



"""simple docstring"""






from __future__ import annotations

__snake_case							:     str   =					list[list[int]]

# assigning initial values to the grid
__snake_case							:     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
__snake_case							:     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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case      ,__snake_case			)		->     bool:
			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     _lowercase       (						__snake_case			)		->     tuple[int, int] | None:
			for i in range(9			):
						for j in range(9			):
									if grid[i][j] == 0:
												return i, j
			return None


def     _lowercase       (						__snake_case			)		->     Matrix | None:
			if location := find_empty_location(__snake_case			):
						__lowerCAmelCase		,			__lowerCAmelCase   :						Any				= location
			else:
						# If the location is ``None``, then the grid is solved.
						return grid

			for digit in range(1      ,10			):
						if is_safe(__snake_case      ,__snake_case      ,__snake_case      ,__snake_case			):
									__lowerCAmelCase   :						Optional[Any]				= digit

									if sudoku(__snake_case			) is not None:
												return grid

									__lowerCAmelCase   :						Dict				= 0

			return None


def     _lowercase       (						__snake_case			)		->     None:
			for row in grid:
						for cell in row:
									print(__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' + '=' * 20)
		print_solution(example_grid)
		print('\nExample grid solution:')
		__snake_case							:     Optional[Any]   =					sudoku(example_grid)
		if solution is not None:
			print_solution(solution)
		else:
			print('Cannot find a solution.')




"""simple docstring"""






import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case							:     Any   =					get_tests_dir('fixtures/spiece.model')



@require_sentencepiece
@require_tokenizers
class     A__     (						__SCREAMING_SNAKE_CASE						,	unittest.TestCase							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			AlbertTokenizer
	SCREAMING_SNAKE_CASE					   =			AlbertTokenizerFast
	SCREAMING_SNAKE_CASE					   =			True
	SCREAMING_SNAKE_CASE					   =			True
	SCREAMING_SNAKE_CASE					   =			True

	def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> Optional[int]:

				"""simple docstring"""

				super().setUp()

				# We have a SentencePiece fixture for testing
				__lowerCAmelCase   :						List[Any]				= AlbertTokenizer(_SCREAMING_SNAKE_CASE)
				tokenizer.save_pretrained(self.tmpdirname)

	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any] ,    _SCREAMING_SNAKE_CASE:	Optional[int])       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= "this is a test"
				__lowerCAmelCase   :						Any				= "this is a test"
				return input_text, output_text

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= "<pad>"
				__lowerCAmelCase   :						List[str]				= 0

				self.assertEqual(self.get_tokenizer()._convert_token_to_id(_SCREAMING_SNAKE_CASE) ,    _SCREAMING_SNAKE_CASE)
				self.assertEqual(self.get_tokenizer()._convert_id_to_token(_SCREAMING_SNAKE_CASE) ,    _SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= list(self.get_tokenizer().get_vocab().keys())

				self.assertEqual(vocab_keys[0] ,    "<pad>")
				self.assertEqual(vocab_keys[1] ,    "<unk>")
				self.assertEqual(vocab_keys[-1] ,    "▁eloquent")
				self.assertEqual(len(_SCREAMING_SNAKE_CASE) ,    3_0000)

	def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[Any])       -> str:

				"""simple docstring"""

				self.assertEqual(self.get_tokenizer().vocab_size ,    3_0000)

	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any])       -> List[Any]:

				"""simple docstring"""

				if not self.test_rust_tokenizer:
							return

				__lowerCAmelCase   :						List[str]				= self.get_tokenizer()
				__lowerCAmelCase   :						Dict				= self.get_rust_tokenizer()

				__lowerCAmelCase   :						Optional[int]				= "I was born in 92000, and this is falsé."

				__lowerCAmelCase   :						Tuple				= tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[str]				= rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						List[Any]				= tokenizer.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Any				= rust_tokenizer.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						List[str]				= self.get_rust_tokenizer()
				__lowerCAmelCase   :						str				= tokenizer.encode(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Dict				= rust_tokenizer.encode(_SCREAMING_SNAKE_CASE)
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE     (  self:	List[str])       -> int:

				"""simple docstring"""

				__lowerCAmelCase   :						Optional[int]				= AlbertTokenizer(_SCREAMING_SNAKE_CASE ,    keep_accents=_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						List[str]				= tokenizer.tokenize("This is a test")
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    ["▁this", "▁is", "▁a", "▁test"])

				self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE) ,    [48, 25, 21, 1289])

				__lowerCAmelCase   :						Union[str, Any]				= tokenizer.tokenize("I was born in 92000, and this is falsé.")
				self.assertListEqual(
				    _SCREAMING_SNAKE_CASE ,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."])
				__lowerCAmelCase   :						Dict				= tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)
				self.assertListEqual(_SCREAMING_SNAKE_CASE ,    [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9])

				__lowerCAmelCase   :						Any				= tokenizer.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE)
				self.assertListEqual(
				    _SCREAMING_SNAKE_CASE ,    ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."] ,    )

	def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> str:

				"""simple docstring"""

				__lowerCAmelCase   :						int				= AlbertTokenizer(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase   :						Dict				= tokenizer.encode("sequence builders")
				__lowerCAmelCase   :						List[Any]				= tokenizer.encode("multi-sequence build")

				__lowerCAmelCase   :						Union[str, Any]				= tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[str]				= tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

				assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
				assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
				    tokenizer.sep_token_id
				]







	@slow
	def 							_SCREAMING_SNAKE_CASE     (  self:	int)       -> List[str]:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= {"attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "input_ids": [[2, 2_1970, 13, 5, 6092, 167, 28, 7103, 2153, 673, 8, 7028, 1_2051, 18, 17, 7103, 2153, 673, 8, 3515, 1_8684, 8, 4461, 6, 1927, 297, 8, 1_2060, 2607, 18, 13, 5, 4461, 15, 1_0538, 38, 8, 135, 15, 822, 58, 15, 993, 1_0363, 15, 1460, 8005, 4461, 15, 993, 255, 2328, 9, 9, 9, 6, 26, 1112, 816, 3260, 13, 5, 103, 2377, 6, 17, 1112, 816, 2782, 13, 5, 103, 1_0641, 6, 29, 84, 2512, 2430, 782, 1_8684, 2761, 19, 808, 2430, 2556, 17, 855, 1480, 9477, 4091, 128, 1_1712, 15, 7103, 2153, 673, 17, 2_4883, 9990, 9, 3], [2, 1_1502, 25, 1006, 20, 782, 8, 1_1809, 855, 1732, 1_9393, 1_8667, 37, 367, 2_1018, 69, 1854, 34, 1_1860, 1_9124, 27, 156, 225, 17, 193, 4141, 19, 65, 9124, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 2231, 886, 2385, 1_7659, 84, 14, 1_6792, 1952, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
				# fmt: on

				self.tokenizer_integration_test_util(
				    expected_encoding=_SCREAMING_SNAKE_CASE ,    model_name="albert-base-v2" ,    revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e" ,    )