


'''simple docstring'''
import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class        lowercase     (							SCREAMING_SNAKE_CASE_     ,		unittest.TestCase ):

		"""simple docstring"""

		_a   			=    LEDTokenizer
		_a   			=    LEDTokenizerFast
		_a   			=    True




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							super().setUp()
							UpperCamelCase__       :Optional[int]							 =			[
							    'l',
							    'o',
							    'w',
							    'e',
							    'r',
							    's',
							    't',
							    'i',
							    'd',
							    'n',
							    '\u0120',
							    '\u0120l',
							    '\u0120n',
							    '\u0120lo',
							    '\u0120low',
							    'er',
							    '\u0120lowest',
							    '\u0120newer',
							    '\u0120wider',
							    '<unk>',
							]
							UpperCamelCase__       :List[Any]							 =			dict(zip(snake_case__   ,       range(len(snake_case__							)							)							)							)
							UpperCamelCase__       :Optional[int]							 =			['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
							UpperCamelCase__       :str							 =			{'unk_token': '<unk>'}

							UpperCamelCase__       :Union[str, Any]							 =			os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES['''vocab_file''']							)
							UpperCamelCase__       :int							 =			os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES['''merges_file''']							)
							with open(self.vocab_file   ,       '''w'''   ,       encoding='''utf-8'''							) as fp:
												fp.write(json.dumps(snake_case__							) + '''\n'''							)
							with open(self.merges_file   ,       '''w'''   ,       encoding='''utf-8'''							) as fp:
												fp.write('''\n'''.join(snake_case__							)							)




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


							kwargs.update(self.special_tokens_map							)
							return self.tokenizer_class.from_pretrained(self.tmpdirname   ,       **snake_case__							)




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


							kwargs.update(self.special_tokens_map							)
							return self.rust_tokenizer_class.from_pretrained(self.tmpdirname   ,       **snake_case__							)




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_							):

							'''simple docstring'''


							return "lower newer", "lower newer"




		@cached_property
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							return LEDTokenizer.from_pretrained('''allenai/led-base-16384'''							)




		@cached_property
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384'''							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Optional[int]							 =			['A long paragraph for summarization.', 'Another paragraph for summarization.']
							UpperCamelCase__       :Optional[Any]							 =			[0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :Dict							 =			tokenizer(snake_case__   ,       max_length=len(snake_case__							)   ,       padding=snake_case__   ,       return_tensors='''pt'''							)
												self.assertIsInstance(snake_case__   ,       snake_case__							)

												self.assertEqual((2, 9)   ,       batch.input_ids.shape							)
												self.assertEqual((2, 9)   ,       batch.attention_mask.shape							)
												UpperCamelCase__       :str							 =			batch.input_ids.tolist()[0]
												self.assertListEqual(snake_case__   ,       snake_case__							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :List[str]							 =			['A long paragraph for summarization.', 'Another paragraph for summarization.']
							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :Dict							 =			tokenizer(snake_case__   ,       padding=snake_case__   ,       return_tensors='''pt'''							)
												self.assertIn('''input_ids'''   ,       snake_case__							)
												self.assertIn('''attention_mask'''   ,       snake_case__							)
												self.assertNotIn('''labels'''   ,       snake_case__							)
												self.assertNotIn('''decoder_attention_mask'''   ,       snake_case__							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :str							 =			[
							    'Summary of the text.',
							    'Another summary.',
							]
							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :int							 =			tokenizer(text_target=snake_case__   ,       max_length=32   ,       padding='''max_length'''   ,       return_tensors='''pt'''							)
												self.assertEqual(32   ,       targets['''input_ids'''].shape[1]							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :List[Any]							 =			tokenizer(
												    ['''I am a small frog''' * 1024, '''I am a small frog''']   ,       padding=snake_case__   ,       truncation=snake_case__   ,       return_tensors='''pt'''							)
												self.assertIsInstance(snake_case__   ,       snake_case__							)
												self.assertEqual(batch.input_ids.shape   ,       (2, 5122)							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :str							 =			['A long paragraph for summarization.']
							UpperCamelCase__       :str							 =			[
							    'Summary of the text.',
							]
							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :int							 =			tokenizer(snake_case__   ,       return_tensors='''pt'''							)
												UpperCamelCase__       :List[Any]							 =			tokenizer(text_target=snake_case__   ,       return_tensors='''pt'''							)
												UpperCamelCase__       :str							 =			inputs['input_ids']
												UpperCamelCase__       :int							 =			targets['input_ids']
												self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()							)
												self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()							)
												self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()							)
												self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()							)




		@require_torch
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
												UpperCamelCase__       :int							 =			['Summary of the text.', 'Another summary.']
												UpperCamelCase__       :Dict							 =			[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

												UpperCamelCase__       :List[Any]							 =			tokenizer(snake_case__   ,       padding=snake_case__							)
												UpperCamelCase__       :Tuple							 =			[[0] * len(snake_case__							) for x in encoded_output['input_ids']]
												UpperCamelCase__       :Optional[Any]							 =			tokenizer.pad(snake_case__							)
												self.assertSequenceEqual(outputs['''global_attention_mask''']   ,       snake_case__							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							pass




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''							):
																	UpperCamelCase__       :Optional[int]							 =			self.rust_tokenizer_class.from_pretrained(snake_case__   ,       **snake_case__							)
																	UpperCamelCase__       :Tuple							 =			self.tokenizer_class.from_pretrained(snake_case__   ,       **snake_case__							)
																	UpperCamelCase__       :List[str]							 =			'A, <mask> AllenNLP sentence.'
																	UpperCamelCase__       :Union[str, Any]							 =			tokenizer_r.encode_plus(snake_case__   ,       add_special_tokens=snake_case__   ,       return_token_type_ids=snake_case__							)
																	UpperCamelCase__       :Dict							 =			tokenizer_p.encode_plus(snake_case__   ,       add_special_tokens=snake_case__   ,       return_token_type_ids=snake_case__							)
																	self.assertEqual(sum(tokens_r['''token_type_ids''']							)   ,       sum(tokens_p['''token_type_ids''']							)							)
																	self.assertEqual(
																	    sum(tokens_r['''attention_mask''']							) / len(tokens_r['''attention_mask''']							)   ,       sum(tokens_p['''attention_mask''']							) / len(tokens_p['''attention_mask''']							)   ,       )

																	UpperCamelCase__       :List[str]							 =			tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']							)
																	UpperCamelCase__       :str							 =			tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']							)
																	self.assertSequenceEqual(tokens_p['''input_ids''']   ,       [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)
																	self.assertSequenceEqual(tokens_r['''input_ids''']   ,       [0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]							)

																	self.assertSequenceEqual(
																	    snake_case__   ,       ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']							)
																	self.assertSequenceEqual(
																	    snake_case__   ,       ['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>''']							)



'''simple docstring'''
from __future__ import annotations

__snake_case											=					list[list[int]]

# assigning initial values to the grid
__snake_case											=					[
    [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											=					[
    [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       a				(      __a			, __a			, __a			, __a       )  ->     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       a				(      __a       )  ->     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       a				(      __a       )  ->     Matrix | None:



					'''simple docstring'''






					if location := find_empty_location(__a       ):
										UpperCamelCase__ ,    UpperCamelCase__       :Optional[int]							 =			location
					else:
										# If the location is ``None``, then the grid is solved.
										return grid

					for digit in range(1			, 10       ):
										if is_safe(__a			, __a			, __a			, __a       ):
															UpperCamelCase__       :Tuple							 =			digit

															if sudoku(__a       ) is not None:
																				return grid

															UpperCamelCase__       :Union[str, Any]							 =			0

					return None


def       a				(      __a       )  ->     None:



					'''simple docstring'''






					for row in grid:
										for cell in row:
															print(__a			, 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											=					sudoku(example_grid)
				if solution is not None:
						print_solution(solution)
				else:
						print('''Cannot find a solution.''')