





from __future__ import annotations

A_      =      list[list[int]]

# assigning initial values to the grid
A_      =      [
    [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_      =      [
    [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        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase       )->       bool:



			"""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        __UpperCAmelCase    (       UpperCAmelCase       )->       tuple[int, int] | None:



			"""simple docstring"""







			for i in range(9       ):
						for j in range(9       ):
									if grid[i][j] == 0:
												return i, j
			return None






def        __UpperCAmelCase    (       UpperCAmelCase       )->       Matrix | None:



			"""simple docstring"""







			if location := find_empty_location(UpperCAmelCase       ):
						lowercase		,lowercase							=		location
			else:
						# If the location is ``None``, then the grid is solved.
						return grid

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

									if sudoku(UpperCAmelCase       ) is not None:
												return grid

									lowercase							=		0

			return None






def        __UpperCAmelCase    (       UpperCAmelCase       )->       None:



			"""simple docstring"""







			for row in grid:
						for cell in row:
									print(UpperCAmelCase,		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" + "=" * 20)
												print_solution(example_grid)
												print("\nExample grid solution:")
												A_      =      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_      =      {
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_      =      [
						    "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "GPTBigCodeForSequenceClassification",
						    "GPTBigCodeForTokenClassification",
						    "GPTBigCodeForCausalLM",
						    "GPTBigCodeModel",
						    "GPTBigCodePreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_gpt_bigcode import (
												    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GPTBigCodeForCausalLM,
												    GPTBigCodeForSequenceClassification,
												    GPTBigCodeForTokenClassification,
												    GPTBigCodeModel,
												    GPTBigCodePreTrainedModel,
												)


else:
						import sys

						A_      =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





