


'''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


__UpperCAmelCase      :Tuple			    =       "▁"

__UpperCAmelCase      :List[str]			    =       get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
class      a    (		_a     ,  unittest.TestCase	):


     """simple docstring"""






     SCREAMING_SNAKE_CASE	:			Optional[int]							       =       BertGenerationTokenizer
     SCREAMING_SNAKE_CASE	:			List[Any]							       =       False
     SCREAMING_SNAKE_CASE	:			Optional[int]							       =       True

     def 			lowerCamelCase__			(    self					:		str      )						->							str:
          super().setUp()

          __UpperCAmelCase     :			int  							=      BertGenerationTokenizer(__UpperCAmelCase							,			keep_accents=__UpperCAmelCase      )
          tokenizer.save_pretrained(self.tmpdirname      )

     def 			lowerCamelCase__			(    self					:		int      )						->							Dict:
          __UpperCAmelCase     :			str  							=      '''<s>'''
          __UpperCAmelCase     :			List[Any]  							=      1

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

     def 			lowerCamelCase__			(    self					:		List[Any]      )						->							str:
          __UpperCAmelCase     :			List[Any]  							=      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(__UpperCAmelCase      )							,			1002      )

     def 			lowerCamelCase__			(    self					:		List[str]      )						->							List[Any]:
          self.assertEqual(self.get_tokenizer().vocab_size							,			1000      )

     def 			lowerCamelCase__			(    self					:		Tuple      )						->							Optional[int]:
          __UpperCAmelCase     :			Tuple  							=      BertGenerationTokenizer(__UpperCAmelCase							,			keep_accents=__UpperCAmelCase      )

          __UpperCAmelCase     :			List[str]  							=      tokenizer.tokenize('''This is a test'''      )
          self.assertListEqual(__UpperCAmelCase							,			['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']      )

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

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

          __UpperCAmelCase     :			Any  							=      tokenizer.convert_ids_to_tokens(__UpperCAmelCase      )
          self.assertListEqual(
              __UpperCAmelCase							,			[
                  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 			lowerCamelCase__			(    self					:		List[Any]      )						->							List[str]:
          return BertGenerationTokenizer.from_pretrained('''google/bert_for_seq_generation_L-24_bbc_encoder'''      )

     @slow
     def 			lowerCamelCase__			(    self					:		Any      )						->							str:
          __UpperCAmelCase     :			Dict  							=      '''Hello World!'''
          __UpperCAmelCase     :			str  							=      [1_8536, 2260, 101]

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

     @slow
     def 			lowerCamelCase__			(    self					:		List[Any]      )						->							str:
          __UpperCAmelCase     :			Union[str, Any]  							=      (
              '''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'''
          )
          __UpperCAmelCase     :			int  							=      [
              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(__UpperCAmelCase							,			self.big_tokenizer.encode(__UpperCAmelCase      )      )

     @require_torch
     @slow
     def 			lowerCamelCase__			(    self					:		Any      )						->							Dict:
          import torch

          from transformers import BertGenerationConfig, BertGenerationEncoder

          # Build sequence
          __UpperCAmelCase     :			Optional[Any]  							=      list(self.big_tokenizer.get_vocab().keys()      )[:10]
          __UpperCAmelCase     :			Optional[Any]  							=      ''' '''.join(__UpperCAmelCase      )
          __UpperCAmelCase     :			Tuple  							=      self.big_tokenizer.encode_plus(__UpperCAmelCase							,			return_tensors='''pt'''							,			return_token_type_ids=__UpperCAmelCase      )
          __UpperCAmelCase     :			Dict  							=      self.big_tokenizer.batch_encode_plus(
              [sequence + ''' ''' + sequence]							,			return_tensors='''pt'''							,			return_token_type_ids=__UpperCAmelCase      )

          __UpperCAmelCase     :			Optional[int]  							=      BertGenerationConfig()
          __UpperCAmelCase     :			Dict  							=      BertGenerationEncoder(__UpperCAmelCase      )

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

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






     @slow
     def 			lowerCamelCase__			(    self					:		str      )						->							Optional[Any]:
          __UpperCAmelCase     :			str  							=      {'''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=__UpperCAmelCase							,			model_name='''google/bert_for_seq_generation_L-24_bbc_encoder'''							,			revision='''c817d1fd1be2ffa69431227a1fe320544943d4db'''							,			)



'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCAmelCase      :List[Any]			    =       {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       ["LxmertTokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       [
          "LxmertEncoder",
          "LxmertForPreTraining",
          "LxmertForQuestionAnswering",
          "LxmertModel",
          "LxmertPreTrainedModel",
          "LxmertVisualFeatureEncoder",
          "LxmertXLayer",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[str]			    =       [
          "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFLxmertForPreTraining",
          "TFLxmertMainLayer",
          "TFLxmertModel",
          "TFLxmertPreTrainedModel",
          "TFLxmertVisualFeatureEncoder",
      ]


if TYPE_CHECKING:
      from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
      from .tokenization_lxmert import LxmertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_lxmert_fast import LxmertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_lxmert import (
                LxmertEncoder,
                LxmertForPreTraining,
                LxmertForQuestionAnswering,
                LxmertModel,
                LxmertPreTrainedModel,
                LxmertVisualFeatureEncoder,
                LxmertXLayer,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_lxmert import (
                TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFLxmertForPreTraining,
                TFLxmertMainLayer,
                TFLxmertModel,
                TFLxmertPreTrainedModel,
                TFLxmertVisualFeatureEncoder,
            )

else:
      import sys

      __UpperCAmelCase      :int			    =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)