



"""simple docstring"""







import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


A    =			'▁'

A    =			get_tests_dir('fixtures/test_sentencepiece.model')






@require_sentencepiece
class      UpperCAmelCase__		(      UpperCamelCase   ,unittest.TestCase     ):
		lowerCAmelCase_       :	Union[str, Any] 							=     BertGenerationTokenizer
		lowerCAmelCase_       :	Any 							=     False
		lowerCAmelCase_       :	Optional[int] 							=     True



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






									'''simple docstring'''

									super().setUp()

									A         =					BertGenerationTokenizer(snake_case      ,							keep_accents=snake_case				)
									tokenizer.save_pretrained(self.tmpdirname				)



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






									'''simple docstring'''

									A         =					'<s>'
									A         =					1

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



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






									'''simple docstring'''

									A         =					list(self.get_tokenizer().get_vocab().keys()				)

									self.assertEqual(vocab_keys[0]      ,							'<unk>'				)
									self.assertEqual(vocab_keys[1]      ,							'<s>'				)
									self.assertEqual(vocab_keys[-1]      ,							'<pad>'				)
									self.assertEqual(len(snake_case				)      ,							1_002				)



		def 					A_		( self  :    int				)			->						str:






									'''simple docstring'''

									self.assertEqual(self.get_tokenizer().vocab_size      ,							1_000				)



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






									'''simple docstring'''

									A         =					BertGenerationTokenizer(snake_case      ,							keep_accents=snake_case				)

									A         =					tokenizer.tokenize('This is a test'				)
									self.assertListEqual(snake_case      ,							['▁This', '▁is', '▁a', '▁t', 'est']				)

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(snake_case				)      ,							[285, 46, 10, 170, 382]      ,							)

									A         =					tokenizer.tokenize('I was born in 92000, and this is falsé.'				)
									self.assertListEqual(
									    snake_case      ,							[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '9',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        'é',
									        '.',
									    ]      ,							)
									A         =					tokenizer.convert_tokens_to_ids(snake_case				)
									self.assertListEqual(
									    snake_case      ,							[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]      ,							)

									A         =					tokenizer.convert_ids_to_tokens(snake_case				)
									self.assertListEqual(
									    snake_case      ,							[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '<unk>',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        '<unk>',
									        '.',
									    ]      ,							)



		@cached_property
		def 					A_		( self  :    Tuple				)			->						str:






									'''simple docstring'''

									return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'				)



		@slow
		def 					A_		( self  :    Optional[int]				)			->						Optional[int]:






									'''simple docstring'''

									A         =					'Hello World!'
									A         =					[18_536, 2_260, 101]

									self.assertListEqual(snake_case      ,							self.big_tokenizer.encode(snake_case				)				)



		@slow
		def 					A_		( self  :    str				)			->						Tuple:






									'''simple docstring'''

									A         =					(
									    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
									    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
									)
									A         =					[
									    871,
									    419,
									    358,
									    946,
									    991,
									    2_521,
									    452,
									    358,
									    1_357,
									    387,
									    7_751,
									    3_536,
									    112,
									    985,
									    456,
									    126,
									    865,
									    938,
									    5_400,
									    5_734,
									    458,
									    1_368,
									    467,
									    786,
									    2_462,
									    5_246,
									    1_159,
									    633,
									    865,
									    4_519,
									    457,
									    582,
									    852,
									    2_557,
									    427,
									    916,
									    508,
									    405,
									    34_324,
									    497,
									    391,
									    408,
									    11_342,
									    1_244,
									    385,
									    100,
									    938,
									    985,
									    456,
									    574,
									    362,
									    12_597,
									    3_200,
									    3_129,
									    1_172,
									]

									self.assertListEqual(snake_case      ,							self.big_tokenizer.encode(snake_case				)				)



		@require_torch
		@slow
		def 					A_		( self  :    Dict				)			->						Dict:






									'''simple docstring'''

									import torch

									from transformers import BertGenerationConfig, BertGenerationEncoder

									# Build sequence
									A         =					list(self.big_tokenizer.get_vocab().keys()				)[:10]
									A         =					' '.join(snake_case				)
									A         =					self.big_tokenizer.encode_plus(snake_case      ,							return_tensors='pt'      ,							return_token_type_ids=snake_case				)
									A         =					self.big_tokenizer.batch_encode_plus(
									    [sequence + ' ' + sequence]      ,							return_tensors='pt'      ,							return_token_type_ids=snake_case				)

									A         =					BertGenerationConfig()
									A         =					BertGenerationEncoder(snake_case				)

									assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

									with torch.no_grad():
																model(**snake_case				)
																model(**snake_case				)



		@slow
		def 					A_		( self  :    Optional[Any]				)			->						List[str]:






									'''simple docstring'''

									A         =					{'input_ids': [[39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114], [448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=snake_case      ,							model_name='google/bert_for_seq_generation_L-24_bbc_encoder'      ,							revision='c817d1fd1be2ffa69431227a1fe320544943d4db'      ,							)








"""simple docstring"""







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     ):
		lowerCAmelCase_       :	Tuple 							=     LayoutLMTokenizer
		lowerCAmelCase_       :	Any 							=     LayoutLMTokenizerFast
		lowerCAmelCase_       :	Optional[int] 							=     True
		lowerCAmelCase_       :	List[Any] 							=     True



		def 					A_		( self  :    Optional[Any]				)			->						Optional[Any]:






									'''simple docstring'''

									super().setUp()

									A         =					[
									    '[UNK]',
									    '[CLS]',
									    '[SEP]',
									    'want',
									    '##want',
									    '##ed',
									    'wa',
									    'un',
									    'runn',
									    '##ing',
									    ',',
									    'low',
									    'lowest',
									]
									A         =					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  :    str      ,							**snake_case  :    Tuple				)			->						Union[str, Any]:






									'''simple docstring'''

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



		def 					A_		( self  :    List[str]      ,							snake_case  :    int				)			->						List[Any]:






									'''simple docstring'''

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



		def 					A_		( self  :    Tuple				)			->						Optional[int]:






									'''simple docstring'''

									A         =					self.tokenizer_class(self.vocab_file				)

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



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






									'''simple docstring'''

									pass



