





def     a__ (					lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_											=len(__UpperCamelCase  )
   UpperCAmelCase_											=len(__UpperCamelCase  )
   UpperCAmelCase_											=(
       first_str_length if first_str_length > second_str_length else second_str_length
   )
   UpperCAmelCase_											=[]
   for char_count in range(__UpperCamelCase  ):
      if char_count < first_str_length:
         output_list.append(first_str[char_count]  )
      if char_count < second_str_length:
         output_list.append(second_str[char_count]  )
   return "".join(__UpperCamelCase  )


if __name__ == "__main__":
     print(alternative_string_arrange("""AB""", """XYZ"""), end=""" """)











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowercase  :   Any						      ={
    """configuration_upernet""": ["""UperNetConfig"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __lowercase  :   Tuple						      =[
         """UperNetForSemanticSegmentation""",
         """UperNetPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_upernet import UperNetConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
     import sys

     __lowercase  :   Any						      =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




