


'''simple docstring'''



import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCAmelCase    :str				       =     "▁"

__UpperCAmelCase    :Dict				       =     get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class 			a       (	__a			,						unittest.TestCase ):


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				str							     =     BigBirdTokenizer
     SCREAMING_SNAKE_CASE :				Any							     =     BigBirdTokenizerFast
     SCREAMING_SNAKE_CASE :				int							     =     True
     SCREAMING_SNAKE_CASE :				str							     =     True

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Optional[Any]:
          super().setUp()

          __UpperCAmelCase			:				Union[str, Any]													=    self.tokenizer_class(a_							,				keep_accents=a_    )
          tokenizer.save_pretrained(self.tmpdirname    )

     def 				lowerCamelCase__				(       self  :	Any    )		->							Any:
          __UpperCAmelCase			:				Any													=    """<s>"""
          __UpperCAmelCase			:				List[Any]													=    1

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

     def 				lowerCamelCase__				(       self  :	List[str]    )		->							Tuple:
          __UpperCAmelCase			:				Tuple													=    list(self.get_tokenizer().get_vocab().keys()    )

          self.assertEqual(vocab_keys[0]							,				'''<unk>'''    )
          self.assertEqual(vocab_keys[1]							,				'''<s>'''    )
          self.assertEqual(vocab_keys[-1]							,				'''[MASK]'''    )
          self.assertEqual(len(a_    )							,				1004    )

     def 				lowerCamelCase__				(       self  :	int    )		->							Any:
          self.assertEqual(self.get_tokenizer().vocab_size							,				1000    )

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Tuple:



          if not self.test_rust_tokenizer:
               return

          __UpperCAmelCase			:				Optional[int]													=    self.get_tokenizer()
          __UpperCAmelCase			:				Any													=    self.get_rust_tokenizer()

          __UpperCAmelCase			:				Optional[Any]													=    """I was born in 92000, and this is falsé."""

          __UpperCAmelCase			:				Tuple													=    tokenizer.tokenize(a_    )
          __UpperCAmelCase			:				Tuple													=    rust_tokenizer.tokenize(a_    )
          self.assertListEqual(a_							,				a_    )

          __UpperCAmelCase			:				List[str]													=    tokenizer.encode(a_							,				add_special_tokens=a_    )
          __UpperCAmelCase			:				Optional[Any]													=    rust_tokenizer.encode(a_							,				add_special_tokens=a_    )
          self.assertListEqual(a_							,				a_    )

          __UpperCAmelCase			:				Tuple													=    self.get_rust_tokenizer()
          __UpperCAmelCase			:				Union[str, Any]													=    tokenizer.encode(a_    )
          __UpperCAmelCase			:				Optional[Any]													=    rust_tokenizer.encode(a_    )
          self.assertListEqual(a_							,				a_    )

     def 				lowerCamelCase__				(       self  :	str    )		->							Optional[int]:
          __UpperCAmelCase			:				int													=    BigBirdTokenizer(a_							,				keep_accents=a_    )

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

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

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

          __UpperCAmelCase			:				Optional[Any]													=    tokenizer.convert_ids_to_tokens(a_    )
          self.assertListEqual(
              a_							,				[
                  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  :	str    )		->							Optional[Any]:
          return BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''    )

     @slow
     def 				lowerCamelCase__				(       self  :	Union[str, Any]    )		->							Optional[int]:
          __UpperCAmelCase			:				Union[str, Any]													=    """Hello World!"""
          __UpperCAmelCase			:				List[str]													=    [65, 1_8536, 2260, 101, 66]

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

     @slow
     def 				lowerCamelCase__				(       self  :	Dict    )		->							str:
          __UpperCAmelCase			:				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"""
          )
          # fmt: off
          __UpperCAmelCase			:				Union[str, Any]													=    [65, 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, 66]  # noqa: E231
          # fmt: on
          self.assertListEqual(a_							,				self.big_tokenizer.encode(a_    )    )

     @require_torch
     @slow
     def 				lowerCamelCase__				(       self  :	Union[str, Any]    )		->							Optional[Any]:
          import torch

          from transformers import BigBirdConfig, BigBirdModel

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

          __UpperCAmelCase			:				Any													=    BigBirdConfig(attention_type='''original_full'''    )
          __UpperCAmelCase			:				str													=    BigBirdModel(a_    )

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

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

     @slow
     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Optional[Any]:
          __UpperCAmelCase			:				Optional[Any]													=    BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''    )
          __UpperCAmelCase			:				Optional[int]													=    tokenizer.decode(tokenizer('''Paris is the [MASK].'''    ).input_ids    )

          self.assertTrue(decoded_text == '''[CLS] Paris is the[MASK].[SEP]'''    )






     @slow
     def 				lowerCamelCase__				(       self  :	Union[str, Any]    )		->							Optional[Any]:
          __UpperCAmelCase			:				Any													=    {"""input_ids""": [[65, 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, 66], [65, 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, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 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=a_							,				model_name='''google/bigbird-roberta-base'''							,				revision='''215c99f1600e06f83acce68422f2035b2b5c3510'''							,				)



'''simple docstring'''



from typing import TYPE_CHECKING

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


__UpperCAmelCase    :Optional[Any]				       =     {
    "configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
    "processing_layoutlmv2": ["LayoutLMv2Processor"],
    "tokenization_layoutlmv2": ["LayoutLMv2Tokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :Any				       =     ["LayoutLMv2TokenizerFast"]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :int				       =     ["LayoutLMv2FeatureExtractor"]
      __UpperCAmelCase    :Optional[int]				       =     ["LayoutLMv2ImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase    :List[Any]				       =     [
          "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST",
          "LayoutLMv2ForQuestionAnswering",
          "LayoutLMv2ForSequenceClassification",
          "LayoutLMv2ForTokenClassification",
          "LayoutLMv2Layer",
          "LayoutLMv2Model",
          "LayoutLMv2PreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaLayer,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )
else:
      import sys

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