code: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_torch_available,
  )
  
  
  __A   :     List[Any]      =			{'''configuration_regnet''': ['''REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RegNetConfig''']}
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     int      =			[
       '''REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''RegNetForImageClassification''',
       '''RegNetModel''',
       '''RegNetPreTrainedModel''',
   ]
  
  try:
   if not is_tf_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     int      =			[
       '''TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFRegNetForImageClassification''',
       '''TFRegNetModel''',
       '''TFRegNetPreTrainedModel''',
   ]
  
  try:
   if not is_flax_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     Tuple      =			[
       '''FlaxRegNetForImageClassification''',
       '''FlaxRegNetModel''',
       '''FlaxRegNetPreTrainedModel''',
   ]
  
  
  if TYPE_CHECKING:
   from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_regnet import (
        REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        RegNetForImageClassification,
        RegNetModel,
        RegNetPreTrainedModel,
    )
  
   try:
    if not is_tf_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_tf_regnet import (
        TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFRegNetForImageClassification,
        TFRegNetModel,
        TFRegNetPreTrainedModel,
    )
  
   try:
    if not is_flax_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_flax_regnet import (
        FlaxRegNetForImageClassification,
        FlaxRegNetModel,
        FlaxRegNetPreTrainedModel,
    )
  
  
  else:
   import sys
  
   __A   :     Union[str, Any]      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure)
  
  
  
  
  
  
style_context: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  __A   :     Optional[int]      =			{
      '''configuration_splinter''': ['''SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SplinterConfig'''],
      '''tokenization_splinter''': ['''SplinterTokenizer'''],
  }
  
  try:
   if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     Optional[int]      =			['''SplinterTokenizerFast''']
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   __A   :     Union[str, Any]      =			[
       '''SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SplinterForQuestionAnswering''',
       '''SplinterForPreTraining''',
       '''SplinterLayer''',
       '''SplinterModel''',
       '''SplinterPreTrainedModel''',
   ]
  
  
  if TYPE_CHECKING:
   from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
   from .tokenization_splinter import SplinterTokenizer
  
   try:
    if not is_tokenizers_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .tokenization_splinter_fast import SplinterTokenizerFast
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_splinter import (
        SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
        SplinterForPreTraining,
        SplinterForQuestionAnswering,
        SplinterLayer,
        SplinterModel,
        SplinterPreTrainedModel,
    )
  
  
  else:
   import sys
  
   __A   :     Optional[Any]      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
  