



'''simple docstring'''





import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class __A     (    A  ,  unittest.TestCase		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[int]		=			FunnelTokenizer
 __lowerCamelCase       :			Optional[Any]		=			FunnelTokenizerFast
 __lowerCamelCase       :			Union[str, Any]		=			True
 __lowerCamelCase       :			Optional[int]		=			True



 def    a__    (self			)       ->	Optional[Any]:


      """simple docstring"""



      super().setUp()

      _a           =    [
          '''<unk>''',
          '''<cls>''',
          '''<sep>''',
          '''want''',
          '''##want''',
          '''##ed''',
          '''wa''',
          '''un''',
          '''runn''',
          '''##ing''',
          ''',''',
          '''low''',
          '''lowest''',
      ]
      _a           =    os.path.join(self.tmpdirname					,  VOCAB_FILES_NAMES['''vocab_file''']			)
      with open(self.vocab_file					,  '''w'''					,  encoding='''utf-8'''			) as vocab_writer:
           vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]			)			)



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


      """simple docstring"""



      return FunnelTokenizer.from_pretrained(self.tmpdirname					,  **A			)



 def    a__    (self					,  **A			)       ->	Optional[Any]:


      """simple docstring"""



      return FunnelTokenizerFast.from_pretrained(self.tmpdirname					,  **A			)



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


      """simple docstring"""



      _a           =    '''UNwant\u00E9d,running'''
      _a           =    '''unwanted, running'''
      return input_text, output_text



 def    a__    (self			)       ->	Tuple:


      """simple docstring"""



      _a           =    self.tokenizer_class(self.vocab_file			)

      _a           =    tokenizer.tokenize('''UNwant\u00E9d,running'''			)
      self.assertListEqual(A					,  ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']			)
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A			)					,  [7, 4, 5, 10, 8, 9]			)



 def    a__    (self			)       ->	List[Any]:


      """simple docstring"""



      _a           =    self.get_tokenizers(do_lower_case=A			)
      for tokenizer in tokenizers:
           _a           =    tokenizer('''UNwant\u00E9d,running'''			)
           _a           =    len(inputs['''input_ids''']			) - 1
           self.assertListEqual(inputs['''token_type_ids''']					,  [2] + [0] * sentence_len			)

           _a           =    tokenizer('''UNwant\u00E9d,running'''					,  '''UNwant\u00E9d,running'''			)
           self.assertListEqual(inputs['''token_type_ids''']					,  [2] + [0] * sentence_len + [1] * sentence_len			)








'''simple docstring'''





from __future__ import annotations




def lowerCAmelCase    (__A    ,      __A):



     """simple docstring"""



     if len(__A) == 0:
          return False
     _a           =    len(__A) // 2
     if a_list[midpoint] == item:
          return True
     if item < a_list[midpoint]:
          return binary_search(a_list[:midpoint]    ,      __A)
     else:
          return binary_search(a_list[midpoint + 1 :]    ,      __A)


if __name__ == "__main__":
  lowercase_									=    input("Enter numbers separated by comma:\n").strip()
  lowercase_									=    [int(item.strip()) for item in user_input.split(",")]
  lowercase_									=    int(input("Enter the number to be found in the list:\n").strip())
  lowercase_									=    "" if binary_search(sequence, target) else "not "
  print(F"""{target} was {not_str}found in {sequence}""")



