code: 
  
  
  
  
  
  
  import unittest
  
  from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
  from transformers.utils import cached_property
  
  
  
  
  class 				_lowerCamelCase (    unittest.TestCase    ):
  
  
  
        """simple docstring"""
  
  
  
  
  
  
        @cached_property
        def 						UpperCAmelCase		( self   )       ->   str:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"   )
  
  
  
  
  
  
  
        @cached_property
        def 						UpperCAmelCase		( self   )       ->   Dict:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"   )
  
  
  
  
  
  
  
        def 						UpperCAmelCase		( self   )       ->   str:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          __snake_case   :				Optional[int]        =       self.tokenizer_ab
          __snake_case   :				Optional[Any]        =       " I am a small frog."
          __snake_case   :				Dict        =       tok([src_text]				,						padding=UpperCAmelCase				,						truncation=UpperCAmelCase   )["input_ids"]
          __snake_case   :				int        =       tok.batch_decode(UpperCAmelCase				,						skip_special_tokens=UpperCAmelCase				,						clean_up_tokenization_spaces=UpperCAmelCase   )[0]
          assert src_text == decoded
  
  
  
  
  
  
  
        def 						UpperCAmelCase		( self   )       ->   Tuple:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          __snake_case   :				Optional[int]        =       self.rust_tokenizer_ab
          __snake_case   :				Optional[int]        =       " I am a small frog."
          __snake_case   :				int        =       tok([src_text]				,						padding=UpperCAmelCase				,						truncation=UpperCAmelCase   )["input_ids"]
          __snake_case   :				Tuple        =       tok.batch_decode(UpperCAmelCase				,						skip_special_tokens=UpperCAmelCase				,						clean_up_tokenization_spaces=UpperCAmelCase   )[0]
          assert src_text == decoded
  
  
  
  
  
  
  
        def 						UpperCAmelCase		( self   )       ->   Optional[Any]:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          assert self.tokenizer_ab.add_prefix_space
          assert self.tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5502, 2], [5502, 2]]
  
  
  
  
  
  
  
        def 						UpperCAmelCase		( self   )       ->   Optional[Any]:
  
  
  
  
  
  
          '''simple docstring'''
  
  
  
  
  
  
          assert self.rust_tokenizer_ab.add_prefix_space
          assert self.rust_tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5502, 2], [5502, 2]]
  
  
style_context: 
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  _UpperCamelCase       = {
      '''configuration_deta''': ['''DETA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetaConfig'''],
  }
  
  try:
       if not is_vision_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = ['''DetaImageProcessor''']
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = [
           '''DETA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''DetaForObjectDetection''',
           '''DetaModel''',
           '''DetaPreTrainedModel''',
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig
  
       try:
            if not is_vision_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .image_processing_deta import DetaImageProcessor
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_deta import (
                DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
                DetaForObjectDetection,
                DetaModel,
                DetaPreTrainedModel,
            )
  
  else:
       import sys
  
       _UpperCamelCase       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  