




from __future__ import annotations

__A						:							Dict							=  list[list[int]]

# assigning initial values to the grid
__A						:							Matrix							=  [
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
__A						:							Matrix							=  [
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			for i in range(9   ):
						if grid[row][i] == n or grid[i][column] == n:
									return False

			for i in range(3   ):
						for j in range(3   ):
									if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
												return False

			return True
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			for i in range(9   ):
						for j in range(9   ):
									if grid[i][j] == 0:
												return i, j
			return None
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			if location := find_empty_location(SCREAMING_SNAKE_CASE   ):
						SCREAMING_SNAKE_CASE     ,  SCREAMING_SNAKE_CASE           =					location
			else:
						# If the location is ``None``, then the grid is solved.
						return grid

			for digit in range(1					,	10   ):
						if is_safe(SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE					,	SCREAMING_SNAKE_CASE   ):
									SCREAMING_SNAKE_CASE           =					digit

									if sudoku(SCREAMING_SNAKE_CASE   ) is not None:
												return grid

									SCREAMING_SNAKE_CASE           =					0

			return None
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			for row in grid:
						for cell in row:
									print(SCREAMING_SNAKE_CASE					,	end=""" """   )
						print()


if __name__ == "__main__":
		# make a copy of grid so that you can compare with the unmodified grid
		for example_grid in (initial_grid, no_solution):
				print("""\nExample grid:\n""" + """=""" * 2_0)
				print_solution(example_grid)
				print("""\nExample grid solution:""")
				__A						:							Any							=  sudoku(example_grid)
				if solution is not None:
						print_solution(solution)
				else:
						print("""Cannot find a solution.""")












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A						:							Dict							=  {
    """configuration_nllb_moe""": [
        """NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """NllbMoeConfig""",
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A						:							List[Any]							=  [
		    """NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """NllbMoeForConditionalGeneration""",
		    """NllbMoeModel""",
		    """NllbMoePreTrainedModel""",
		    """NllbMoeTop2Router""",
		    """NllbMoeSparseMLP""",
		]


if TYPE_CHECKING:
		from .configuration_nllb_moe import (
		    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    NllbMoeConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_nllb_moe import (
				    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    NllbMoeForConditionalGeneration,
				    NllbMoeModel,
				    NllbMoePreTrainedModel,
				    NllbMoeSparseMLP,
				    NllbMoeTopaRouter,
				)


else:
		import sys

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






