

'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase__						:       Optional[int]										=						{
    """configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase__						:       str										=						[
					    """TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TimesformerModel""",
					    """TimesformerForVideoClassification""",
					    """TimesformerPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_timesformer import (
										    TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TimesformerForVideoClassification,
										    TimesformerModel,
										    TimesformerPreTrainedModel,
										)

else:
					import sys

					lowerCAmelCase__						:       Any										=						_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__						:       Dict										=						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__						:       List[Any]										=						parser.parse_args()

					lowerCAmelCase__						:       Optional[Any]										=						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

					lowerCAmelCase__						:       Optional[int]										=						CLIPImageProcessor()
					lowerCAmelCase__						:       str										=						CLIPVisionModelWithProjection.from_pretrained("""openai/clip-vit-large-patch14""")

					lowerCAmelCase__						:       Dict										=						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)



