




'''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_    	=				"▁"

UpperCamelCase_    	=				get_tests_dir("fixtures/test_sentencepiece.model")






@require_sentencepiece
@require_tokenizers
class 							_a				(			SCREAMING_SNAKE_CASE ,      unittest.TestCase ):





       '''simple docstring'''






       A						:				Dict        =						BigBirdTokenizer
       A						:				Any        =						BigBirdTokenizerFast
       A						:				Optional[int]        =						True
       A						:				Any        =						True







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             super().setUp()

             SCREAMING_SNAKE_CASE   :      Tuple    					=						self.tokenizer_class(A,							keep_accents=A  )
             tokenizer.save_pretrained(self.tmpdirname  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						'<s>'
             SCREAMING_SNAKE_CASE   :      int    					=						1

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







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Union[str, 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],							'[MASK]'  )
             self.assertEqual(len(A  ),							1_004  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







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







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             if not self.test_rust_tokenizer:
                   return

             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.get_tokenizer()
             SCREAMING_SNAKE_CASE   :      Any    					=						self.get_rust_tokenizer()

             SCREAMING_SNAKE_CASE   :      List[str]    					=						'I was born in 92000, and this is falsé.'

             SCREAMING_SNAKE_CASE   :      List[str]    					=						tokenizer.tokenize(A  )
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						rust_tokenizer.tokenize(A  )
             self.assertListEqual(A,							A  )

             SCREAMING_SNAKE_CASE   :      Dict    					=						tokenizer.encode(A,							add_special_tokens=A  )
             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						rust_tokenizer.encode(A,							add_special_tokens=A  )
             self.assertListEqual(A,							A  )

             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						self.get_rust_tokenizer()
             SCREAMING_SNAKE_CASE   :      Tuple    					=						tokenizer.encode(A  )
             SCREAMING_SNAKE_CASE   :      Dict    					=						rust_tokenizer.encode(A  )
             self.assertListEqual(A,							A  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      int    					=						BigBirdTokenizer(A,							keep_accents=A  )

             SCREAMING_SNAKE_CASE   :      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],							)

             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						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',
                     '.',
                 ],							)
             SCREAMING_SNAKE_CASE   :      List[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],							)

             SCREAMING_SNAKE_CASE   :      str    					=						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        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             return BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'  )







       @slow
       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[Any]    					=						'Hello World!'
             SCREAMING_SNAKE_CASE   :      int    					=						[65, 18_536, 2_260, 101, 66]

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







       @slow
       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Tuple    					=						(
                 '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
             SCREAMING_SNAKE_CASE   :      int    					=						[65, 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, 66]  # noqa: E231
             # fmt: on
             self.assertListEqual(A,							self.big_tokenizer.encode(A  )  )







       @require_torch
       @slow
       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             import torch

             from transformers import BigBirdConfig, BigBirdModel

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

             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						BigBirdConfig(attention_type='original_full'  )
             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						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        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Tuple    					=						BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'  )
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						tokenizer.decode(tokenizer('Paris is the [MASK].'  ).input_ids  )

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







       @slow
       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						{'input_ids': [[65, 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, 66], [65, 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, 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, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 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_torch_available


__snake_case    					=					{'configuration_mmbt': ['MMBTConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case    					=					['MMBTForClassification', 'MMBTModel', 'ModalEmbeddings']


if TYPE_CHECKING:
   from .configuration_mmbt import MMBTConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
   import sys

   __snake_case    					=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)