


def 	_lowerCAmelCase					( UpperCamelCase__:  int				,       UpperCamelCase__:  int				,       UpperCamelCase__:  list[list[int]]    )			-> int:





	"""simple docstring"""







	def update_area_of_max_square(UpperCamelCase__:  int				,       UpperCamelCase__:  int    ) -> int:
		# BASE CASE
		if row >= rows or col >= cols:
			return 0

		A             =					update_area_of_max_square(UpperCamelCase__				,       col + 1    )
		A             =					update_area_of_max_square(row + 1				,       col + 1    )
		A             =					update_area_of_max_square(row + 1				,       UpperCamelCase__    )

		if mat[row][col]:
			A             =					1 + min([right, diagonal, down]    )
			A             =					max(largest_square_area[0]				,       UpperCamelCase__    )
			return sub_problem_sol
		else:
			return 0

	A             =					[0]
	update_area_of_max_square(0				,       0    )
	return largest_square_area[0]





def 	_lowerCAmelCase					( UpperCamelCase__:  int				,       UpperCamelCase__:  int				,       UpperCamelCase__:  list[list[int]]    )			-> int:





	"""simple docstring"""







	def update_area_of_max_square_using_dp_array(
	    UpperCamelCase__:  int				,       UpperCamelCase__:  int				,       UpperCamelCase__:  list[list[int]]    ) -> int:
		if row >= rows or col >= cols:
			return 0
		if dp_array[row][col] != -1:
			return dp_array[row][col]

		A             =					update_area_of_max_square_using_dp_array(UpperCamelCase__				,       col + 1				,       UpperCamelCase__    )
		A             =					update_area_of_max_square_using_dp_array(row + 1				,       col + 1				,       UpperCamelCase__    )
		A             =					update_area_of_max_square_using_dp_array(row + 1				,       UpperCamelCase__				,       UpperCamelCase__    )

		if mat[row][col]:
			A             =					1 + min([right, diagonal, down]    )
			A             =					max(largest_square_area[0]				,       UpperCamelCase__    )
			A             =					sub_problem_sol
			return sub_problem_sol
		else:
			return 0

	A             =					[0]
	A             =					[[-1] * cols for _ in range(UpperCamelCase__    )]
	update_area_of_max_square_using_dp_array(0				,       0				,       UpperCamelCase__    )

	return largest_square_area[0]





def 	_lowerCAmelCase					( UpperCamelCase__:  int				,       UpperCamelCase__:  int				,       UpperCamelCase__:  list[list[int]]    )			-> int:





	"""simple docstring"""







	A             =					[[0] * (cols + 1) for _ in range(rows + 1    )]
	A             =					0
	for row in range(rows - 1				,       -1				,       -1    ):
		for col in range(cols - 1				,       -1				,       -1    ):
			A             =					dp_array[row][col + 1]
			A             =					dp_array[row + 1][col + 1]
			A             =					dp_array[row + 1][col]

			if mat[row][col] == 1:
				A             =					1 + min(UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__    )
				A             =					max(dp_array[row][col]				,       UpperCamelCase__    )
			else:
				A             =					0

	return largest_square_area





def 	_lowerCAmelCase					( UpperCamelCase__:  int				,       UpperCamelCase__:  int				,       UpperCamelCase__:  list[list[int]]    )			-> int:





	"""simple docstring"""







	A             =					[0] * (cols + 1)
	A             =					[0] * (cols + 1)
	A             =					0
	for row in range(rows - 1				,       -1				,       -1    ):
		for col in range(cols - 1				,       -1				,       -1    ):
			A             =					current_row[col + 1]
			A             =					next_row[col + 1]
			A             =					next_row[col]

			if mat[row][col] == 1:
				A             =					1 + min(UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__    )
				A             =					max(current_row[col]				,       UpperCamelCase__    )
			else:
				A             =					0
		A             =					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]]))







_lowercase							:   Dict						=						"0.21.0"

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
				from .utils import rich



