




class        UpperCAmelCase_  :  # Public class to implement a graph

						'''simple docstring'''




						def __init__(   self				,							_A				,							_A				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= row
													__SCREAMING_SNAKE_CASE									= col
													__SCREAMING_SNAKE_CASE									= graph






						def 	_A     (   self				,							_A				,							_A				,							_A		):







													'''simple docstring'''

													return (
													    0 <= i < self.ROW
													    and 0 <= j < self.COL
													    and not visited[i][j]
													    and self.graph[i][j]
													)






						def 	_A     (   self				,							_A				,							_A				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= [-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
													__SCREAMING_SNAKE_CASE									= [-1, 0, 1, -1, 1, -1, 0, 1]
													__SCREAMING_SNAKE_CASE									= True  # Make those cells visited
													for k in range(8		):
																				if self.is_safe(i + row_nbr[k]				,							j + col_nbr[k]				,							__lowerCAmelCase		):
																											self.diffs(i + row_nbr[k]				,							j + col_nbr[k]				,							__lowerCAmelCase		)






						def 	_A     (   self		):  # And finally, count all islands.







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= [[False for j in range(self.COL		)] for i in range(self.ROW		)]
													__SCREAMING_SNAKE_CASE									= 0
													for i in range(self.ROW		):
																				for j in range(self.COL		):
																											if visited[i][j] is False and self.graph[i][j] == 1:
																																		self.diffs(__lowerCAmelCase				,							__lowerCAmelCase				,							__lowerCAmelCase		)
																																		count += 1
													return count











import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class        UpperCAmelCase_  (       UpperCamelCase_   ,   unittest.TestCase	):

						'''simple docstring'''




						UpperCamelCase__      :			Optional[int]      =  LayoutLMTokenizer
						UpperCamelCase__      :			Any      =  LayoutLMTokenizerFast
						UpperCamelCase__      :			Optional[int]      =  True
						UpperCamelCase__      :			int      =  True






						def 	_A     (   self		):







													'''simple docstring'''

													super().setUp()

													__SCREAMING_SNAKE_CASE									= [
													    '[UNK]',
													    '[CLS]',
													    '[SEP]',
													    'want',
													    '##want',
													    '##ed',
													    'wa',
													    'un',
													    'runn',
													    '##ing',
													    ',',
													    'low',
													    'lowest',
													]
													__SCREAMING_SNAKE_CASE									= os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES['vocab_file']		)
													with open(self.vocab_file				,							'w'				,							encoding='utf-8'		) as vocab_writer:
																				vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]		)		)






						def 	_A     (   self				,							**_A		):







													'''simple docstring'''

													return LayoutLMTokenizer.from_pretrained(self.tmpdirname				,							**_A		)






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= 'UNwant\u00E9d,running'
													__SCREAMING_SNAKE_CASE									= 'unwanted, running'
													return input_text, output_text






						def 	_A     (   self		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= self.tokenizer_class(self.vocab_file		)

													__SCREAMING_SNAKE_CASE									= tokenizer.tokenize('UNwant\u00E9d,running'		)
													self.assertListEqual(_A				,							['un', '##want', '##ed', ',', 'runn', '##ing']		)
													self.assertListEqual(tokenizer.convert_tokens_to_ids(_A		)				,							[7, 4, 5, 10, 8, 9]		)






						def 	_A     (   self		):







													'''simple docstring'''

													pass






