






from __future__ import annotations






def     _snake_case    (__lowercase    ,      __lowercase):
   if len(__lowercase) == 0:
      return False
   UpperCamelCase_									=     len(__lowercase) // 2
   if a_list[midpoint] == item:
      return True
   if item < a_list[midpoint]:
      return binary_search(a_list[:midpoint]    ,      __lowercase)
   else:
      return binary_search(a_list[midpoint + 1 :]    ,      __lowercase)


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













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


try:
 if not (is_transformers_available() and is_torch_available()):
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 from ...utils.dummy_torch_and_transformers_objects import (
     ImageTextPipelineOutput,
     UniDiffuserPipeline,
 )
else:
 from .modeling_text_decoder import UniDiffuserTextDecoder
 from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
 from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline





