

'''simple docstring'''
import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase :      Tuple					 =     get_tests_dir("fixtures/spiece.model")







@require_sentencepiece
@require_tokenizers
class 							A__    (       A__     ,   unittest.TestCase  ):
  A__		 =				DebertaVaTokenizer
  A__		 =				DebertaVaTokenizerFast
  A__		 =				True
  A__		 =				True





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





       '''simple docstring'''






       super().setUp()

       # We have a SentencePiece fixture for testing
       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					unk_token='<unk>' )
       tokenizer.save_pretrained(self.tmpdirname )





  def 						A  (		self      :	List[str]							,					_a      :	int )	->    Optional[Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='this is a test'
       _SCREAMING_SNAKE_CASE							    ='this is a test'
       return input_text, output_text





  def 						A  (		self      :	List[str] )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='<pad>'
       _SCREAMING_SNAKE_CASE							    =0

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





  def 						A  (		self      :	Optional[Any] )	->    List[str]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =list(self.get_tokenizer().get_vocab().keys() )
       self.assertEqual(vocab_keys[0]							,					'<pad>' )
       self.assertEqual(vocab_keys[1]							,					'<unk>' )
       self.assertEqual(vocab_keys[-1]							,					'[PAD]' )
       self.assertEqual(len(_a )							,					3_0001 )





  def 						A  (		self      :	Tuple )	->    Any:





       '''simple docstring'''






       self.assertEqual(self.get_tokenizer().vocab_size							,					3_0000 )





  def 						A  (		self      :	List[Any] )	->    List[str]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =' \tHeLLo!how  \n Are yoU?  '
       _SCREAMING_SNAKE_CASE							    =['▁hello', '!', 'how', '▁are', '▁you', '?']
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					do_lower_case=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					do_lower_case=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )





  @unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.' )
  def 						A  (		self      :	Any )	->    Union[str, Any]:





       '''simple docstring'''






       pass





  @unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.' )
  def 						A  (		self      :	Union[str, Any] )	->    List[Any]:





       '''simple docstring'''






       pass





  def 						A  (		self      :	Any )	->    int:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='I was born in 92000, and this is falsé.'
       _SCREAMING_SNAKE_CASE							    =['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', '▁', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '▁', '.', ]
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )





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





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='I was born in 92000, and this is falsé.'
       _SCREAMING_SNAKE_CASE							    =['▁i', '▁was', '▁born', '▁in', '▁9', '2000', '▁', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '▁', '.', ]
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )
       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )
       self.assertListEqual(_a							,					_a )





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





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='I was born in 92000, and this is falsé.'
       _SCREAMING_SNAKE_CASE							    =['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.', ]
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )





  def 						A  (		self      :	Optional[int] )	->    Any:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='I was born in 92000, and this is falsé.'
       _SCREAMING_SNAKE_CASE							    =['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', '▁', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '▁', '.', ]
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )





  def 						A  (		self      :	Union[str, Any] )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =' \tHeLLo!how  \n Are yoU?  '
       _SCREAMING_SNAKE_CASE							    =['▁', '<unk>', 'e', '<unk>', 'o', '!', 'how', '▁', '<unk>', 're', '▁yo', '<unk>', '?']
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					do_lower_case=_a							,					split_by_punct=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )

       self.assertListEqual(_a							,					_a )





  def 						A  (		self      :	Tuple )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =self.get_tokenizer()
       _SCREAMING_SNAKE_CASE							    =self.get_rust_tokenizer()

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

       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(tokenizer.encode(_a							,					add_special_tokens=_a ) )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_a							,					add_special_tokens=_a ) )
       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =tokenizer.encode(_a							,					add_special_tokens=_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.encode(_a							,					add_special_tokens=_a )
       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =self.get_rust_tokenizer()
       _SCREAMING_SNAKE_CASE							    =tokenizer.encode(_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.encode(_a )
       self.assertListEqual(_a							,					_a )





  def 						A  (		self      :	Optional[int] )	->    str:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ='This is a test'
       _SCREAMING_SNAKE_CASE							    =[13, 1, 4398, 25, 21, 1289]
       _SCREAMING_SNAKE_CASE							    =['▁', 'T', 'his', '▁is', '▁a', '▁test']
       _SCREAMING_SNAKE_CASE							    =['▁', '<unk>', 'his', '▁is', '▁a', '▁test']

       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a							,					keep_accents=_a )
       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizerFast(_a							,					keep_accents=_a )

       _SCREAMING_SNAKE_CASE							    =tokenizer.encode(_a							,					add_special_tokens=_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.tokenize(_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(_a )
       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.encode(_a							,					add_special_tokens=_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.tokenize(_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(_a )
       self.assertListEqual(_a							,					_a )

       # fmt: off
       _SCREAMING_SNAKE_CASE							    ='I was born in 92000, and this is falsé.'
       _SCREAMING_SNAKE_CASE							    =[13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
       _SCREAMING_SNAKE_CASE							    =['▁', 'I', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.', ]
       _SCREAMING_SNAKE_CASE							    =['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.', ]
       # fmt: on

       _SCREAMING_SNAKE_CASE							    =tokenizer.encode(_a							,					add_special_tokens=_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.tokenize(_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.convert_ids_to_tokens(_a )
       self.assertListEqual(_a							,					_a )

       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.encode(_a							,					add_special_tokens=_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.tokenize(_a )
       self.assertListEqual(_a							,					_a )
       _SCREAMING_SNAKE_CASE							    =rust_tokenizer.convert_ids_to_tokens(_a )
       self.assertListEqual(_a							,					_a )





  def 						A  (		self      :	Tuple )	->    Union[str, Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =DebertaVaTokenizer(_a )

       _SCREAMING_SNAKE_CASE							    =tokenizer.encode('sequence builders' )
       _SCREAMING_SNAKE_CASE							    =tokenizer.encode('multi-sequence build' )

       _SCREAMING_SNAKE_CASE							    =tokenizer.build_inputs_with_special_tokens(_a )
       _SCREAMING_SNAKE_CASE							    =tokenizer.build_inputs_with_special_tokens(_a							,					_a )

       self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]							,					_a )
       self.assertEqual(
           [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]							,					_a							,					)





  @slow
  def 						A  (		self      :	int )	->    Dict:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ={'input_ids': [[1, 3_9867, 36, 1_9390, 486, 27, 3_5052, 8_1436, 18, 6_0685, 1225, 7, 3_5052, 8_1436, 18, 9367, 1_6899, 18, 1_5937, 53, 594, 773, 18, 1_6287, 3_0465, 36, 1_5937, 6, 4_1139, 38, 3_6979, 6_0763, 191, 6, 3_4132, 99, 6, 5_0538, 390, 4_3230, 6, 3_4132, 2779, 2_0850, 14, 699, 1072, 1194, 36, 382, 1_0901, 53, 7, 699, 1072, 2084, 36, 2_0422, 630, 53, 19, 105, 3049, 1896, 1053, 1_6899, 1506, 11, 3_7978, 4243, 7, 1237, 3_1869, 200, 1_6566, 654, 6, 3_5052, 8_1436, 7, 5_5630, 1_3593, 4, 2], [1, 26, 1_5011, 13, 667, 8, 1053, 18, 2_3611, 1237, 7_2356, 1_2820, 34, 10_4134, 1209, 35, 1_3313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 1232, 2864, 1_5785, 1_4951, 105, 5, 8581, 1250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=_a							,					model_name='microsoft/deberta-v2-xlarge'							,					revision='ad6e42c1532ddf3a15c39246b63f5559d558b670'							,					)



'''simple docstring'''
from typing import TYPE_CHECKING

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


lowerCamelCase :      Any					 =     {
    "configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
    "convert_funnel_original_tf_checkpoint_to_pytorch": [],
    "tokenization_funnel": ["FunnelTokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase :      Optional[Any]					 =     ["FunnelTokenizerFast"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase :      List[str]					 =     [
         "FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
         "FunnelBaseModel",
         "FunnelForMaskedLM",
         "FunnelForMultipleChoice",
         "FunnelForPreTraining",
         "FunnelForQuestionAnswering",
         "FunnelForSequenceClassification",
         "FunnelForTokenClassification",
         "FunnelModel",
         "FunnelPreTrainedModel",
         "load_tf_weights_in_funnel",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase :      Union[str, Any]					 =     [
         "TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFFunnelBaseModel",
         "TFFunnelForMaskedLM",
         "TFFunnelForMultipleChoice",
         "TFFunnelForPreTraining",
         "TFFunnelForQuestionAnswering",
         "TFFunnelForSequenceClassification",
         "TFFunnelForTokenClassification",
         "TFFunnelModel",
         "TFFunnelPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
     from .tokenization_funnel import FunnelTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_funnel_fast import FunnelTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_funnel import (
              FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
              FunnelBaseModel,
              FunnelForMaskedLM,
              FunnelForMultipleChoice,
              FunnelForPreTraining,
              FunnelForQuestionAnswering,
              FunnelForSequenceClassification,
              FunnelForTokenClassification,
              FunnelModel,
              FunnelPreTrainedModel,
              load_tf_weights_in_funnel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_funnel import (
              TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFFunnelBaseModel,
              TFFunnelForMaskedLM,
              TFFunnelForMultipleChoice,
              TFFunnelForPreTraining,
              TFFunnelForQuestionAnswering,
              TFFunnelForSequenceClassification,
              TFFunnelForTokenClassification,
              TFFunnelModel,
              TFFunnelPreTrainedModel,
          )

else:
     import sys

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