Spaces:
Running
on
T4
Running
on
T4
| # coding=utf-8 | |
| # Copyright 2018 The HuggingFace Inc. team. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """ Auto Model class.""" | |
| import warnings | |
| from collections import OrderedDict | |
| from ...utils import logging | |
| from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update | |
| from .configuration_auto import CONFIG_MAPPING_NAMES | |
| logger = logging.get_logger(__name__) | |
| TF_MODEL_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Base model mapping | |
| ("albert", "TFAlbertModel"), | |
| ("bart", "TFBartModel"), | |
| ("bert", "TFBertModel"), | |
| ("blenderbot", "TFBlenderbotModel"), | |
| ("blenderbot-small", "TFBlenderbotSmallModel"), | |
| ("blip", "TFBlipModel"), | |
| ("camembert", "TFCamembertModel"), | |
| ("clip", "TFCLIPModel"), | |
| ("convbert", "TFConvBertModel"), | |
| ("convnext", "TFConvNextModel"), | |
| ("ctrl", "TFCTRLModel"), | |
| ("cvt", "TFCvtModel"), | |
| ("data2vec-vision", "TFData2VecVisionModel"), | |
| ("deberta", "TFDebertaModel"), | |
| ("deberta-v2", "TFDebertaV2Model"), | |
| ("deit", "TFDeiTModel"), | |
| ("distilbert", "TFDistilBertModel"), | |
| ("dpr", "TFDPRQuestionEncoder"), | |
| ("efficientformer", "TFEfficientFormerModel"), | |
| ("electra", "TFElectraModel"), | |
| ("esm", "TFEsmModel"), | |
| ("flaubert", "TFFlaubertModel"), | |
| ("funnel", ("TFFunnelModel", "TFFunnelBaseModel")), | |
| ("gpt-sw3", "TFGPT2Model"), | |
| ("gpt2", "TFGPT2Model"), | |
| ("gptj", "TFGPTJModel"), | |
| ("groupvit", "TFGroupViTModel"), | |
| ("hubert", "TFHubertModel"), | |
| ("layoutlm", "TFLayoutLMModel"), | |
| ("layoutlmv3", "TFLayoutLMv3Model"), | |
| ("led", "TFLEDModel"), | |
| ("longformer", "TFLongformerModel"), | |
| ("lxmert", "TFLxmertModel"), | |
| ("marian", "TFMarianModel"), | |
| ("mbart", "TFMBartModel"), | |
| ("mobilebert", "TFMobileBertModel"), | |
| ("mobilevit", "TFMobileViTModel"), | |
| ("mpnet", "TFMPNetModel"), | |
| ("mt5", "TFMT5Model"), | |
| ("openai-gpt", "TFOpenAIGPTModel"), | |
| ("opt", "TFOPTModel"), | |
| ("pegasus", "TFPegasusModel"), | |
| ("regnet", "TFRegNetModel"), | |
| ("rembert", "TFRemBertModel"), | |
| ("resnet", "TFResNetModel"), | |
| ("roberta", "TFRobertaModel"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormModel"), | |
| ("roformer", "TFRoFormerModel"), | |
| ("sam", "TFSamModel"), | |
| ("segformer", "TFSegformerModel"), | |
| ("speech_to_text", "TFSpeech2TextModel"), | |
| ("swin", "TFSwinModel"), | |
| ("t5", "TFT5Model"), | |
| ("tapas", "TFTapasModel"), | |
| ("transfo-xl", "TFTransfoXLModel"), | |
| ("vision-text-dual-encoder", "TFVisionTextDualEncoderModel"), | |
| ("vit", "TFViTModel"), | |
| ("vit_mae", "TFViTMAEModel"), | |
| ("wav2vec2", "TFWav2Vec2Model"), | |
| ("whisper", "TFWhisperModel"), | |
| ("xglm", "TFXGLMModel"), | |
| ("xlm", "TFXLMModel"), | |
| ("xlm-roberta", "TFXLMRobertaModel"), | |
| ("xlnet", "TFXLNetModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_PRETRAINING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for pre-training mapping | |
| ("albert", "TFAlbertForPreTraining"), | |
| ("bart", "TFBartForConditionalGeneration"), | |
| ("bert", "TFBertForPreTraining"), | |
| ("camembert", "TFCamembertForMaskedLM"), | |
| ("ctrl", "TFCTRLLMHeadModel"), | |
| ("distilbert", "TFDistilBertForMaskedLM"), | |
| ("electra", "TFElectraForPreTraining"), | |
| ("flaubert", "TFFlaubertWithLMHeadModel"), | |
| ("funnel", "TFFunnelForPreTraining"), | |
| ("gpt-sw3", "TFGPT2LMHeadModel"), | |
| ("gpt2", "TFGPT2LMHeadModel"), | |
| ("layoutlm", "TFLayoutLMForMaskedLM"), | |
| ("lxmert", "TFLxmertForPreTraining"), | |
| ("mobilebert", "TFMobileBertForPreTraining"), | |
| ("mpnet", "TFMPNetForMaskedLM"), | |
| ("openai-gpt", "TFOpenAIGPTLMHeadModel"), | |
| ("roberta", "TFRobertaForMaskedLM"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForMaskedLM"), | |
| ("t5", "TFT5ForConditionalGeneration"), | |
| ("tapas", "TFTapasForMaskedLM"), | |
| ("transfo-xl", "TFTransfoXLLMHeadModel"), | |
| ("vit_mae", "TFViTMAEForPreTraining"), | |
| ("xlm", "TFXLMWithLMHeadModel"), | |
| ("xlm-roberta", "TFXLMRobertaForMaskedLM"), | |
| ("xlnet", "TFXLNetLMHeadModel"), | |
| ] | |
| ) | |
| TF_MODEL_WITH_LM_HEAD_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model with LM heads mapping | |
| ("albert", "TFAlbertForMaskedLM"), | |
| ("bart", "TFBartForConditionalGeneration"), | |
| ("bert", "TFBertForMaskedLM"), | |
| ("camembert", "TFCamembertForMaskedLM"), | |
| ("convbert", "TFConvBertForMaskedLM"), | |
| ("ctrl", "TFCTRLLMHeadModel"), | |
| ("distilbert", "TFDistilBertForMaskedLM"), | |
| ("electra", "TFElectraForMaskedLM"), | |
| ("esm", "TFEsmForMaskedLM"), | |
| ("flaubert", "TFFlaubertWithLMHeadModel"), | |
| ("funnel", "TFFunnelForMaskedLM"), | |
| ("gpt-sw3", "TFGPT2LMHeadModel"), | |
| ("gpt2", "TFGPT2LMHeadModel"), | |
| ("gptj", "TFGPTJForCausalLM"), | |
| ("layoutlm", "TFLayoutLMForMaskedLM"), | |
| ("led", "TFLEDForConditionalGeneration"), | |
| ("longformer", "TFLongformerForMaskedLM"), | |
| ("marian", "TFMarianMTModel"), | |
| ("mobilebert", "TFMobileBertForMaskedLM"), | |
| ("mpnet", "TFMPNetForMaskedLM"), | |
| ("openai-gpt", "TFOpenAIGPTLMHeadModel"), | |
| ("rembert", "TFRemBertForMaskedLM"), | |
| ("roberta", "TFRobertaForMaskedLM"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForMaskedLM"), | |
| ("roformer", "TFRoFormerForMaskedLM"), | |
| ("speech_to_text", "TFSpeech2TextForConditionalGeneration"), | |
| ("t5", "TFT5ForConditionalGeneration"), | |
| ("tapas", "TFTapasForMaskedLM"), | |
| ("transfo-xl", "TFTransfoXLLMHeadModel"), | |
| ("whisper", "TFWhisperForConditionalGeneration"), | |
| ("xlm", "TFXLMWithLMHeadModel"), | |
| ("xlm-roberta", "TFXLMRobertaForMaskedLM"), | |
| ("xlnet", "TFXLNetLMHeadModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Causal LM mapping | |
| ("bert", "TFBertLMHeadModel"), | |
| ("camembert", "TFCamembertForCausalLM"), | |
| ("ctrl", "TFCTRLLMHeadModel"), | |
| ("gpt-sw3", "TFGPT2LMHeadModel"), | |
| ("gpt2", "TFGPT2LMHeadModel"), | |
| ("gptj", "TFGPTJForCausalLM"), | |
| ("openai-gpt", "TFOpenAIGPTLMHeadModel"), | |
| ("opt", "TFOPTForCausalLM"), | |
| ("rembert", "TFRemBertForCausalLM"), | |
| ("roberta", "TFRobertaForCausalLM"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForCausalLM"), | |
| ("roformer", "TFRoFormerForCausalLM"), | |
| ("transfo-xl", "TFTransfoXLLMHeadModel"), | |
| ("xglm", "TFXGLMForCausalLM"), | |
| ("xlm", "TFXLMWithLMHeadModel"), | |
| ("xlm-roberta", "TFXLMRobertaForCausalLM"), | |
| ("xlnet", "TFXLNetLMHeadModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("deit", "TFDeiTForMaskedImageModeling"), | |
| ("swin", "TFSwinForMaskedImageModeling"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Image-classsification | |
| ("convnext", "TFConvNextForImageClassification"), | |
| ("cvt", "TFCvtForImageClassification"), | |
| ("data2vec-vision", "TFData2VecVisionForImageClassification"), | |
| ("deit", ("TFDeiTForImageClassification", "TFDeiTForImageClassificationWithTeacher")), | |
| ( | |
| "efficientformer", | |
| ("TFEfficientFormerForImageClassification", "TFEfficientFormerForImageClassificationWithTeacher"), | |
| ), | |
| ("mobilevit", "TFMobileViTForImageClassification"), | |
| ("regnet", "TFRegNetForImageClassification"), | |
| ("resnet", "TFResNetForImageClassification"), | |
| ("segformer", "TFSegformerForImageClassification"), | |
| ("swin", "TFSwinForImageClassification"), | |
| ("vit", "TFViTForImageClassification"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Zero Shot Image Classification mapping | |
| ("blip", "TFBlipModel"), | |
| ("clip", "TFCLIPModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Semantic Segmentation mapping | |
| ("data2vec-vision", "TFData2VecVisionForSemanticSegmentation"), | |
| ("mobilevit", "TFMobileViTForSemanticSegmentation"), | |
| ("segformer", "TFSegformerForSemanticSegmentation"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("blip", "TFBlipForConditionalGeneration"), | |
| ("vision-encoder-decoder", "TFVisionEncoderDecoderModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_MASKED_LM_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Masked LM mapping | |
| ("albert", "TFAlbertForMaskedLM"), | |
| ("bert", "TFBertForMaskedLM"), | |
| ("camembert", "TFCamembertForMaskedLM"), | |
| ("convbert", "TFConvBertForMaskedLM"), | |
| ("deberta", "TFDebertaForMaskedLM"), | |
| ("deberta-v2", "TFDebertaV2ForMaskedLM"), | |
| ("distilbert", "TFDistilBertForMaskedLM"), | |
| ("electra", "TFElectraForMaskedLM"), | |
| ("esm", "TFEsmForMaskedLM"), | |
| ("flaubert", "TFFlaubertWithLMHeadModel"), | |
| ("funnel", "TFFunnelForMaskedLM"), | |
| ("layoutlm", "TFLayoutLMForMaskedLM"), | |
| ("longformer", "TFLongformerForMaskedLM"), | |
| ("mobilebert", "TFMobileBertForMaskedLM"), | |
| ("mpnet", "TFMPNetForMaskedLM"), | |
| ("rembert", "TFRemBertForMaskedLM"), | |
| ("roberta", "TFRobertaForMaskedLM"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForMaskedLM"), | |
| ("roformer", "TFRoFormerForMaskedLM"), | |
| ("tapas", "TFTapasForMaskedLM"), | |
| ("xlm", "TFXLMWithLMHeadModel"), | |
| ("xlm-roberta", "TFXLMRobertaForMaskedLM"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Seq2Seq Causal LM mapping | |
| ("bart", "TFBartForConditionalGeneration"), | |
| ("blenderbot", "TFBlenderbotForConditionalGeneration"), | |
| ("blenderbot-small", "TFBlenderbotSmallForConditionalGeneration"), | |
| ("encoder-decoder", "TFEncoderDecoderModel"), | |
| ("led", "TFLEDForConditionalGeneration"), | |
| ("marian", "TFMarianMTModel"), | |
| ("mbart", "TFMBartForConditionalGeneration"), | |
| ("mt5", "TFMT5ForConditionalGeneration"), | |
| ("pegasus", "TFPegasusForConditionalGeneration"), | |
| ("t5", "TFT5ForConditionalGeneration"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("speech_to_text", "TFSpeech2TextForConditionalGeneration"), | |
| ("whisper", "TFWhisperForConditionalGeneration"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Sequence Classification mapping | |
| ("albert", "TFAlbertForSequenceClassification"), | |
| ("bart", "TFBartForSequenceClassification"), | |
| ("bert", "TFBertForSequenceClassification"), | |
| ("camembert", "TFCamembertForSequenceClassification"), | |
| ("convbert", "TFConvBertForSequenceClassification"), | |
| ("ctrl", "TFCTRLForSequenceClassification"), | |
| ("deberta", "TFDebertaForSequenceClassification"), | |
| ("deberta-v2", "TFDebertaV2ForSequenceClassification"), | |
| ("distilbert", "TFDistilBertForSequenceClassification"), | |
| ("electra", "TFElectraForSequenceClassification"), | |
| ("esm", "TFEsmForSequenceClassification"), | |
| ("flaubert", "TFFlaubertForSequenceClassification"), | |
| ("funnel", "TFFunnelForSequenceClassification"), | |
| ("gpt-sw3", "TFGPT2ForSequenceClassification"), | |
| ("gpt2", "TFGPT2ForSequenceClassification"), | |
| ("gptj", "TFGPTJForSequenceClassification"), | |
| ("layoutlm", "TFLayoutLMForSequenceClassification"), | |
| ("layoutlmv3", "TFLayoutLMv3ForSequenceClassification"), | |
| ("longformer", "TFLongformerForSequenceClassification"), | |
| ("mobilebert", "TFMobileBertForSequenceClassification"), | |
| ("mpnet", "TFMPNetForSequenceClassification"), | |
| ("openai-gpt", "TFOpenAIGPTForSequenceClassification"), | |
| ("rembert", "TFRemBertForSequenceClassification"), | |
| ("roberta", "TFRobertaForSequenceClassification"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForSequenceClassification"), | |
| ("roformer", "TFRoFormerForSequenceClassification"), | |
| ("tapas", "TFTapasForSequenceClassification"), | |
| ("transfo-xl", "TFTransfoXLForSequenceClassification"), | |
| ("xlm", "TFXLMForSequenceClassification"), | |
| ("xlm-roberta", "TFXLMRobertaForSequenceClassification"), | |
| ("xlnet", "TFXLNetForSequenceClassification"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Question Answering mapping | |
| ("albert", "TFAlbertForQuestionAnswering"), | |
| ("bert", "TFBertForQuestionAnswering"), | |
| ("camembert", "TFCamembertForQuestionAnswering"), | |
| ("convbert", "TFConvBertForQuestionAnswering"), | |
| ("deberta", "TFDebertaForQuestionAnswering"), | |
| ("deberta-v2", "TFDebertaV2ForQuestionAnswering"), | |
| ("distilbert", "TFDistilBertForQuestionAnswering"), | |
| ("electra", "TFElectraForQuestionAnswering"), | |
| ("flaubert", "TFFlaubertForQuestionAnsweringSimple"), | |
| ("funnel", "TFFunnelForQuestionAnswering"), | |
| ("gptj", "TFGPTJForQuestionAnswering"), | |
| ("layoutlmv3", "TFLayoutLMv3ForQuestionAnswering"), | |
| ("longformer", "TFLongformerForQuestionAnswering"), | |
| ("mobilebert", "TFMobileBertForQuestionAnswering"), | |
| ("mpnet", "TFMPNetForQuestionAnswering"), | |
| ("rembert", "TFRemBertForQuestionAnswering"), | |
| ("roberta", "TFRobertaForQuestionAnswering"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForQuestionAnswering"), | |
| ("roformer", "TFRoFormerForQuestionAnswering"), | |
| ("xlm", "TFXLMForQuestionAnsweringSimple"), | |
| ("xlm-roberta", "TFXLMRobertaForQuestionAnswering"), | |
| ("xlnet", "TFXLNetForQuestionAnsweringSimple"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES = OrderedDict([("wav2vec2", "TFWav2Vec2ForSequenceClassification")]) | |
| TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("layoutlm", "TFLayoutLMForQuestionAnswering"), | |
| ("layoutlmv3", "TFLayoutLMv3ForQuestionAnswering"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Table Question Answering mapping | |
| ("tapas", "TFTapasForQuestionAnswering"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Token Classification mapping | |
| ("albert", "TFAlbertForTokenClassification"), | |
| ("bert", "TFBertForTokenClassification"), | |
| ("camembert", "TFCamembertForTokenClassification"), | |
| ("convbert", "TFConvBertForTokenClassification"), | |
| ("deberta", "TFDebertaForTokenClassification"), | |
| ("deberta-v2", "TFDebertaV2ForTokenClassification"), | |
| ("distilbert", "TFDistilBertForTokenClassification"), | |
| ("electra", "TFElectraForTokenClassification"), | |
| ("esm", "TFEsmForTokenClassification"), | |
| ("flaubert", "TFFlaubertForTokenClassification"), | |
| ("funnel", "TFFunnelForTokenClassification"), | |
| ("layoutlm", "TFLayoutLMForTokenClassification"), | |
| ("layoutlmv3", "TFLayoutLMv3ForTokenClassification"), | |
| ("longformer", "TFLongformerForTokenClassification"), | |
| ("mobilebert", "TFMobileBertForTokenClassification"), | |
| ("mpnet", "TFMPNetForTokenClassification"), | |
| ("rembert", "TFRemBertForTokenClassification"), | |
| ("roberta", "TFRobertaForTokenClassification"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForTokenClassification"), | |
| ("roformer", "TFRoFormerForTokenClassification"), | |
| ("xlm", "TFXLMForTokenClassification"), | |
| ("xlm-roberta", "TFXLMRobertaForTokenClassification"), | |
| ("xlnet", "TFXLNetForTokenClassification"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES = OrderedDict( | |
| [ | |
| # Model for Multiple Choice mapping | |
| ("albert", "TFAlbertForMultipleChoice"), | |
| ("bert", "TFBertForMultipleChoice"), | |
| ("camembert", "TFCamembertForMultipleChoice"), | |
| ("convbert", "TFConvBertForMultipleChoice"), | |
| ("deberta-v2", "TFDebertaV2ForMultipleChoice"), | |
| ("distilbert", "TFDistilBertForMultipleChoice"), | |
| ("electra", "TFElectraForMultipleChoice"), | |
| ("flaubert", "TFFlaubertForMultipleChoice"), | |
| ("funnel", "TFFunnelForMultipleChoice"), | |
| ("longformer", "TFLongformerForMultipleChoice"), | |
| ("mobilebert", "TFMobileBertForMultipleChoice"), | |
| ("mpnet", "TFMPNetForMultipleChoice"), | |
| ("rembert", "TFRemBertForMultipleChoice"), | |
| ("roberta", "TFRobertaForMultipleChoice"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormForMultipleChoice"), | |
| ("roformer", "TFRoFormerForMultipleChoice"), | |
| ("xlm", "TFXLMForMultipleChoice"), | |
| ("xlm-roberta", "TFXLMRobertaForMultipleChoice"), | |
| ("xlnet", "TFXLNetForMultipleChoice"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("bert", "TFBertForNextSentencePrediction"), | |
| ("mobilebert", "TFMobileBertForNextSentencePrediction"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_MASK_GENERATION_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("sam", "TFSamModel"), | |
| ] | |
| ) | |
| TF_MODEL_FOR_TEXT_ENCODING_MAPPING_NAMES = OrderedDict( | |
| [ | |
| ("albert", "TFAlbertModel"), | |
| ("bert", "TFBertModel"), | |
| ("convbert", "TFConvBertModel"), | |
| ("deberta", "TFDebertaModel"), | |
| ("deberta-v2", "TFDebertaV2Model"), | |
| ("distilbert", "TFDistilBertModel"), | |
| ("electra", "TFElectraModel"), | |
| ("flaubert", "TFFlaubertModel"), | |
| ("longformer", "TFLongformerModel"), | |
| ("mobilebert", "TFMobileBertModel"), | |
| ("mt5", "TFMT5EncoderModel"), | |
| ("rembert", "TFRemBertModel"), | |
| ("roberta", "TFRobertaModel"), | |
| ("roberta-prelayernorm", "TFRobertaPreLayerNormModel"), | |
| ("roformer", "TFRoFormerModel"), | |
| ("t5", "TFT5EncoderModel"), | |
| ("xlm", "TFXLMModel"), | |
| ("xlm-roberta", "TFXLMRobertaModel"), | |
| ] | |
| ) | |
| TF_MODEL_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_MAPPING_NAMES) | |
| TF_MODEL_FOR_PRETRAINING_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_FOR_PRETRAINING_MAPPING_NAMES) | |
| TF_MODEL_WITH_LM_HEAD_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_WITH_LM_HEAD_MAPPING_NAMES) | |
| TF_MODEL_FOR_CAUSAL_LM_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES) | |
| TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_VISION_2_SEQ_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES) | |
| TF_MODEL_FOR_MASKED_LM_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_FOR_MASKED_LM_MAPPING_NAMES) | |
| TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_MASK_GENERATION_MAPPING = _LazyAutoMapping( | |
| CONFIG_MAPPING_NAMES, TF_MODEL_FOR_MASK_GENERATION_MAPPING_NAMES | |
| ) | |
| TF_MODEL_FOR_TEXT_ENCODING_MAPPING = _LazyAutoMapping(CONFIG_MAPPING_NAMES, TF_MODEL_FOR_TEXT_ENCODING_MAPPING_NAMES) | |
| class TFAutoModelForMaskGeneration(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_MASK_GENERATION_MAPPING | |
| class TFAutoModelForTextEncoding(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_TEXT_ENCODING_MAPPING | |
| class TFAutoModel(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_MAPPING | |
| TFAutoModel = auto_class_update(TFAutoModel) | |
| class TFAutoModelForAudioClassification(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING | |
| TFAutoModelForAudioClassification = auto_class_update( | |
| TFAutoModelForAudioClassification, head_doc="audio classification" | |
| ) | |
| class TFAutoModelForPreTraining(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_PRETRAINING_MAPPING | |
| TFAutoModelForPreTraining = auto_class_update(TFAutoModelForPreTraining, head_doc="pretraining") | |
| # Private on purpose, the public class will add the deprecation warnings. | |
| class _TFAutoModelWithLMHead(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_WITH_LM_HEAD_MAPPING | |
| _TFAutoModelWithLMHead = auto_class_update(_TFAutoModelWithLMHead, head_doc="language modeling") | |
| class TFAutoModelForCausalLM(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_CAUSAL_LM_MAPPING | |
| TFAutoModelForCausalLM = auto_class_update(TFAutoModelForCausalLM, head_doc="causal language modeling") | |
| class TFAutoModelForMaskedImageModeling(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING | |
| TFAutoModelForMaskedImageModeling = auto_class_update( | |
| TFAutoModelForMaskedImageModeling, head_doc="masked image modeling" | |
| ) | |
| class TFAutoModelForImageClassification(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING | |
| TFAutoModelForImageClassification = auto_class_update( | |
| TFAutoModelForImageClassification, head_doc="image classification" | |
| ) | |
| class TFAutoModelForZeroShotImageClassification(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING | |
| TFAutoModelForZeroShotImageClassification = auto_class_update( | |
| TFAutoModelForZeroShotImageClassification, head_doc="zero-shot image classification" | |
| ) | |
| class TFAutoModelForSemanticSegmentation(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING | |
| TFAutoModelForSemanticSegmentation = auto_class_update( | |
| TFAutoModelForSemanticSegmentation, head_doc="semantic segmentation" | |
| ) | |
| class TFAutoModelForVision2Seq(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_VISION_2_SEQ_MAPPING | |
| TFAutoModelForVision2Seq = auto_class_update(TFAutoModelForVision2Seq, head_doc="vision-to-text modeling") | |
| class TFAutoModelForMaskedLM(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_MASKED_LM_MAPPING | |
| TFAutoModelForMaskedLM = auto_class_update(TFAutoModelForMaskedLM, head_doc="masked language modeling") | |
| class TFAutoModelForSeq2SeqLM(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING | |
| TFAutoModelForSeq2SeqLM = auto_class_update( | |
| TFAutoModelForSeq2SeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="t5-base" | |
| ) | |
| class TFAutoModelForSequenceClassification(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING | |
| TFAutoModelForSequenceClassification = auto_class_update( | |
| TFAutoModelForSequenceClassification, head_doc="sequence classification" | |
| ) | |
| class TFAutoModelForQuestionAnswering(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING | |
| TFAutoModelForQuestionAnswering = auto_class_update(TFAutoModelForQuestionAnswering, head_doc="question answering") | |
| class TFAutoModelForDocumentQuestionAnswering(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING | |
| TFAutoModelForDocumentQuestionAnswering = auto_class_update( | |
| TFAutoModelForDocumentQuestionAnswering, | |
| head_doc="document question answering", | |
| checkpoint_for_example='impira/layoutlm-document-qa", revision="52e01b3', | |
| ) | |
| class TFAutoModelForTableQuestionAnswering(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING | |
| TFAutoModelForTableQuestionAnswering = auto_class_update( | |
| TFAutoModelForTableQuestionAnswering, | |
| head_doc="table question answering", | |
| checkpoint_for_example="google/tapas-base-finetuned-wtq", | |
| ) | |
| class TFAutoModelForTokenClassification(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING | |
| TFAutoModelForTokenClassification = auto_class_update( | |
| TFAutoModelForTokenClassification, head_doc="token classification" | |
| ) | |
| class TFAutoModelForMultipleChoice(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING | |
| TFAutoModelForMultipleChoice = auto_class_update(TFAutoModelForMultipleChoice, head_doc="multiple choice") | |
| class TFAutoModelForNextSentencePrediction(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING | |
| TFAutoModelForNextSentencePrediction = auto_class_update( | |
| TFAutoModelForNextSentencePrediction, head_doc="next sentence prediction" | |
| ) | |
| class TFAutoModelForSpeechSeq2Seq(_BaseAutoModelClass): | |
| _model_mapping = TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING | |
| TFAutoModelForSpeechSeq2Seq = auto_class_update( | |
| TFAutoModelForSpeechSeq2Seq, head_doc="sequence-to-sequence speech-to-text modeling" | |
| ) | |
| class TFAutoModelWithLMHead(_TFAutoModelWithLMHead): | |
| def from_config(cls, config): | |
| warnings.warn( | |
| "The class `TFAutoModelWithLMHead` is deprecated and will be removed in a future version. Please use" | |
| " `TFAutoModelForCausalLM` for causal language models, `TFAutoModelForMaskedLM` for masked language models" | |
| " and `TFAutoModelForSeq2SeqLM` for encoder-decoder models.", | |
| FutureWarning, | |
| ) | |
| return super().from_config(config) | |
| def from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs): | |
| warnings.warn( | |
| "The class `TFAutoModelWithLMHead` is deprecated and will be removed in a future version. Please use" | |
| " `TFAutoModelForCausalLM` for causal language models, `TFAutoModelForMaskedLM` for masked language models" | |
| " and `TFAutoModelForSeq2SeqLM` for encoder-decoder models.", | |
| FutureWarning, | |
| ) | |
| return super().from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) | |