



'''simple docstring'''






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase: Optional[int]							=						{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase: Tuple							=						[
         'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'AutoformerForPrediction',
         'AutoformerModel',
         'AutoformerPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_autoformer import (
         AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         AutoformerConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_autoformer import (
              AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              AutoformerForPrediction,
              AutoformerModel,
              AutoformerPreTrainedModel,
          )

else:
     import sys

     lowerCAmelCase: Optional[int]							=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




'''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)