





"""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 		__snake_case (		a__							,							unittest.TestCase					):





 """simple docstring"""


 _lowerCamelCase				=					BertGenerationTokenizer
 _lowerCamelCase				=					False
 _lowerCamelCase				=					True

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     super().setUp()

     __A   :						Optional[int]									=					BertGenerationTokenizer(_lowerCamelCase ,						keep_accents=_lowerCamelCase  )
     tokenizer.save_pretrained(self.tmpdirname  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[str]									=					'''<s>'''
     __A   :						Optional[Any]									=					1

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

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						int									=					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(_lowerCamelCase  ) ,						1002  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     self.assertEqual(self.get_tokenizer().vocab_size ,						1000  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Dict									=					BertGenerationTokenizer(_lowerCamelCase ,						keep_accents=_lowerCamelCase  )

     __A   :						Optional[int]									=					tokenizer.tokenize('''This is a test'''  )
     self.assertListEqual(_lowerCamelCase ,						['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']  )

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

     __A   :						str									=					tokenizer.tokenize('''I was born in 92000, and this is falsé.'''  )
     self.assertListEqual(
         _lowerCamelCase ,						[
             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   :						Optional[Any]									=					tokenizer.convert_tokens_to_ids(_lowerCamelCase  )
     self.assertListEqual(
         _lowerCamelCase ,						[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4] ,						)

     __A   :						Any									=					tokenizer.convert_ids_to_tokens(_lowerCamelCase  )
     self.assertListEqual(
         _lowerCamelCase ,						[
             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  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[Any]									=					'''Hello World!'''
     __A   :						Union[str, Any]									=					[1_8536, 2260, 101]

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

 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[str]									=					(
         '''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   :						List[str]									=					[
         871,
         419,
         358,
         946,
         991,
         2521,
         452,
         358,
         1357,
         387,
         7751,
         3536,
         112,
         985,
         456,
         126,
         865,
         938,
         5400,
         5734,
         458,
         1368,
         467,
         786,
         2462,
         5246,
         1159,
         633,
         865,
         4519,
         457,
         582,
         852,
         2557,
         427,
         916,
         508,
         405,
         3_4324,
         497,
         391,
         408,
         1_1342,
         1244,
         385,
         100,
         938,
         985,
         456,
         574,
         362,
         1_2597,
         3200,
         3129,
         1172,
     ]

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

 @require_torch
 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     import torch

     from transformers import BertGenerationConfig, BertGenerationEncoder

     # Build sequence
     __A   :						List[str]									=					list(self.big_tokenizer.get_vocab().keys()  )[:10]
     __A   :						str									=					''' '''.join(_lowerCamelCase  )
     __A   :						Dict									=					self.big_tokenizer.encode_plus(_lowerCamelCase ,						return_tensors='''pt''' ,						return_token_type_ids=_lowerCamelCase  )
     __A   :						Dict									=					self.big_tokenizer.batch_encode_plus(
         [sequence + ''' ''' + sequence] ,						return_tensors='''pt''' ,						return_token_type_ids=_lowerCamelCase  )

     __A   :						Dict									=					BertGenerationConfig()
     __A   :						str									=					BertGenerationEncoder(_lowerCamelCase  )

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

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







 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						int									=					{'''input_ids''': [[3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114], [448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 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, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 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=_lowerCamelCase ,						model_name='''google/bert_for_seq_generation_L-24_bbc_encoder''' ,						revision='''c817d1fd1be2ffa69431227a1fe320544943d4db''' ,						)











"""simple docstring"""



from typing import TYPE_CHECKING

from ....utils import _LazyModule


a_			=      {"""tokenization_tapex""": ["""TapexTokenizer"""]}


if TYPE_CHECKING:
       from .tokenization_tapex import TapexTokenizer


else:
       import sys

       a_			=      _LazyModule(__name__, globals()["""__file__"""], _import_structure)




