
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A		     =    {
    '''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _A		     =    [
          '''SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''Swinv2ForImageClassification''',
          '''Swinv2ForMaskedImageModeling''',
          '''Swinv2Model''',
          '''Swinv2PreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_swinva import (
                SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                SwinvaForImageClassification,
                SwinvaForMaskedImageModeling,
                SwinvaModel,
                SwinvaPreTrainedModel,
            )


else:
      import sys

      _A		     =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










from typing import TYPE_CHECKING

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


UpperCAmelCase_     							= {
    'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvBertConfig', 'ConvBertOnnxConfig'],
    'tokenization_convbert': ['ConvBertTokenizer'],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     							= ['ConvBertTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     							= [
      'CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'ConvBertForMaskedLM',
      'ConvBertForMultipleChoice',
      'ConvBertForQuestionAnswering',
      'ConvBertForSequenceClassification',
      'ConvBertForTokenClassification',
      'ConvBertLayer',
      'ConvBertModel',
      'ConvBertPreTrainedModel',
      'load_tf_weights_in_convbert',
  ]


try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     							= [
      'TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFConvBertForMaskedLM',
      'TFConvBertForMultipleChoice',
      'TFConvBertForQuestionAnswering',
      'TFConvBertForSequenceClassification',
      'TFConvBertForTokenClassification',
      'TFConvBertLayer',
      'TFConvBertModel',
      'TFConvBertPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
  from .tokenization_convbert import ConvBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_convbert_fast import ConvBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_convbert import (
        CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ConvBertForMaskedLM,
        ConvBertForMultipleChoice,
        ConvBertForQuestionAnswering,
        ConvBertForSequenceClassification,
        ConvBertForTokenClassification,
        ConvBertLayer,
        ConvBertModel,
        ConvBertPreTrainedModel,
        load_tf_weights_in_convbert,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_convbert import (
        TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFConvBertForMaskedLM,
        TFConvBertForMultipleChoice,
        TFConvBertForQuestionAnswering,
        TFConvBertForSequenceClassification,
        TFConvBertForTokenClassification,
        TFConvBertLayer,
        TFConvBertModel,
        TFConvBertPreTrainedModel,
    )


else:
  import sys

  UpperCAmelCase_     							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

