAnimateDiff/scripts/animate.py", line 242, in main
    unet = UNet3DConditionModel.from_pretrained_2d(args.pretrained_model_path, subfolder="unet", unet_additional_kwargs=OmegaConf.to_container(inference_config.unet_additional_kwargs)).cuda()
  File "/homAnimateDiff/animatediff/models/unet.py", line 526, in from_pretrained_2d
    model_file = cls._get_model_file(
AttributeError: type object 'UNet3DConditionModel' has no attribute '_get_model_file'

I wonder what has changed .

[LukeLIN-web]

I am trying to use from diffusers.utils import _get_model_file But it show

RuntimeError: Error(s) in loading state_dict for AutoencoderKL:
        Missing key(s) in state_dict: "encoder.mid_block.attentions.0.to_q.weight", "encoder.mid_block.attentions.0.to_q.bias", "encoder.mid_block.attentions.0.to_k.weight", "encoder.mid_block.attentions.0.to_k.bias", "encoder.mid_block.attentions.0.to_v.weight", "encoder.mid_block.attentions.0.to_v.bias", "encoder.mid_block.attentions.0.to_out.0.weight", "encoder.mid_block.attentions.0.to_out.0.bias", "decoder.mid_block.attentions.0.to_q.weight", "decoder.mid_block.attentions.0.to_q.bias", "decoder.mid_block.attentions.0.to_k.weight", "decoder.mid_block.attentions.0.to_k.bias", "decoder.mid_block.attentions.0.to_v.weight", "decoder.mid_block.attentions.0.to_v.bias", "decoder.mid_block.attentions.0.to_out.0.weight", "decoder.mid_block.attentions.0.to_out.0.bias". 
        Unexpected key(s) in state_dict: "encoder.mid_block.attentions.0.key.bias", "encoder.mid_block.attentions.0.key.weight", "encoder.mid_block.attentions.0.proj_attn.bias", "encoder.mid_block.attentions.0.proj_attn.weight", "encoder.mid_block.attentions.0.query.bias", "encoder.mid_block.attentions.0.query.weight", "encoder.mid_block.attentions.0.value.bias", "encoder.mid_block.attentions.0.value.weight", "decoder.mid_block.attentions.0.key.bias", "decoder.mid_block.attentions.0.key.weight", "decoder.mid_block.attentions.0.proj_attn.bias", "decoder.mid_block.attentions.0.proj_attn.weight", "decoder.mid_block.attentions.0.query.bias", "decoder.mid_block.attentions.0.query.weight", "decoder.mid_block.attentions.0.value.bias", "decoder.mid_block.attentions.0.value.weight".