text: # This file is autogenerated by the command `make fix-copies`, do not edit.
  # flake8: noqa
  from ..utils import DummyObject, requires_backends
  
  
  class TensorFlowBenchmarkArguments(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TensorFlowBenchmark(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFForcedBOSTokenLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFForcedEOSTokenLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLogitsProcessorList(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLogitsWarper(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMinLengthLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFNoBadWordsLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFNoRepeatNGramLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRepetitionPenaltyLogitsProcessor(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTemperatureLogitsWarper(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTopKLogitsWarper(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTopPLogitsWarper(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  def tf_top_k_top_p_filtering(*args, **kwargs):
      requires_backends(tf_top_k_top_p_filtering, ["tf"])
  
  
  class KerasMetricCallback(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class PushToHubCallback(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFLayoutLMForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLayoutLMForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLayoutLMForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLayoutLMMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLayoutLMModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLayoutLMPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSequenceSummary(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSharedEmbeddings(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  def shape_list(*args, **kwargs):
      requires_backends(shape_list, ["tf"])
  
  
  TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFAlbertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAlbertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_MODEL_FOR_CAUSAL_LM_MAPPING = None
  
  
  TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING = None
  
  
  TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING = None
  
  
  TF_MODEL_FOR_MASKED_LM_MAPPING = None
  
  
  TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING = None
  
  
  TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING = None
  
  
  TF_MODEL_FOR_PRETRAINING_MAPPING = None
  
  
  TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING = None
  
  
  TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING = None
  
  
  TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING = None
  
  
  TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING = None
  
  
  TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING = None
  
  
  TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING = None
  
  
  TF_MODEL_FOR_VISION_2_SEQ_MAPPING = None
  
  
  TF_MODEL_MAPPING = None
  
  
  TF_MODEL_WITH_LM_HEAD_MAPPING = None
  
  
  class TFAutoModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForImageClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForNextSentencePrediction(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForSeq2SeqLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForSpeechSeq2Seq(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForTableQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelForVision2Seq(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFAutoModelWithLMHead(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBartForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBartModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBartPretrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFBertEmbeddings(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForNextSentencePrediction(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotSmallForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotSmallModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFBlenderbotSmallPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFCamembertForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCamembertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFCLIPModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCLIPPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCLIPTextModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCLIPVisionModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFConvBertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvNextForImageClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvNextModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFConvNextPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFCTRLForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCTRLLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCTRLModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFCTRLPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFData2VecVisionForImageClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFData2VecVisionModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFData2VecVisionPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFDebertaForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFDebertaV2ForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaV2ForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaV2ForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaV2ForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaV2Model(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDebertaV2PreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFDistilBertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDistilBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFDPRContextEncoder(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDPRPretrainedContextEncoder(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDPRPretrainedQuestionEncoder(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDPRPretrainedReader(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDPRQuestionEncoder(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFDPRReader(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFElectraForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFElectraPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFEncoderDecoderModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFFlaubertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertForQuestionAnsweringSimple(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFlaubertWithLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFFunnelBaseModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFFunnelPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFGPT2DoubleHeadsModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPT2ForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPT2LMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPT2MainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPT2Model(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPT2PreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPTJForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPTJForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPTJForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPTJModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFGPTJPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFHubertForCTC(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFHubertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFHubertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLEDForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLEDModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLEDPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFLongformerForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLongformerSelfAttention(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFLxmertForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLxmertMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLxmertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLxmertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFLxmertVisualFeatureEncoder(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMarianModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMarianMTModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMarianPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMBartForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMBartModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMBartPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFMobileBertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForNextSentencePrediction(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMobileBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFMPNetForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMPNetPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMT5EncoderModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMT5ForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFMT5Model(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFOpenAIGPTDoubleHeadsModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFOpenAIGPTForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFOpenAIGPTLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFOpenAIGPTMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFOpenAIGPTModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFOpenAIGPTPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFPegasusForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFPegasusModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFPegasusPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRagModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRagPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRagSequenceForGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRagTokenForGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFRemBertForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRemBertPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFRobertaForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRobertaPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFRoFormerForCausalLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFRoFormerPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFSpeech2TextForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSpeech2TextModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSpeech2TextPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFSwinForImageClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSwinForMaskedImageModeling(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSwinModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFSwinPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFT5EncoderModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFT5ForConditionalGeneration(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFT5Model(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFT5PreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFTapasForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTapasForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTapasForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTapasModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTapasPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFAdaptiveEmbedding(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTransfoXLForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTransfoXLLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTransfoXLMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTransfoXLModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFTransfoXLPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFVisionEncoderDecoderModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTForImageClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTMAEForPreTraining(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTMAEModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFViTMAEPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFWav2Vec2ForCTC(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFWav2Vec2Model(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFWav2Vec2PreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFXLMForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMForQuestionAnsweringSimple(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMWithLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFXLMRobertaForMaskedLM(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMRobertaForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMRobertaForQuestionAnswering(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMRobertaForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMRobertaForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLMRobertaModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST = None
  
  
  class TFXLNetForMultipleChoice(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetForQuestionAnsweringSimple(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetForSequenceClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetForTokenClassification(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetLMHeadModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetMainLayer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class TFXLNetPreTrainedModel(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class AdamWeightDecay(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class GradientAccumulator(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  class WarmUp(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  
  
  def create_optimizer(*args, **kwargs):
      requires_backends(create_optimizer, ["tf"])
  
  
  class TFTrainer(metaclass=DummyObject):
      _backends = ["tf"]
  
      def __init__(self, *args, **kwargs):
          requires_backends(self, ["tf"])
  