


from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE	:Tuple  		=     {
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE	:List[Any]  		=     ['''MPNetTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE	:int  		=     [
       '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''MPNetForMaskedLM''',
       '''MPNetForMultipleChoice''',
       '''MPNetForQuestionAnswering''',
       '''MPNetForSequenceClassification''',
       '''MPNetForTokenClassification''',
       '''MPNetLayer''',
       '''MPNetModel''',
       '''MPNetPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE	:Union[str, Any]  		=     [
       '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFMPNetEmbeddings''',
       '''TFMPNetForMaskedLM''',
       '''TFMPNetForMultipleChoice''',
       '''TFMPNetForQuestionAnswering''',
       '''TFMPNetForSequenceClassification''',
       '''TFMPNetForTokenClassification''',
       '''TFMPNetMainLayer''',
       '''TFMPNetModel''',
       '''TFMPNetPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
   from .tokenization_mpnet import MPNetTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_mpnet_fast import MPNetTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mpnet import (
          MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          MPNetForMaskedLM,
          MPNetForMultipleChoice,
          MPNetForQuestionAnswering,
          MPNetForSequenceClassification,
          MPNetForTokenClassification,
          MPNetLayer,
          MPNetModel,
          MPNetPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mpnet import (
          TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFMPNetEmbeddings,
          TFMPNetForMaskedLM,
          TFMPNetForMultipleChoice,
          TFMPNetForQuestionAnswering,
          TFMPNetForSequenceClassification,
          TFMPNetForTokenClassification,
          TFMPNetMainLayer,
          TFMPNetModel,
          TFMPNetPreTrainedModel,
      )

else:
   import sys

   SCREAMING_SNAKE_CASE	:int  		=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








import safs


class     __lowerCAmelCase     ( safs.SaFileSystem					):






  """simple docstring"""




