# This file is autogenerated by the command `make fix-copies`, do not edit. # flake8: noqa from ..file_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"]) 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_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_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 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 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 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"]) 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"]) 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"]) 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_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"]) 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"])