code: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  __A   :     Optional[Any]      =			{
      '''configuration_switch_transformers''': [
          '''SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
          '''SwitchTransformersConfig''',
          '''SwitchTransformersOnnxConfig''',
      ]
  }
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     int      =			[
       '''SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SwitchTransformersEncoderModel''',
       '''SwitchTransformersForConditionalGeneration''',
       '''SwitchTransformersModel''',
       '''SwitchTransformersPreTrainedModel''',
       '''SwitchTransformersTop1Router''',
       '''SwitchTransformersSparseMLP''',
   ]
  
  
  if TYPE_CHECKING:
   from .configuration_switch_transformers import (
       SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SwitchTransformersConfig,
       SwitchTransformersOnnxConfig,
   )
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_switch_transformers import (
        SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwitchTransformersEncoderModel,
        SwitchTransformersForConditionalGeneration,
        SwitchTransformersModel,
        SwitchTransformersPreTrainedModel,
        SwitchTransformersSparseMLP,
        SwitchTransformersTopaRouter,
    )
  
  
  else:
   import sys
  
   __A   :     Union[str, Any]      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
style_context: 
  
  __A   :     List[Any]      =			'''
  # Installation de Transformers
  ! pip install transformers datasets
  # Pour installer à partir du code source au lieu de la dernière version, commentez la commande ci-dessus et décommentez la suivante.
  # ! pip install git+https://github.com/huggingface/transformers.git
  '''
  
  __A   :     Dict      =			[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
  __A   :     Tuple      =			{
      '''{processor_class}''': '''FakeProcessorClass''',
      '''{model_class}''': '''FakeModelClass''',
      '''{object_class}''': '''FakeObjectClass''',
  }
  
  
  
  
  
  