





'''simple docstring'''






from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments
def 				_lowerCamelCase(	)		->	List[Any]:
    A							:							List[Any]				=    HfArgumentParser(UpperCamelCase_		)
    try:
        A							:							Dict				=    parser.parse_args_into_dataclasses()[0]
    except ValueError as e:
        A							:							str				=    '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
        A							:							str				=    ''' '''.join(str(UpperCamelCase_		).split(''' '''		)[:-1]		)
        A							:							Optional[int]				=    ''''''
        A							:							Any				=    eval(str(UpperCamelCase_		).split(''' '''		)[-1]		)
        A							:							int				=    []
        for arg in depreciated_args:
            # arg[2:] removes '--'
            if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
                # arg[5:] removes '--no_'
                full_error_msg += arg_error_msg.format(arg[5:]		)
            else:
                wrong_args.append(UpperCamelCase_		)
        if len(UpperCamelCase_		) > 0:
            A							:							str				=    full_error_msg + begin_error_msg + str(UpperCamelCase_		)
        raise ValueError(UpperCamelCase_		)

    A							:							Dict				=    PyTorchBenchmark(args=UpperCamelCase_		)
    benchmark.run()


if __name__ == "__main__":
     main()








"""simple docstring"""




UpperCamelCase											=     [
    [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
]






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				int       )							->				bool:







  '''simple docstring'''







  return 0 <= row < rows and 0 <= col < cols






def 							lowerCAmelCase			(   UpperCamelCase_:				int  ,			UpperCamelCase_:				int  ,			UpperCamelCase_:				set  ,			UpperCamelCase_:				list[list[int]]       )							->				int:







  '''simple docstring'''







  _a					      =						len(UpperCamelCase_       )
  _a					      =						len(mat[0]       )
  if is_safe(UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_       ) and (row, col) not in seen and mat[row][col] == 1:
    seen.add((row, col)       )
    return (
        1
        + depth_first_search(row + 1  ,			UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_       )
        + depth_first_search(row - 1  ,			UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_       )
        + depth_first_search(UpperCamelCase_  ,			col + 1  ,			UpperCamelCase_  ,			UpperCamelCase_       )
        + depth_first_search(UpperCamelCase_  ,			col - 1  ,			UpperCamelCase_  ,			UpperCamelCase_       )
    )
  else:
    return 0






def 							lowerCAmelCase			(   UpperCamelCase_:				list[list[int]]       )							->				int:







  '''simple docstring'''







  _a					      =						set()

  _a					      =						0
  for row, line in enumerate(UpperCamelCase_       ):
    for col, item in enumerate(UpperCamelCase_       ):
      if item == 1 and (row, col) not in seen:
        # Maximizing the area
        _a					      =						max(UpperCamelCase_  ,			depth_first_search(UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_  ,			UpperCamelCase_       )       )
  return max_area


if __name__ == "__main__":
     import doctest

     print(find_max_area(matrix))  # Output -> 6
     doctest.testmod()


