


def       lowercase_		(		_A			:    Tuple    ,					_A			:    Union[str, Any]    ,					_A			:    Optional[int]						):

      """simple docstring"""




      def update_area_of_max_square(_A			:    List[Any]    ,					_A			:    Dict						) -> int:
            # BASE CASE
            if row >= rows or col >= cols:
                  return 0

            lowerCamelCase__		:				Optional[int]    =  update_area_of_max_square(_snake_case    ,					col + 1						)
            lowerCamelCase__		:				List[Any]    =  update_area_of_max_square(row + 1    ,					col + 1						)
            lowerCamelCase__		:				int    =  update_area_of_max_square(row + 1    ,					_snake_case						)

            if mat[row][col]:
                  lowerCamelCase__		:				Dict    =  1 + min([right, diagonal, down]						)
                  lowerCamelCase__		:				List[Any]    =  max(largest_square_area[0]    ,					_snake_case						)
                  return sub_problem_sol
            else:
                  return 0

      lowerCamelCase__		:				int    =  [0]
      update_area_of_max_square(0    ,					0						)
      return largest_square_area[0]

def       lowercase_		(		_A			:    List[Any]    ,					_A			:    Tuple    ,					_A			:    Optional[Any]						):

      """simple docstring"""




      def update_area_of_max_square_using_dp_array(
          _A			:    Optional[int]    ,					_A			:    Any    ,					_A			:    str						) -> int:
            if row >= rows or col >= cols:
                  return 0
            if dp_array[row][col] != -1:
                  return dp_array[row][col]

            lowerCamelCase__		:				List[str]    =  update_area_of_max_square_using_dp_array(_snake_case    ,					col + 1    ,					_snake_case						)
            lowerCamelCase__		:				Tuple    =  update_area_of_max_square_using_dp_array(row + 1    ,					col + 1    ,					_snake_case						)
            lowerCamelCase__		:				Union[str, Any]    =  update_area_of_max_square_using_dp_array(row + 1    ,					_snake_case    ,					_snake_case						)

            if mat[row][col]:
                  lowerCamelCase__		:				Union[str, Any]    =  1 + min([right, diagonal, down]						)
                  lowerCamelCase__		:				Any    =  max(largest_square_area[0]    ,					_snake_case						)
                  lowerCamelCase__		:				int    =  sub_problem_sol
                  return sub_problem_sol
            else:
                  return 0

      lowerCamelCase__		:				int    =  [0]
      lowerCamelCase__		:				Any    =  [[-1] * cols for _ in range(_snake_case						)]
      update_area_of_max_square_using_dp_array(0    ,					0    ,					_snake_case						)

      return largest_square_area[0]

def       lowercase_		(		_A			:    Optional[int]    ,					_A			:    int    ,					_A			:    List[str]						):

      """simple docstring"""




      lowerCamelCase__		:				Optional[Any]    =  [[0] * (cols + 1) for _ in range(rows + 1						)]
      lowerCamelCase__		:				str    =  0
      for row in range(rows - 1    ,					-1    ,					-1						):
            for col in range(cols - 1    ,					-1    ,					-1						):
                  lowerCamelCase__		:				Tuple    =  dp_array[row][col + 1]
                  lowerCamelCase__		:				Tuple    =  dp_array[row + 1][col + 1]
                  lowerCamelCase__		:				Union[str, Any]    =  dp_array[row + 1][col]

                  if mat[row][col] == 1:
                        lowerCamelCase__		:				str    =  1 + min(_snake_case    ,					_snake_case    ,					_snake_case						)
                        lowerCamelCase__		:				List[Any]    =  max(dp_array[row][col]    ,					_snake_case						)
                  else:
                        lowerCamelCase__		:				Optional[Any]    =  0

      return largest_square_area

def       lowercase_		(		_A			:    List[str]    ,					_A			:    List[Any]    ,					_A			:    Tuple						):

      """simple docstring"""




      lowerCamelCase__		:				List[str]    =  [0] * (cols + 1)
      lowerCamelCase__		:				List[str]    =  [0] * (cols + 1)
      lowerCamelCase__		:				Union[str, Any]    =  0
      for row in range(rows - 1    ,					-1    ,					-1						):
            for col in range(cols - 1    ,					-1    ,					-1						):
                  lowerCamelCase__		:				Dict    =  current_row[col + 1]
                  lowerCamelCase__		:				str    =  next_row[col + 1]
                  lowerCamelCase__		:				Any    =  next_row[col]

                  if mat[row][col] == 1:
                        lowerCamelCase__		:				Union[str, Any]    =  1 + min(_snake_case    ,					_snake_case    ,					_snake_case						)
                        lowerCamelCase__		:				int    =  max(current_row[col]    ,					_snake_case						)
                  else:
                        lowerCamelCase__		:				Dict    =  0
            lowerCamelCase__		:				Tuple    =  current_row

      return largest_square_area


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))




"""simple docstring"""




import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   ArgumentParser(
							    description=(
							        """PyTorch TPU distributed training launch """
							        """helper utility that will spawn up """
							        """multiple distributed processes"""
							    )						)

							# Optional arguments for the launch helper
							parser.add_argument("""--num_cores"""   ,type=_snake_case   ,default=1   ,help="""Number of TPU cores to use (1 or 8)."""						)

							# positional
							parser.add_argument(
							    """training_script"""   ,type=_snake_case   ,help=(
							        """The full path to the single TPU training """
							        """program/script to be launched in parallel, """
							        """followed by all the arguments for the """
							        """training script"""
							    )   ,)

							# rest from the training program
							parser.add_argument("""training_script_args"""   ,nargs=_snake_case						)

							return parser.parse_args()

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       int           =   parse_args()

							# Import training_script as a module.
							SCREAMING_SNAKE_CASE__						:       Dict           =   Path(args.training_script						)
							sys.path.append(str(script_fpath.parent.resolve()						)						)
							SCREAMING_SNAKE_CASE__						:       int           =   script_fpath.stem
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   importlib.import_module(_snake_case						)

							# Patch sys.argv
							SCREAMING_SNAKE_CASE__						:       str           =   [args.training_script] + args.training_script_args + ["""--tpu_num_cores""", str(args.num_cores						)]
							xmp.spawn(mod._mp_fn   ,args=()   ,nprocs=args.num_cores						)


if __name__ == "__main__":
					main()




