
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
   if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import (
       VersatileDiffusionDualGuidedPipeline,
       VersatileDiffusionImageVariationPipeline,
       VersatileDiffusionPipeline,
       VersatileDiffusionTextToImagePipeline,
   )
else:
   from .modeling_text_unet import UNetFlatConditionModel
   from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
   from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
   from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
   from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline











from typing import Union

import fire
import torch
from tqdm import tqdm



def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase = "cpu",	lowerCamelCase = None      ):
  lowercase			:Optional[Any]							=  torch.load(lowerCamelCase,	map_location=lowerCamelCase      )
  for k, v in tqdm(state_dict.items()      ):
    if not isinstance(lowerCamelCase,	torch.Tensor      ):
      raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"      )
    lowercase			:List[Any]							=  v.half()
  if save_path is None:  # overwrite src_path
    lowercase			:Optional[Any]							=  src_path
  torch.save(lowerCamelCase,	lowerCamelCase      )


if __name__ == "__main__":
     fire.Fire(convert)



