





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


lowercase_					     =	"""▁"""

lowercase_					     =	get_tests_dir("""fixtures/test_sentencepiece.model""")
@require_sentencepiece
@require_tokenizers
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase    ,			unittest.TestCase   ):
   _UpperCamelCase					:	str				      = BigBirdTokenizer
   _UpperCamelCase					:	Optional[Any]				      = BigBirdTokenizerFast
   _UpperCamelCase					:	List[str]				      = True
   _UpperCamelCase					:	Tuple				      = True


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     int:





     """simple docstring"""







     super().setUp()

     lowercase__			    =						self.tokenizer_class(a    ,  keep_accents=a )
     tokenizer.save_pretrained(self.tmpdirname )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Dict:





     """simple docstring"""







     lowercase__			    =						'<s>'
     lowercase__			    =						1

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


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





     """simple docstring"""







     lowercase__			    =						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  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Union[str, Any]:





     """simple docstring"""







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


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Optional[Any]:





     """simple docstring"""







     if not self.test_rust_tokenizer:
       return

     lowercase__			    =						self.get_tokenizer()
     lowercase__			    =						self.get_rust_tokenizer()

     lowercase__			    =						'I was born in 92000, and this is falsé.'

     lowercase__			    =						tokenizer.tokenize(a )
     lowercase__			    =						rust_tokenizer.tokenize(a )
     self.assertListEqual(a    ,  a )

     lowercase__			    =						tokenizer.encode(a    ,  add_special_tokens=a )
     lowercase__			    =						rust_tokenizer.encode(a    ,  add_special_tokens=a )
     self.assertListEqual(a    ,  a )

     lowercase__			    =						self.get_rust_tokenizer()
     lowercase__			    =						tokenizer.encode(a )
     lowercase__			    =						rust_tokenizer.encode(a )
     self.assertListEqual(a    ,  a )


   def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     str:





     """simple docstring"""







     lowercase__			    =						BigBirdTokenizer(a    ,  keep_accents=a )

     lowercase__			    =						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]    ,  )

     lowercase__			    =						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',
             '.',
         ]    ,  )
     lowercase__			    =						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]    ,  )

     lowercase__			    =						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  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     Any:





     """simple docstring"""







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


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





     """simple docstring"""







     lowercase__			    =						'Hello World!'
     lowercase__			    =						[65, 18_536, 2_260, 101, 66]

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


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





     """simple docstring"""







     lowercase__			    =						(
         '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
     lowercase__			    =						[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  SCREAMING_SNAKE_CASE_							(					self    :       Tuple )->     Dict:





     """simple docstring"""







     import torch

     from transformers import BigBirdConfig, BigBirdModel

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

     lowercase__			    =						BigBirdConfig(attention_type='original_full' )
     lowercase__			    =						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  SCREAMING_SNAKE_CASE_							(					self    :       int )->     Dict:





     """simple docstring"""







     lowercase__			    =						BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base' )
     lowercase__			    =						tokenizer.decode(tokenizer('Paris is the [MASK].' ).input_ids )

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


   @slow
   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int] )->     List[Any]:





     """simple docstring"""







     lowercase__			    =						{'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'    ,  )









from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class        SCREAMING_SNAKE_CASE     (UpperCAmelCase   ):
   _UpperCamelCase					:	Tuple				      = 'ClapFeatureExtractor'
   _UpperCamelCase					:	Union[str, Any]				      = ('RobertaTokenizer', 'RobertaTokenizerFast')


   def __init__(					self    :       List[Any]    ,  a    :       int    ,  a    :       str )->     Any:





     """simple docstring"""







     super().__init__(a    ,  a )


   def __call__(					self    :       Any    ,  a    :       Tuple=None    ,  a    :       Optional[int]=None    ,  a    :       int=None    ,  **a    :       Optional[int] )->     Union[str, Any]:





     """simple docstring"""







     lowercase__			    =						kwargs.pop('sampling_rate'    ,  a )

     if text is None and audios is None:
       raise ValueError('You have to specify either text or audios. Both cannot be none.' )

     if text is not None:
       lowercase__			    =						self.tokenizer(a    ,  return_tensors=a    ,  **a )

     if audios is not None:
       lowercase__			    =						self.feature_extractor(
           a    ,  sampling_rate=a    ,  return_tensors=a    ,  **a )

     if text is not None and audios is not None:
       lowercase__			    =						audio_features.input_features
       return encoding
     elif text is not None:
       return encoding
     else:
       return BatchEncoding(data=dict(**a )    ,  tensor_type=a )


   def  SCREAMING_SNAKE_CASE_							(					self    :       str    ,  *a    :       Dict    ,  **a    :       int )->     Optional[int]:





     """simple docstring"""







     return self.tokenizer.batch_decode(*a    ,  **a )


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[Any]    ,  *a    :       int    ,  **a    :       Dict )->     Dict:





     """simple docstring"""







     return self.tokenizer.decode(*a    ,  **a )


   @property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any] )->     Optional[int]:





     """simple docstring"""







     lowercase__			    =						self.tokenizer.model_input_names
     lowercase__			    =						self.feature_extractor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names ) )


