

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCamelCase__					:	Any				    =	{
    '''configuration_blenderbot_small''': [
        '''BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BlenderbotSmallConfig''',
        '''BlenderbotSmallOnnxConfig''',
    ],
    '''tokenization_blenderbot_small''': ['''BlenderbotSmallTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__					:	Dict				    =	['''BlenderbotSmallTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__					:	Dict				    =	[
						    '''BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''BlenderbotSmallForCausalLM''',
						    '''BlenderbotSmallForConditionalGeneration''',
						    '''BlenderbotSmallModel''',
						    '''BlenderbotSmallPreTrainedModel''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__					:	Optional[Any]				    =	[
						    '''TFBlenderbotSmallForConditionalGeneration''',
						    '''TFBlenderbotSmallModel''',
						    '''TFBlenderbotSmallPreTrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__					:	Optional[Any]				    =	[
						    '''FlaxBlenderbotSmallForConditionalGeneration''',
						    '''FlaxBlenderbotSmallModel''',
						    '''FlaxBlenderbotSmallPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_blenderbot_small import (
						    BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    BlenderbotSmallConfig,
						    BlenderbotSmallOnnxConfig,
						)
						from .tokenization_blenderbot_small import BlenderbotSmallTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_blenderbot_small_fast import BlenderbotSmallTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_blenderbot_small import (
												    BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BlenderbotSmallForCausalLM,
												    BlenderbotSmallForConditionalGeneration,
												    BlenderbotSmallModel,
												    BlenderbotSmallPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_blenderbot_small import (
												    TFBlenderbotSmallForConditionalGeneration,
												    TFBlenderbotSmallModel,
												    TFBlenderbotSmallPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_blenderbot_small import (
												    FlaxBlenderbotSmallForConditionalGeneration,
												    FlaxBlenderbotSmallModel,
												    FlaxBlenderbotSmallPreTrainedModel,
												)

else:
						import sys

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












import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
					A       :   List[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.''',
					)

					A       :   List[Any]					= parser.parse_args()

					A       :   int					= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

					A       :   Tuple					= CLIPImageProcessor()
					A       :   int					= CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

					A       :   Tuple					= 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)



