


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 __future__ import annotations




def    snake_case_     (  snake_case			,							snake_case     )  ->				bool:
       if len(snake_case     ) == 0:
              return False
       lowercase__:   Any  			=   len(snake_case     ) // 2
       if a_list[midpoint] == item:
              return True
       if item < a_list[midpoint]:
              return binary_search(a_list[:midpoint]			,							snake_case     )
       else:
              return binary_search(a_list[midpoint + 1 :]			,							snake_case     )


if __name__ == "__main__":
 __lowerCAmelCase		       =							input('''Enter numbers separated by comma:\n''').strip()
 __lowerCAmelCase		       =							[int(item.strip()) for item in user_input.split(''',''')]
 __lowerCAmelCase		       =							int(input('''Enter the number to be found in the list:\n''').strip())
 __lowerCAmelCase		       =							'''''' if binary_search(sequence, target) else '''not '''
 print(F'''{target} was {not_str}found in {sequence}''')


