



'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase: Any							=						logging.get_logger(__name__)

lowerCAmelCase: Any							=						{'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}

class 							a__( lowerCamelCase__     ):
    lowercase__			=   """ctrl"""
    lowercase__			=   ["""past_key_values"""]
    lowercase__			=   {
        """max_position_embeddings""": """n_positions""",
        """hidden_size""": """n_embd""",
        """num_attention_heads""": """n_head""",
        """num_hidden_layers""": """n_layer""",
    }







    def __init__(				self			:  Optional[Any]						,      __snake_case			:  Optional[int]=24_65_34						,      __snake_case			:  List[Any]=2_56						,      __snake_case			:  str=12_80						,      __snake_case			:  Tuple=81_92						,      __snake_case			:  Any=48						,      __snake_case			:  int=16						,      __snake_case			:  Any=0.1						,      __snake_case			:  List[Any]=0.1						,      __snake_case			:  List[Any]=1e-6						,      __snake_case			:  int=0.02						,      __snake_case			:  Union[str, Any]=True						,      **__snake_case			:  Optional[int]						,      ):
      a						: Dict					       =					vocab_size
      a						: Dict					       =					n_positions
      a						: Optional[int]					       =					n_embd
      a						: Union[str, Any]					       =					n_layer
      a						: Any					       =					n_head
      a						: Optional[Any]					       =					dff
      a						: List[Any]					       =					resid_pdrop
      a						: Any					       =					embd_pdrop
      a						: Union[str, Any]					       =					layer_norm_epsilon
      a						: List[Any]					       =					initializer_range

      a						: Dict					       =					use_cache

      super().__init__(**__snake_case     )




'''simple docstring'''






import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
     lowerCAmelCase: Any							=						argparse.ArgumentParser()

     parser.add_argument('--dump_path', default=None, type=str, required=True, help='Path to the output model.')

     parser.add_argument(
         '--txt2img_unclip',
         default='kakaobrain/karlo-v1-alpha',
         type=str,
         required=False,
         help='The pretrained txt2img unclip.',
     )

     lowerCAmelCase: Optional[int]							=						parser.parse_args()

     lowerCAmelCase: List[Any]							=						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

     lowerCAmelCase: Optional[Any]							=						CLIPImageProcessor()
     lowerCAmelCase: Tuple							=						CLIPVisionModelWithProjection.from_pretrained('openai/clip-vit-large-patch14')

     lowerCAmelCase: List[str]							=						UnCLIPImageVariationPipeline(
         decoder=txtaimg.decoder,
         text_encoder=txtaimg.text_encoder,
         tokenizer=txtaimg.tokenizer,
         text_proj=txtaimg.text_proj,
         feature_extractor=feature_extractor,
         image_encoder=image_encoder,
         super_res_first=txtaimg.super_res_first,
         super_res_last=txtaimg.super_res_last,
         decoder_scheduler=txtaimg.decoder_scheduler,
         super_res_scheduler=txtaimg.super_res_scheduler,
     )

     imgaimg.save_pretrained(args.dump_path)