text: # This file is autogenerated by the command `make fix-copies`, do not edit.
  # flake8: noqa
  from ..file_utils import DummyObject, requires_backends
  
  
  QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class QDQBertForMaskedLM(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertForNextSentencePrediction(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertForTokenClassification(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertLayer(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertLMHeadModel(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertModel(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  class QDQBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["pytorch_quantization", "torch"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["pytorch_quantization", "torch"])
  
  
  def load_tf_weights_in_qdqbert(*args, **kwargs):
      requires_backends(load_tf_weights_in_qdqbert, ["pytorch_quantization", "torch"])
  