



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


a__      =		{
    """configuration_flaubert""": ["""FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FlaubertConfig""", """FlaubertOnnxConfig"""],
    """tokenization_flaubert""": ["""FlaubertTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__      =		[
      """FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FlaubertForMultipleChoice""",
      """FlaubertForQuestionAnswering""",
      """FlaubertForQuestionAnsweringSimple""",
      """FlaubertForSequenceClassification""",
      """FlaubertForTokenClassification""",
      """FlaubertModel""",
      """FlaubertWithLMHeadModel""",
      """FlaubertPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__      =		[
      """TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFFlaubertForMultipleChoice""",
      """TFFlaubertForQuestionAnsweringSimple""",
      """TFFlaubertForSequenceClassification""",
      """TFFlaubertForTokenClassification""",
      """TFFlaubertModel""",
      """TFFlaubertPreTrainedModel""",
      """TFFlaubertWithLMHeadModel""",
  ]


if TYPE_CHECKING:
  from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
  from .tokenization_flaubert import FlaubertTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flaubert import (
        FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        FlaubertForMultipleChoice,
        FlaubertForQuestionAnswering,
        FlaubertForQuestionAnsweringSimple,
        FlaubertForSequenceClassification,
        FlaubertForTokenClassification,
        FlaubertModel,
        FlaubertPreTrainedModel,
        FlaubertWithLMHeadModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_flaubert import (
        TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFFlaubertForMultipleChoice,
        TFFlaubertForQuestionAnsweringSimple,
        TFFlaubertForSequenceClassification,
        TFFlaubertForTokenClassification,
        TFFlaubertModel,
        TFFlaubertPreTrainedModel,
        TFFlaubertWithLMHeadModel,
    )

else:
  import sys

  a__      =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





def  lowercase    (				SCREAMING_SNAKE_CASE__    :		float			,    SCREAMING_SNAKE_CASE__    :		float			)					->       float:
 return a + b


if __name__ == "__main__":
  a__      =		5
  a__      =		6
  print(F'''The sum of {a} + {b} is {add(a, b)}''')
