diff --git "a/transformers_4_35_0/__init__.py" "b/transformers_4_35_0/__init__.py" new file mode 100644--- /dev/null +++ "b/transformers_4_35_0/__init__.py" @@ -0,0 +1,7670 @@ +# Copyright 2020 The HuggingFace Team. All rights reserved. +# +# 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. + +# When adding a new object to this init, remember to add it twice: once inside the `_import_structure` dictionary and +# once inside the `if TYPE_CHECKING` branch. The `TYPE_CHECKING` should have import statements as usual, but they are +# only there for type checking. The `_import_structure` is a dictionary submodule to list of object names, and is used +# to defer the actual importing for when the objects are requested. This way `import transformers` provides the names +# in the namespace without actually importing anything (and especially none of the backends). + +__version__ = "4.35.0.dev0" + +from typing import TYPE_CHECKING + +# Check the dependencies satisfy the minimal versions required. +from . import dependency_versions_check +from .utils import ( + OptionalDependencyNotAvailable, + _LazyModule, + is_bitsandbytes_available, + is_essentia_available, + is_flax_available, + is_keras_nlp_available, + is_librosa_available, + is_pretty_midi_available, + is_scipy_available, + is_sentencepiece_available, + is_speech_available, + is_tensorflow_text_available, + is_tf_available, + is_timm_available, + is_tokenizers_available, + is_torch_available, + is_torchvision_available, + is_vision_available, + logging, +) + + +logger = logging.get_logger(__name__) # pylint: disable=invalid-name + + +# Base objects, independent of any specific backend +_import_structure = { + "audio_utils": [], + "benchmark": [], + "commands": [], + "configuration_utils": ["PretrainedConfig"], + "convert_graph_to_onnx": [], + "convert_slow_tokenizers_checkpoints_to_fast": [], + "convert_tf_hub_seq_to_seq_bert_to_pytorch": [], + "data": [ + "DataProcessor", + "InputExample", + "InputFeatures", + "SingleSentenceClassificationProcessor", + "SquadExample", + "SquadFeatures", + "SquadV1Processor", + "SquadV2Processor", + "glue_compute_metrics", + "glue_convert_examples_to_features", + "glue_output_modes", + "glue_processors", + "glue_tasks_num_labels", + "squad_convert_examples_to_features", + "xnli_compute_metrics", + "xnli_output_modes", + "xnli_processors", + "xnli_tasks_num_labels", + ], + "data.data_collator": [ + "DataCollator", + "DataCollatorForLanguageModeling", + "DataCollatorForPermutationLanguageModeling", + "DataCollatorForSeq2Seq", + "DataCollatorForSOP", + "DataCollatorForTokenClassification", + "DataCollatorForWholeWordMask", + "DataCollatorWithPadding", + "DefaultDataCollator", + "default_data_collator", + ], + "data.metrics": [], + "data.processors": [], + "debug_utils": [], + "deepspeed": [], + "dependency_versions_check": [], + "dependency_versions_table": [], + "dynamic_module_utils": [], + "feature_extraction_sequence_utils": ["SequenceFeatureExtractor"], + "feature_extraction_utils": ["BatchFeature", "FeatureExtractionMixin"], + "file_utils": [], + "generation": ["GenerationConfig", "TextIteratorStreamer", "TextStreamer"], + "hf_argparser": ["HfArgumentParser"], + "hyperparameter_search": [], + "image_transforms": [], + "integrations": [ + "is_clearml_available", + "is_comet_available", + "is_neptune_available", + "is_optuna_available", + "is_ray_available", + "is_ray_tune_available", + "is_sigopt_available", + "is_tensorboard_available", + "is_wandb_available", + ], + "modelcard": ["ModelCard"], + "modeling_tf_pytorch_utils": [ + "convert_tf_weight_name_to_pt_weight_name", + "load_pytorch_checkpoint_in_tf2_model", + "load_pytorch_model_in_tf2_model", + "load_pytorch_weights_in_tf2_model", + "load_tf2_checkpoint_in_pytorch_model", + "load_tf2_model_in_pytorch_model", + "load_tf2_weights_in_pytorch_model", + ], + "models": [], + # Models + "models.albert": ["ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "AlbertConfig"], + "models.align": [ + "ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP", + "AlignConfig", + "AlignProcessor", + "AlignTextConfig", + "AlignVisionConfig", + ], + "models.altclip": [ + "ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "AltCLIPConfig", + "AltCLIPProcessor", + "AltCLIPTextConfig", + "AltCLIPVisionConfig", + ], + "models.audio_spectrogram_transformer": [ + "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "ASTConfig", + ], + "models.auto": [ + "ALL_PRETRAINED_CONFIG_ARCHIVE_MAP", + "CONFIG_MAPPING", + "FEATURE_EXTRACTOR_MAPPING", + "IMAGE_PROCESSOR_MAPPING", + "MODEL_NAMES_MAPPING", + "PROCESSOR_MAPPING", + "TOKENIZER_MAPPING", + "AutoConfig", + "AutoFeatureExtractor", + "AutoImageProcessor", + "AutoProcessor", + "AutoTokenizer", + ], + "models.autoformer": [ + "AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "AutoformerConfig", + ], + "models.bark": [ + "BarkCoarseConfig", + "BarkConfig", + "BarkFineConfig", + "BarkProcessor", + "BarkSemanticConfig", + ], + "models.bart": ["BartConfig", "BartTokenizer"], + "models.barthez": [], + "models.bartpho": [], + "models.beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig"], + "models.bert": [ + "BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "BasicTokenizer", + "BertConfig", + "BertTokenizer", + "WordpieceTokenizer", + ], + "models.bert_generation": ["BertGenerationConfig"], + "models.bert_japanese": ["BertJapaneseTokenizer", "CharacterTokenizer", "MecabTokenizer"], + "models.bertweet": ["BertweetTokenizer"], + "models.big_bird": ["BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP", "BigBirdConfig"], + "models.bigbird_pegasus": [ + "BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP", + "BigBirdPegasusConfig", + ], + "models.biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig", "BioGptTokenizer"], + "models.bit": ["BIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BitConfig"], + "models.blenderbot": ["BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BlenderbotConfig", "BlenderbotTokenizer"], + "models.blenderbot_small": [ + "BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP", + "BlenderbotSmallConfig", + "BlenderbotSmallTokenizer", + ], + "models.blip": [ + "BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "BlipConfig", + "BlipProcessor", + "BlipTextConfig", + "BlipVisionConfig", + ], + "models.blip_2": [ + "BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Blip2Config", + "Blip2Processor", + "Blip2QFormerConfig", + "Blip2VisionConfig", + ], + "models.bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig"], + "models.bridgetower": [ + "BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "BridgeTowerConfig", + "BridgeTowerProcessor", + "BridgeTowerTextConfig", + "BridgeTowerVisionConfig", + ], + "models.bros": ["BROS_PRETRAINED_CONFIG_ARCHIVE_MAP", "BrosConfig", "BrosProcessor"], + "models.byt5": ["ByT5Tokenizer"], + "models.camembert": ["CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CamembertConfig"], + "models.canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig", "CanineTokenizer"], + "models.chinese_clip": [ + "CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "ChineseCLIPConfig", + "ChineseCLIPProcessor", + "ChineseCLIPTextConfig", + "ChineseCLIPVisionConfig", + ], + "models.clap": [ + "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST", + "ClapAudioConfig", + "ClapConfig", + "ClapProcessor", + "ClapTextConfig", + ], + "models.clip": [ + "CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "CLIPConfig", + "CLIPProcessor", + "CLIPTextConfig", + "CLIPTokenizer", + "CLIPVisionConfig", + ], + "models.clipseg": [ + "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP", + "CLIPSegConfig", + "CLIPSegProcessor", + "CLIPSegTextConfig", + "CLIPSegVisionConfig", + ], + "models.code_llama": [], + "models.codegen": ["CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP", "CodeGenConfig", "CodeGenTokenizer"], + "models.conditional_detr": ["CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConditionalDetrConfig"], + "models.convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBertTokenizer"], + "models.convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig"], + "models.convnextv2": ["CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextV2Config"], + "models.cpm": [], + "models.cpmant": ["CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CpmAntConfig", "CpmAntTokenizer"], + "models.ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig", "CTRLTokenizer"], + "models.cvt": ["CVT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CvtConfig"], + "models.data2vec": [ + "DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Data2VecAudioConfig", + "Data2VecTextConfig", + "Data2VecVisionConfig", + ], + "models.deberta": ["DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaConfig", "DebertaTokenizer"], + "models.deberta_v2": ["DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaV2Config"], + "models.decision_transformer": ["DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "DecisionTransformerConfig"], + "models.deformable_detr": ["DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeformableDetrConfig"], + "models.deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig"], + "models.deprecated": [], + "models.deprecated.bort": [], + "models.deprecated.mctct": [ + "MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "MCTCTConfig", + "MCTCTFeatureExtractor", + "MCTCTProcessor", + ], + "models.deprecated.mmbt": ["MMBTConfig"], + "models.deprecated.open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"], + "models.deprecated.retribert": [ + "RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "RetriBertConfig", + "RetriBertTokenizer", + ], + "models.deprecated.tapex": ["TapexTokenizer"], + "models.deprecated.trajectory_transformer": [ + "TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "TrajectoryTransformerConfig", + ], + "models.deprecated.van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"], + "models.deta": ["DETA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetaConfig"], + "models.detr": ["DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetrConfig"], + "models.dialogpt": [], + "models.dinat": ["DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DinatConfig"], + "models.dinov2": ["DINOV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Dinov2Config"], + "models.distilbert": ["DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DistilBertConfig", "DistilBertTokenizer"], + "models.dit": [], + "models.donut": ["DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "DonutProcessor", "DonutSwinConfig"], + "models.dpr": [ + "DPR_PRETRAINED_CONFIG_ARCHIVE_MAP", + "DPRConfig", + "DPRContextEncoderTokenizer", + "DPRQuestionEncoderTokenizer", + "DPRReaderOutput", + "DPRReaderTokenizer", + ], + "models.dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"], + "models.efficientformer": ["EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "EfficientFormerConfig"], + "models.efficientnet": ["EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "EfficientNetConfig"], + "models.electra": ["ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP", "ElectraConfig", "ElectraTokenizer"], + "models.encodec": [ + "ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP", + "EncodecConfig", + "EncodecFeatureExtractor", + ], + "models.encoder_decoder": ["EncoderDecoderConfig"], + "models.ernie": [ + "ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", + "ErnieConfig", + ], + "models.ernie_m": ["ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieMConfig"], + "models.esm": ["ESM_PRETRAINED_CONFIG_ARCHIVE_MAP", "EsmConfig", "EsmTokenizer"], + "models.falcon": ["FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP", "FalconConfig"], + "models.flaubert": ["FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FlaubertConfig", "FlaubertTokenizer"], + "models.flava": [ + "FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP", + "FlavaConfig", + "FlavaImageCodebookConfig", + "FlavaImageConfig", + "FlavaMultimodalConfig", + "FlavaTextConfig", + ], + "models.fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"], + "models.focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"], + "models.fsmt": ["FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP", "FSMTConfig", "FSMTTokenizer"], + "models.funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig", "FunnelTokenizer"], + "models.git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitProcessor", "GitVisionConfig"], + "models.glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"], + "models.gpt2": ["GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPT2Config", "GPT2Tokenizer"], + "models.gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"], + "models.gpt_neo": ["GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoConfig"], + "models.gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"], + "models.gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"], + "models.gpt_sw3": [], + "models.gptj": ["GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTJConfig"], + "models.gptsan_japanese": [ + "GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", + "GPTSanJapaneseConfig", + "GPTSanJapaneseTokenizer", + ], + "models.graphormer": ["GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "GraphormerConfig"], + "models.groupvit": [ + "GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "GroupViTConfig", + "GroupViTTextConfig", + "GroupViTVisionConfig", + ], + "models.herbert": ["HerbertTokenizer"], + "models.hubert": ["HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "HubertConfig"], + "models.ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig"], + "models.idefics": [ + "IDEFICS_PRETRAINED_CONFIG_ARCHIVE_MAP", + "IdeficsConfig", + ], + "models.imagegpt": ["IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ImageGPTConfig"], + "models.informer": ["INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "InformerConfig"], + "models.instructblip": [ + "INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "InstructBlipConfig", + "InstructBlipProcessor", + "InstructBlipQFormerConfig", + "InstructBlipVisionConfig", + ], + "models.jukebox": [ + "JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP", + "JukeboxConfig", + "JukeboxPriorConfig", + "JukeboxTokenizer", + "JukeboxVQVAEConfig", + ], + "models.layoutlm": ["LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMConfig", "LayoutLMTokenizer"], + "models.layoutlmv2": [ + "LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", + "LayoutLMv2Config", + "LayoutLMv2FeatureExtractor", + "LayoutLMv2ImageProcessor", + "LayoutLMv2Processor", + "LayoutLMv2Tokenizer", + ], + "models.layoutlmv3": [ + "LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP", + "LayoutLMv3Config", + "LayoutLMv3FeatureExtractor", + "LayoutLMv3ImageProcessor", + "LayoutLMv3Processor", + "LayoutLMv3Tokenizer", + ], + "models.layoutxlm": ["LayoutXLMProcessor"], + "models.led": ["LED_PRETRAINED_CONFIG_ARCHIVE_MAP", "LEDConfig", "LEDTokenizer"], + "models.levit": ["LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LevitConfig"], + "models.lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"], + "models.llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"], + "models.longformer": ["LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongformerConfig", "LongformerTokenizer"], + "models.longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config"], + "models.luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig", "LukeTokenizer"], + "models.lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig", "LxmertTokenizer"], + "models.m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config"], + "models.marian": ["MarianConfig"], + "models.markuplm": [ + "MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP", + "MarkupLMConfig", + "MarkupLMFeatureExtractor", + "MarkupLMProcessor", + "MarkupLMTokenizer", + ], + "models.mask2former": [ + "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Mask2FormerConfig", + ], + "models.maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig", "MaskFormerSwinConfig"], + "models.mbart": ["MBartConfig"], + "models.mbart50": [], + "models.mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig"], + "models.megatron_bert": ["MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegatronBertConfig"], + "models.megatron_gpt2": [], + "models.mgp_str": ["MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP", "MgpstrConfig", "MgpstrProcessor", "MgpstrTokenizer"], + "models.mistral": ["MISTRAL_PRETRAINED_CONFIG_ARCHIVE_MAP", "MistralConfig"], + "models.mluke": [], + "models.mobilebert": ["MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileBertConfig", "MobileBertTokenizer"], + "models.mobilenet_v1": ["MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileNetV1Config"], + "models.mobilenet_v2": ["MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileNetV2Config"], + "models.mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig"], + "models.mobilevitv2": ["MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTV2Config"], + "models.mpnet": ["MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "MPNetConfig", "MPNetTokenizer"], + "models.mpt": ["MPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MptConfig"], + "models.mra": ["MRA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MraConfig"], + "models.mt5": ["MT5Config"], + "models.musicgen": [ + "MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP", + "MusicgenConfig", + "MusicgenDecoderConfig", + ], + "models.mvp": ["MvpConfig", "MvpTokenizer"], + "models.nat": ["NAT_PRETRAINED_CONFIG_ARCHIVE_MAP", "NatConfig"], + "models.nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"], + "models.nllb": [], + "models.nllb_moe": ["NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP", "NllbMoeConfig"], + "models.nougat": ["NougatProcessor"], + "models.nystromformer": [ + "NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "NystromformerConfig", + ], + "models.oneformer": ["ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "OneFormerConfig", "OneFormerProcessor"], + "models.openai": ["OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenAIGPTConfig", "OpenAIGPTTokenizer"], + "models.opt": ["OPTConfig"], + "models.owlvit": [ + "OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "OwlViTConfig", + "OwlViTProcessor", + "OwlViTTextConfig", + "OwlViTVisionConfig", + ], + "models.pegasus": ["PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP", "PegasusConfig", "PegasusTokenizer"], + "models.pegasus_x": ["PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP", "PegasusXConfig"], + "models.perceiver": ["PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PerceiverConfig", "PerceiverTokenizer"], + "models.persimmon": ["PERSIMMON_PRETRAINED_CONFIG_ARCHIVE_MAP", "PersimmonConfig"], + "models.phobert": ["PhobertTokenizer"], + "models.pix2struct": [ + "PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Pix2StructConfig", + "Pix2StructProcessor", + "Pix2StructTextConfig", + "Pix2StructVisionConfig", + ], + "models.plbart": ["PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "PLBartConfig"], + "models.poolformer": ["POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PoolFormerConfig"], + "models.pop2piano": [ + "POP2PIANO_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Pop2PianoConfig", + ], + "models.prophetnet": ["PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ProphetNetConfig", "ProphetNetTokenizer"], + "models.pvt": ["PVT_PRETRAINED_CONFIG_ARCHIVE_MAP", "PvtConfig"], + "models.qdqbert": ["QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "QDQBertConfig"], + "models.rag": ["RagConfig", "RagRetriever", "RagTokenizer"], + "models.realm": ["REALM_PRETRAINED_CONFIG_ARCHIVE_MAP", "RealmConfig", "RealmTokenizer"], + "models.reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConfig"], + "models.regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"], + "models.rembert": ["REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RemBertConfig"], + "models.resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig"], + "models.roberta": ["ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "RobertaConfig", "RobertaTokenizer"], + "models.roberta_prelayernorm": ["ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP", "RobertaPreLayerNormConfig"], + "models.roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig", "RoCBertTokenizer"], + "models.roformer": ["ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoFormerConfig", "RoFormerTokenizer"], + "models.rwkv": ["RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP", "RwkvConfig"], + "models.sam": [ + "SAM_PRETRAINED_CONFIG_ARCHIVE_MAP", + "SamConfig", + "SamMaskDecoderConfig", + "SamProcessor", + "SamPromptEncoderConfig", + "SamVisionConfig", + ], + "models.segformer": ["SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SegformerConfig"], + "models.sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"], + "models.sew_d": ["SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWDConfig"], + "models.speech_encoder_decoder": ["SpeechEncoderDecoderConfig"], + "models.speech_to_text": [ + "SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Speech2TextConfig", + "Speech2TextProcessor", + ], + "models.speech_to_text_2": [ + "SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Speech2Text2Config", + "Speech2Text2Processor", + "Speech2Text2Tokenizer", + ], + "models.speecht5": [ + "SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP", + "SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP", + "SpeechT5Config", + "SpeechT5FeatureExtractor", + "SpeechT5HifiGanConfig", + "SpeechT5Processor", + ], + "models.splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig", "SplinterTokenizer"], + "models.squeezebert": ["SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "SqueezeBertConfig", "SqueezeBertTokenizer"], + "models.swiftformer": ["SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwiftFormerConfig"], + "models.swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig"], + "models.swin2sr": ["SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swin2SRConfig"], + "models.swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"], + "models.switch_transformers": ["SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwitchTransformersConfig"], + "models.t5": ["T5_PRETRAINED_CONFIG_ARCHIVE_MAP", "T5Config"], + "models.table_transformer": ["TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TableTransformerConfig"], + "models.tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig", "TapasTokenizer"], + "models.time_series_transformer": [ + "TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "TimeSeriesTransformerConfig", + ], + "models.timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"], + "models.timm_backbone": ["TimmBackboneConfig"], + "models.transfo_xl": [ + "TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP", + "TransfoXLConfig", + "TransfoXLCorpus", + "TransfoXLTokenizer", + ], + "models.trocr": [ + "TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", + "TrOCRConfig", + "TrOCRProcessor", + ], + "models.tvlt": [ + "TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "TvltConfig", + "TvltFeatureExtractor", + "TvltProcessor", + ], + "models.umt5": ["UMT5Config"], + "models.unispeech": [ + "UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", + "UniSpeechConfig", + ], + "models.unispeech_sat": [ + "UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "UniSpeechSatConfig", + ], + "models.upernet": ["UperNetConfig"], + "models.videomae": ["VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "VideoMAEConfig"], + "models.vilt": [ + "VILT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "ViltConfig", + "ViltFeatureExtractor", + "ViltImageProcessor", + "ViltProcessor", + ], + "models.vision_encoder_decoder": ["VisionEncoderDecoderConfig"], + "models.vision_text_dual_encoder": ["VisionTextDualEncoderConfig", "VisionTextDualEncoderProcessor"], + "models.visual_bert": ["VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "VisualBertConfig"], + "models.vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConfig"], + "models.vit_hybrid": ["VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTHybridConfig"], + "models.vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMAEConfig"], + "models.vit_msn": ["VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMSNConfig"], + "models.vitdet": ["VITDET_PRETRAINED_CONFIG_ARCHIVE_MAP", "VitDetConfig"], + "models.vitmatte": ["VITMATTE_PRETRAINED_CONFIG_ARCHIVE_MAP", "VitMatteConfig"], + "models.vits": [ + "VITS_PRETRAINED_CONFIG_ARCHIVE_MAP", + "VitsConfig", + "VitsTokenizer", + ], + "models.vivit": [ + "VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", + "VivitConfig", + ], + "models.wav2vec2": [ + "WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Wav2Vec2Config", + "Wav2Vec2CTCTokenizer", + "Wav2Vec2FeatureExtractor", + "Wav2Vec2Processor", + "Wav2Vec2Tokenizer", + ], + "models.wav2vec2_conformer": [ + "WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "Wav2Vec2ConformerConfig", + ], + "models.wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"], + "models.wav2vec2_with_lm": ["Wav2Vec2ProcessorWithLM"], + "models.wavlm": [ + "WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", + "WavLMConfig", + ], + "models.whisper": [ + "WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP", + "WhisperConfig", + "WhisperFeatureExtractor", + "WhisperProcessor", + "WhisperTokenizer", + ], + "models.x_clip": [ + "XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP", + "XCLIPConfig", + "XCLIPProcessor", + "XCLIPTextConfig", + "XCLIPVisionConfig", + ], + "models.xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XGLMConfig"], + "models.xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMTokenizer"], + "models.xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"], + "models.xlm_roberta": ["XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMRobertaConfig"], + "models.xlm_roberta_xl": ["XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMRobertaXLConfig"], + "models.xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLNetConfig"], + "models.xmod": ["XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP", "XmodConfig"], + "models.yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig"], + "models.yoso": ["YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP", "YosoConfig"], + "onnx": [], + "pipelines": [ + "AudioClassificationPipeline", + "AutomaticSpeechRecognitionPipeline", + "Conversation", + "ConversationalPipeline", + "CsvPipelineDataFormat", + "DepthEstimationPipeline", + "DocumentQuestionAnsweringPipeline", + "FeatureExtractionPipeline", + "FillMaskPipeline", + "ImageClassificationPipeline", + "ImageSegmentationPipeline", + "ImageToImagePipeline", + "ImageToTextPipeline", + "JsonPipelineDataFormat", + "NerPipeline", + "ObjectDetectionPipeline", + "PipedPipelineDataFormat", + "Pipeline", + "PipelineDataFormat", + "QuestionAnsweringPipeline", + "SummarizationPipeline", + "TableQuestionAnsweringPipeline", + "Text2TextGenerationPipeline", + "TextClassificationPipeline", + "TextGenerationPipeline", + "TextToAudioPipeline", + "TokenClassificationPipeline", + "TranslationPipeline", + "VideoClassificationPipeline", + "VisualQuestionAnsweringPipeline", + "ZeroShotAudioClassificationPipeline", + "ZeroShotClassificationPipeline", + "ZeroShotImageClassificationPipeline", + "ZeroShotObjectDetectionPipeline", + "pipeline", + ], + "processing_utils": ["ProcessorMixin"], + "testing_utils": [], + "tokenization_utils": ["PreTrainedTokenizer"], + "tokenization_utils_base": [ + "AddedToken", + "BatchEncoding", + "CharSpan", + "PreTrainedTokenizerBase", + "SpecialTokensMixin", + "TokenSpan", + ], + "tools": [ + "Agent", + "AzureOpenAiAgent", + "HfAgent", + "LocalAgent", + "OpenAiAgent", + "PipelineTool", + "RemoteTool", + "Tool", + "launch_gradio_demo", + "load_tool", + ], + "trainer_callback": [ + "DefaultFlowCallback", + "EarlyStoppingCallback", + "PrinterCallback", + "ProgressCallback", + "TrainerCallback", + "TrainerControl", + "TrainerState", + ], + "trainer_utils": ["EvalPrediction", "IntervalStrategy", "SchedulerType", "enable_full_determinism", "set_seed"], + "training_args": ["TrainingArguments"], + "training_args_seq2seq": ["Seq2SeqTrainingArguments"], + "training_args_tf": ["TFTrainingArguments"], + "utils": [ + "CONFIG_NAME", + "MODEL_CARD_NAME", + "PYTORCH_PRETRAINED_BERT_CACHE", + "PYTORCH_TRANSFORMERS_CACHE", + "SPIECE_UNDERLINE", + "TF2_WEIGHTS_NAME", + "TF_WEIGHTS_NAME", + "TRANSFORMERS_CACHE", + "WEIGHTS_NAME", + "TensorType", + "add_end_docstrings", + "add_start_docstrings", + "is_apex_available", + "is_bitsandbytes_available", + "is_datasets_available", + "is_decord_available", + "is_faiss_available", + "is_flax_available", + "is_keras_nlp_available", + "is_phonemizer_available", + "is_psutil_available", + "is_py3nvml_available", + "is_pyctcdecode_available", + "is_safetensors_available", + "is_scipy_available", + "is_sentencepiece_available", + "is_sklearn_available", + "is_speech_available", + "is_tensorflow_text_available", + "is_tf_available", + "is_timm_available", + "is_tokenizers_available", + "is_torch_available", + "is_torch_neuroncore_available", + "is_torch_npu_available", + "is_torch_tpu_available", + "is_torchvision_available", + "is_torch_xpu_available", + "is_vision_available", + "logging", + ], + "utils.quantization_config": ["BitsAndBytesConfig", "GPTQConfig"], +} + +# sentencepiece-backed objects +try: + if not is_sentencepiece_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_sentencepiece_objects + + _import_structure["utils.dummy_sentencepiece_objects"] = [ + name for name in dir(dummy_sentencepiece_objects) if not name.startswith("_") + ] +else: + _import_structure["models.albert"].append("AlbertTokenizer") + _import_structure["models.barthez"].append("BarthezTokenizer") + _import_structure["models.bartpho"].append("BartphoTokenizer") + _import_structure["models.bert_generation"].append("BertGenerationTokenizer") + _import_structure["models.big_bird"].append("BigBirdTokenizer") + _import_structure["models.camembert"].append("CamembertTokenizer") + _import_structure["models.code_llama"].append("CodeLlamaTokenizer") + _import_structure["models.cpm"].append("CpmTokenizer") + _import_structure["models.deberta_v2"].append("DebertaV2Tokenizer") + _import_structure["models.ernie_m"].append("ErnieMTokenizer") + _import_structure["models.fnet"].append("FNetTokenizer") + _import_structure["models.gpt_sw3"].append("GPTSw3Tokenizer") + _import_structure["models.layoutxlm"].append("LayoutXLMTokenizer") + _import_structure["models.llama"].append("LlamaTokenizer") + _import_structure["models.m2m_100"].append("M2M100Tokenizer") + _import_structure["models.marian"].append("MarianTokenizer") + _import_structure["models.mbart"].append("MBartTokenizer") + _import_structure["models.mbart50"].append("MBart50Tokenizer") + _import_structure["models.mluke"].append("MLukeTokenizer") + _import_structure["models.mt5"].append("MT5Tokenizer") + _import_structure["models.nllb"].append("NllbTokenizer") + _import_structure["models.pegasus"].append("PegasusTokenizer") + _import_structure["models.plbart"].append("PLBartTokenizer") + _import_structure["models.reformer"].append("ReformerTokenizer") + _import_structure["models.rembert"].append("RemBertTokenizer") + _import_structure["models.speech_to_text"].append("Speech2TextTokenizer") + _import_structure["models.speecht5"].append("SpeechT5Tokenizer") + _import_structure["models.t5"].append("T5Tokenizer") + _import_structure["models.xglm"].append("XGLMTokenizer") + _import_structure["models.xlm_prophetnet"].append("XLMProphetNetTokenizer") + _import_structure["models.xlm_roberta"].append("XLMRobertaTokenizer") + _import_structure["models.xlnet"].append("XLNetTokenizer") + +# tokenizers-backed objects +try: + if not is_tokenizers_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_tokenizers_objects + + _import_structure["utils.dummy_tokenizers_objects"] = [ + name for name in dir(dummy_tokenizers_objects) if not name.startswith("_") + ] +else: + # Fast tokenizers structure + _import_structure["models.albert"].append("AlbertTokenizerFast") + _import_structure["models.bart"].append("BartTokenizerFast") + _import_structure["models.barthez"].append("BarthezTokenizerFast") + _import_structure["models.bert"].append("BertTokenizerFast") + _import_structure["models.big_bird"].append("BigBirdTokenizerFast") + _import_structure["models.blenderbot"].append("BlenderbotTokenizerFast") + _import_structure["models.blenderbot_small"].append("BlenderbotSmallTokenizerFast") + _import_structure["models.bloom"].append("BloomTokenizerFast") + _import_structure["models.camembert"].append("CamembertTokenizerFast") + _import_structure["models.clip"].append("CLIPTokenizerFast") + _import_structure["models.code_llama"].append("CodeLlamaTokenizerFast") + _import_structure["models.codegen"].append("CodeGenTokenizerFast") + _import_structure["models.convbert"].append("ConvBertTokenizerFast") + _import_structure["models.cpm"].append("CpmTokenizerFast") + _import_structure["models.deberta"].append("DebertaTokenizerFast") + _import_structure["models.deberta_v2"].append("DebertaV2TokenizerFast") + _import_structure["models.deprecated.retribert"].append("RetriBertTokenizerFast") + _import_structure["models.distilbert"].append("DistilBertTokenizerFast") + _import_structure["models.dpr"].extend( + ["DPRContextEncoderTokenizerFast", "DPRQuestionEncoderTokenizerFast", "DPRReaderTokenizerFast"] + ) + _import_structure["models.electra"].append("ElectraTokenizerFast") + _import_structure["models.fnet"].append("FNetTokenizerFast") + _import_structure["models.funnel"].append("FunnelTokenizerFast") + _import_structure["models.gpt2"].append("GPT2TokenizerFast") + _import_structure["models.gpt_neox"].append("GPTNeoXTokenizerFast") + _import_structure["models.gpt_neox_japanese"].append("GPTNeoXJapaneseTokenizer") + _import_structure["models.herbert"].append("HerbertTokenizerFast") + _import_structure["models.layoutlm"].append("LayoutLMTokenizerFast") + _import_structure["models.layoutlmv2"].append("LayoutLMv2TokenizerFast") + _import_structure["models.layoutlmv3"].append("LayoutLMv3TokenizerFast") + _import_structure["models.layoutxlm"].append("LayoutXLMTokenizerFast") + _import_structure["models.led"].append("LEDTokenizerFast") + _import_structure["models.llama"].append("LlamaTokenizerFast") + _import_structure["models.longformer"].append("LongformerTokenizerFast") + _import_structure["models.lxmert"].append("LxmertTokenizerFast") + _import_structure["models.markuplm"].append("MarkupLMTokenizerFast") + _import_structure["models.mbart"].append("MBartTokenizerFast") + _import_structure["models.mbart50"].append("MBart50TokenizerFast") + _import_structure["models.mobilebert"].append("MobileBertTokenizerFast") + _import_structure["models.mpnet"].append("MPNetTokenizerFast") + _import_structure["models.mt5"].append("MT5TokenizerFast") + _import_structure["models.mvp"].append("MvpTokenizerFast") + _import_structure["models.nllb"].append("NllbTokenizerFast") + _import_structure["models.nougat"].append("NougatTokenizerFast") + _import_structure["models.openai"].append("OpenAIGPTTokenizerFast") + _import_structure["models.pegasus"].append("PegasusTokenizerFast") + _import_structure["models.realm"].append("RealmTokenizerFast") + _import_structure["models.reformer"].append("ReformerTokenizerFast") + _import_structure["models.rembert"].append("RemBertTokenizerFast") + _import_structure["models.roberta"].append("RobertaTokenizerFast") + _import_structure["models.roformer"].append("RoFormerTokenizerFast") + _import_structure["models.splinter"].append("SplinterTokenizerFast") + _import_structure["models.squeezebert"].append("SqueezeBertTokenizerFast") + _import_structure["models.t5"].append("T5TokenizerFast") + _import_structure["models.whisper"].append("WhisperTokenizerFast") + _import_structure["models.xglm"].append("XGLMTokenizerFast") + _import_structure["models.xlm_roberta"].append("XLMRobertaTokenizerFast") + _import_structure["models.xlnet"].append("XLNetTokenizerFast") + _import_structure["tokenization_utils_fast"] = ["PreTrainedTokenizerFast"] + + +try: + if not (is_sentencepiece_available() and is_tokenizers_available()): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_sentencepiece_and_tokenizers_objects + + _import_structure["utils.dummy_sentencepiece_and_tokenizers_objects"] = [ + name for name in dir(dummy_sentencepiece_and_tokenizers_objects) if not name.startswith("_") + ] +else: + _import_structure["convert_slow_tokenizer"] = ["SLOW_TO_FAST_CONVERTERS", "convert_slow_tokenizer"] + +# Speech-specific objects +try: + if not is_speech_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_speech_objects + + _import_structure["utils.dummy_speech_objects"] = [ + name for name in dir(dummy_speech_objects) if not name.startswith("_") + ] +else: + _import_structure["models.audio_spectrogram_transformer"].append("ASTFeatureExtractor") + _import_structure["models.speech_to_text"].append("Speech2TextFeatureExtractor") + +# Tensorflow-text-specific objects +try: + if not is_tensorflow_text_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_tensorflow_text_objects + + _import_structure["utils.dummy_tensorflow_text_objects"] = [ + name for name in dir(dummy_tensorflow_text_objects) if not name.startswith("_") + ] +else: + _import_structure["models.bert"].append("TFBertTokenizer") + +# keras-nlp-specific objects +try: + if not is_keras_nlp_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_keras_nlp_objects + + _import_structure["utils.dummy_keras_nlp_objects"] = [ + name for name in dir(dummy_keras_nlp_objects) if not name.startswith("_") + ] +else: + _import_structure["models.gpt2"].append("TFGPT2Tokenizer") + +# Vision-specific objects +try: + if not is_vision_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_vision_objects + + _import_structure["utils.dummy_vision_objects"] = [ + name for name in dir(dummy_vision_objects) if not name.startswith("_") + ] +else: + _import_structure["image_processing_utils"] = ["ImageProcessingMixin"] + _import_structure["image_utils"] = ["ImageFeatureExtractionMixin"] + _import_structure["models.beit"].extend(["BeitFeatureExtractor", "BeitImageProcessor"]) + _import_structure["models.bit"].extend(["BitImageProcessor"]) + _import_structure["models.blip"].extend(["BlipImageProcessor"]) + _import_structure["models.bridgetower"].append("BridgeTowerImageProcessor") + _import_structure["models.chinese_clip"].extend(["ChineseCLIPFeatureExtractor", "ChineseCLIPImageProcessor"]) + _import_structure["models.clip"].extend(["CLIPFeatureExtractor", "CLIPImageProcessor"]) + _import_structure["models.conditional_detr"].extend( + ["ConditionalDetrFeatureExtractor", "ConditionalDetrImageProcessor"] + ) + _import_structure["models.convnext"].extend(["ConvNextFeatureExtractor", "ConvNextImageProcessor"]) + _import_structure["models.deformable_detr"].extend( + ["DeformableDetrFeatureExtractor", "DeformableDetrImageProcessor"] + ) + _import_structure["models.deit"].extend(["DeiTFeatureExtractor", "DeiTImageProcessor"]) + _import_structure["models.deta"].append("DetaImageProcessor") + _import_structure["models.detr"].extend(["DetrFeatureExtractor", "DetrImageProcessor"]) + _import_structure["models.donut"].extend(["DonutFeatureExtractor", "DonutImageProcessor"]) + _import_structure["models.dpt"].extend(["DPTFeatureExtractor", "DPTImageProcessor"]) + _import_structure["models.efficientformer"].append("EfficientFormerImageProcessor") + _import_structure["models.efficientnet"].append("EfficientNetImageProcessor") + _import_structure["models.flava"].extend(["FlavaFeatureExtractor", "FlavaImageProcessor", "FlavaProcessor"]) + _import_structure["models.glpn"].extend(["GLPNFeatureExtractor", "GLPNImageProcessor"]) + _import_structure["models.idefics"].extend(["IdeficsImageProcessor"]) + _import_structure["models.imagegpt"].extend(["ImageGPTFeatureExtractor", "ImageGPTImageProcessor"]) + _import_structure["models.layoutlmv2"].extend(["LayoutLMv2FeatureExtractor", "LayoutLMv2ImageProcessor"]) + _import_structure["models.layoutlmv3"].extend(["LayoutLMv3FeatureExtractor", "LayoutLMv3ImageProcessor"]) + _import_structure["models.levit"].extend(["LevitFeatureExtractor", "LevitImageProcessor"]) + _import_structure["models.mask2former"].append("Mask2FormerImageProcessor") + _import_structure["models.maskformer"].extend(["MaskFormerFeatureExtractor", "MaskFormerImageProcessor"]) + _import_structure["models.mobilenet_v1"].extend(["MobileNetV1FeatureExtractor", "MobileNetV1ImageProcessor"]) + _import_structure["models.mobilenet_v2"].extend(["MobileNetV2FeatureExtractor", "MobileNetV2ImageProcessor"]) + _import_structure["models.mobilevit"].extend(["MobileViTFeatureExtractor", "MobileViTImageProcessor"]) + _import_structure["models.nougat"].append("NougatImageProcessor") + _import_structure["models.oneformer"].extend(["OneFormerImageProcessor"]) + _import_structure["models.owlvit"].extend(["OwlViTFeatureExtractor", "OwlViTImageProcessor"]) + _import_structure["models.perceiver"].extend(["PerceiverFeatureExtractor", "PerceiverImageProcessor"]) + _import_structure["models.pix2struct"].extend(["Pix2StructImageProcessor"]) + _import_structure["models.poolformer"].extend(["PoolFormerFeatureExtractor", "PoolFormerImageProcessor"]) + _import_structure["models.pvt"].extend(["PvtImageProcessor"]) + _import_structure["models.sam"].extend(["SamImageProcessor"]) + _import_structure["models.segformer"].extend(["SegformerFeatureExtractor", "SegformerImageProcessor"]) + _import_structure["models.swin2sr"].append("Swin2SRImageProcessor") + _import_structure["models.tvlt"].append("TvltImageProcessor") + _import_structure["models.videomae"].extend(["VideoMAEFeatureExtractor", "VideoMAEImageProcessor"]) + _import_structure["models.vilt"].extend(["ViltFeatureExtractor", "ViltImageProcessor", "ViltProcessor"]) + _import_structure["models.vit"].extend(["ViTFeatureExtractor", "ViTImageProcessor"]) + _import_structure["models.vit_hybrid"].extend(["ViTHybridImageProcessor"]) + _import_structure["models.vitmatte"].append("VitMatteImageProcessor") + _import_structure["models.vivit"].append("VivitImageProcessor") + _import_structure["models.yolos"].extend(["YolosFeatureExtractor", "YolosImageProcessor"]) + + +# PyTorch-backed objects +try: + if not is_torch_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_pt_objects + + _import_structure["utils.dummy_pt_objects"] = [name for name in dir(dummy_pt_objects) if not name.startswith("_")] +else: + _import_structure["activations"] = [] + _import_structure["benchmark.benchmark"] = ["PyTorchBenchmark"] + _import_structure["benchmark.benchmark_args"] = ["PyTorchBenchmarkArguments"] + _import_structure["data.datasets"] = [ + "GlueDataset", + "GlueDataTrainingArguments", + "LineByLineTextDataset", + "LineByLineWithRefDataset", + "LineByLineWithSOPTextDataset", + "SquadDataset", + "SquadDataTrainingArguments", + "TextDataset", + "TextDatasetForNextSentencePrediction", + ] + _import_structure["generation"].extend( + [ + "AlternatingCodebooksLogitsProcessor", + "BeamScorer", + "BeamSearchScorer", + "ClassifierFreeGuidanceLogitsProcessor", + "ConstrainedBeamSearchScorer", + "Constraint", + "ConstraintListState", + "DisjunctiveConstraint", + "EncoderNoRepeatNGramLogitsProcessor", + "EncoderRepetitionPenaltyLogitsProcessor", + "EpsilonLogitsWarper", + "EtaLogitsWarper", + "ExponentialDecayLengthPenalty", + "ForcedBOSTokenLogitsProcessor", + "ForcedEOSTokenLogitsProcessor", + "ForceTokensLogitsProcessor", + "GenerationMixin", + "HammingDiversityLogitsProcessor", + "InfNanRemoveLogitsProcessor", + "LogitNormalization", + "LogitsProcessor", + "LogitsProcessorList", + "LogitsWarper", + "MaxLengthCriteria", + "MaxTimeCriteria", + "MinLengthLogitsProcessor", + "MinNewTokensLengthLogitsProcessor", + "NoBadWordsLogitsProcessor", + "NoRepeatNGramLogitsProcessor", + "PhrasalConstraint", + "PrefixConstrainedLogitsProcessor", + "RepetitionPenaltyLogitsProcessor", + "SequenceBiasLogitsProcessor", + "StoppingCriteria", + "StoppingCriteriaList", + "SuppressTokensAtBeginLogitsProcessor", + "SuppressTokensLogitsProcessor", + "TemperatureLogitsWarper", + "TopKLogitsWarper", + "TopPLogitsWarper", + "TypicalLogitsWarper", + "UnbatchedClassifierFreeGuidanceLogitsProcessor", + "WhisperTimeStampLogitsProcessor", + "top_k_top_p_filtering", + ] + ) + _import_structure["generation_utils"] = [] + _import_structure["modeling_outputs"] = [] + _import_structure["modeling_utils"] = ["PreTrainedModel"] + + # PyTorch models structure + _import_structure["models.albert"].extend( + [ + "ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "AlbertForMaskedLM", + "AlbertForMultipleChoice", + "AlbertForPreTraining", + "AlbertForQuestionAnswering", + "AlbertForSequenceClassification", + "AlbertForTokenClassification", + "AlbertModel", + "AlbertPreTrainedModel", + "load_tf_weights_in_albert", + ] + ) + _import_structure["models.align"].extend( + [ + "ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST", + "AlignModel", + "AlignPreTrainedModel", + "AlignTextModel", + "AlignVisionModel", + ] + ) + _import_structure["models.altclip"].extend( + [ + "ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "AltCLIPModel", + "AltCLIPPreTrainedModel", + "AltCLIPTextModel", + "AltCLIPVisionModel", + ] + ) + _import_structure["models.audio_spectrogram_transformer"].extend( + [ + "AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "ASTForAudioClassification", + "ASTModel", + "ASTPreTrainedModel", + ] + ) + _import_structure["models.auto"].extend( + [ + "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", + "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", + "MODEL_FOR_AUDIO_XVECTOR_MAPPING", + "MODEL_FOR_BACKBONE_MAPPING", + "MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING", + "MODEL_FOR_CAUSAL_LM_MAPPING", + "MODEL_FOR_CTC_MAPPING", + "MODEL_FOR_DEPTH_ESTIMATION_MAPPING", + "MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING", + "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", + "MODEL_FOR_IMAGE_SEGMENTATION_MAPPING", + "MODEL_FOR_IMAGE_TO_IMAGE_MAPPING", + "MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING", + "MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING", + "MODEL_FOR_MASKED_LM_MAPPING", + "MODEL_FOR_MASK_GENERATION_MAPPING", + "MODEL_FOR_MULTIPLE_CHOICE_MAPPING", + "MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING", + "MODEL_FOR_OBJECT_DETECTION_MAPPING", + "MODEL_FOR_PRETRAINING_MAPPING", + "MODEL_FOR_QUESTION_ANSWERING_MAPPING", + "MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING", + "MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING", + "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", + "MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING", + "MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING", + "MODEL_FOR_TEXT_ENCODING_MAPPING", + "MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING", + "MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING", + "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", + "MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING", + "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", + "MODEL_FOR_VISION_2_SEQ_MAPPING", + "MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING", + "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", + "MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING", + "MODEL_MAPPING", + "MODEL_WITH_LM_HEAD_MAPPING", + "AutoBackbone", + "AutoModel", + "AutoModelForAudioClassification", + "AutoModelForAudioFrameClassification", + "AutoModelForAudioXVector", + "AutoModelForCausalLM", + "AutoModelForCTC", + "AutoModelForDepthEstimation", + "AutoModelForDocumentQuestionAnswering", + "AutoModelForImageClassification", + "AutoModelForImageSegmentation", + "AutoModelForImageToImage", + "AutoModelForInstanceSegmentation", + "AutoModelForMaskedImageModeling", + "AutoModelForMaskedLM", + "AutoModelForMaskGeneration", + "AutoModelForMultipleChoice", + "AutoModelForNextSentencePrediction", + "AutoModelForObjectDetection", + "AutoModelForPreTraining", + "AutoModelForQuestionAnswering", + "AutoModelForSemanticSegmentation", + "AutoModelForSeq2SeqLM", + "AutoModelForSequenceClassification", + "AutoModelForSpeechSeq2Seq", + "AutoModelForTableQuestionAnswering", + "AutoModelForTextEncoding", + "AutoModelForTextToSpectrogram", + "AutoModelForTextToWaveform", + "AutoModelForTokenClassification", + "AutoModelForUniversalSegmentation", + "AutoModelForVideoClassification", + "AutoModelForVision2Seq", + "AutoModelForVisualQuestionAnswering", + "AutoModelForZeroShotImageClassification", + "AutoModelForZeroShotObjectDetection", + "AutoModelWithLMHead", + ] + ) + _import_structure["models.autoformer"].extend( + [ + "AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "AutoformerForPrediction", + "AutoformerModel", + "AutoformerPreTrainedModel", + ] + ) + _import_structure["models.bark"].extend( + [ + "BARK_PRETRAINED_MODEL_ARCHIVE_LIST", + "BarkCausalModel", + "BarkCoarseModel", + "BarkFineModel", + "BarkModel", + "BarkPreTrainedModel", + "BarkSemanticModel", + ] + ) + _import_structure["models.bart"].extend( + [ + "BART_PRETRAINED_MODEL_ARCHIVE_LIST", + "BartForCausalLM", + "BartForConditionalGeneration", + "BartForQuestionAnswering", + "BartForSequenceClassification", + "BartModel", + "BartPretrainedModel", + "BartPreTrainedModel", + "PretrainedBartModel", + ] + ) + _import_structure["models.beit"].extend( + [ + "BEIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "BeitForImageClassification", + "BeitForMaskedImageModeling", + "BeitForSemanticSegmentation", + "BeitModel", + "BeitPreTrainedModel", + ] + ) + _import_structure["models.bert"].extend( + [ + "BERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "BertForMaskedLM", + "BertForMultipleChoice", + "BertForNextSentencePrediction", + "BertForPreTraining", + "BertForQuestionAnswering", + "BertForSequenceClassification", + "BertForTokenClassification", + "BertLayer", + "BertLMHeadModel", + "BertModel", + "BertPreTrainedModel", + "load_tf_weights_in_bert", + ] + ) + _import_structure["models.bert_generation"].extend( + [ + "BertGenerationDecoder", + "BertGenerationEncoder", + "BertGenerationPreTrainedModel", + "load_tf_weights_in_bert_generation", + ] + ) + _import_structure["models.big_bird"].extend( + [ + "BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST", + "BigBirdForCausalLM", + "BigBirdForMaskedLM", + "BigBirdForMultipleChoice", + "BigBirdForPreTraining", + "BigBirdForQuestionAnswering", + "BigBirdForSequenceClassification", + "BigBirdForTokenClassification", + "BigBirdLayer", + "BigBirdModel", + "BigBirdPreTrainedModel", + "load_tf_weights_in_big_bird", + ] + ) + _import_structure["models.bigbird_pegasus"].extend( + [ + "BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST", + "BigBirdPegasusForCausalLM", + "BigBirdPegasusForConditionalGeneration", + "BigBirdPegasusForQuestionAnswering", + "BigBirdPegasusForSequenceClassification", + "BigBirdPegasusModel", + "BigBirdPegasusPreTrainedModel", + ] + ) + _import_structure["models.biogpt"].extend( + [ + "BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "BioGptForCausalLM", + "BioGptForSequenceClassification", + "BioGptForTokenClassification", + "BioGptModel", + "BioGptPreTrainedModel", + ] + ) + _import_structure["models.bit"].extend( + [ + "BIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "BitBackbone", + "BitForImageClassification", + "BitModel", + "BitPreTrainedModel", + ] + ) + _import_structure["models.blenderbot"].extend( + [ + "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST", + "BlenderbotForCausalLM", + "BlenderbotForConditionalGeneration", + "BlenderbotModel", + "BlenderbotPreTrainedModel", + ] + ) + _import_structure["models.blenderbot_small"].extend( + [ + "BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST", + "BlenderbotSmallForCausalLM", + "BlenderbotSmallForConditionalGeneration", + "BlenderbotSmallModel", + "BlenderbotSmallPreTrainedModel", + ] + ) + _import_structure["models.blip"].extend( + [ + "BLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "BlipForConditionalGeneration", + "BlipForImageTextRetrieval", + "BlipForQuestionAnswering", + "BlipModel", + "BlipPreTrainedModel", + "BlipTextModel", + "BlipVisionModel", + ] + ) + _import_structure["models.blip_2"].extend( + [ + "BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST", + "Blip2ForConditionalGeneration", + "Blip2Model", + "Blip2PreTrainedModel", + "Blip2QFormerModel", + "Blip2VisionModel", + ] + ) + _import_structure["models.bloom"].extend( + [ + "BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST", + "BloomForCausalLM", + "BloomForQuestionAnswering", + "BloomForSequenceClassification", + "BloomForTokenClassification", + "BloomModel", + "BloomPreTrainedModel", + ] + ) + _import_structure["models.bridgetower"].extend( + [ + "BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST", + "BridgeTowerForContrastiveLearning", + "BridgeTowerForImageAndTextRetrieval", + "BridgeTowerForMaskedLM", + "BridgeTowerModel", + "BridgeTowerPreTrainedModel", + ] + ) + _import_structure["models.bros"].extend( + [ + "BROS_PRETRAINED_MODEL_ARCHIVE_LIST", + "BrosForTokenClassification", + "BrosModel", + "BrosPreTrainedModel", + "BrosProcessor", + "BrosSpadeEEForTokenClassification", + "BrosSpadeELForTokenClassification", + ] + ) + _import_structure["models.camembert"].extend( + [ + "CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "CamembertForCausalLM", + "CamembertForMaskedLM", + "CamembertForMultipleChoice", + "CamembertForQuestionAnswering", + "CamembertForSequenceClassification", + "CamembertForTokenClassification", + "CamembertModel", + "CamembertPreTrainedModel", + ] + ) + _import_structure["models.canine"].extend( + [ + "CANINE_PRETRAINED_MODEL_ARCHIVE_LIST", + "CanineForMultipleChoice", + "CanineForQuestionAnswering", + "CanineForSequenceClassification", + "CanineForTokenClassification", + "CanineLayer", + "CanineModel", + "CaninePreTrainedModel", + "load_tf_weights_in_canine", + ] + ) + _import_structure["models.chinese_clip"].extend( + [ + "CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "ChineseCLIPModel", + "ChineseCLIPPreTrainedModel", + "ChineseCLIPTextModel", + "ChineseCLIPVisionModel", + ] + ) + _import_structure["models.clap"].extend( + [ + "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST", + "ClapAudioModel", + "ClapAudioModelWithProjection", + "ClapFeatureExtractor", + "ClapModel", + "ClapPreTrainedModel", + "ClapTextModel", + "ClapTextModelWithProjection", + ] + ) + _import_structure["models.clip"].extend( + [ + "CLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "CLIPModel", + "CLIPPreTrainedModel", + "CLIPTextModel", + "CLIPTextModelWithProjection", + "CLIPVisionModel", + "CLIPVisionModelWithProjection", + ] + ) + _import_structure["models.clipseg"].extend( + [ + "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST", + "CLIPSegForImageSegmentation", + "CLIPSegModel", + "CLIPSegPreTrainedModel", + "CLIPSegTextModel", + "CLIPSegVisionModel", + ] + ) + _import_structure["models.codegen"].extend( + [ + "CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST", + "CodeGenForCausalLM", + "CodeGenModel", + "CodeGenPreTrainedModel", + ] + ) + _import_structure["models.conditional_detr"].extend( + [ + "CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST", + "ConditionalDetrForObjectDetection", + "ConditionalDetrForSegmentation", + "ConditionalDetrModel", + "ConditionalDetrPreTrainedModel", + ] + ) + _import_structure["models.convbert"].extend( + [ + "CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "ConvBertForMaskedLM", + "ConvBertForMultipleChoice", + "ConvBertForQuestionAnswering", + "ConvBertForSequenceClassification", + "ConvBertForTokenClassification", + "ConvBertLayer", + "ConvBertModel", + "ConvBertPreTrainedModel", + "load_tf_weights_in_convbert", + ] + ) + _import_structure["models.convnext"].extend( + [ + "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST", + "ConvNextBackbone", + "ConvNextForImageClassification", + "ConvNextModel", + "ConvNextPreTrainedModel", + ] + ) + _import_structure["models.convnextv2"].extend( + [ + "CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST", + "ConvNextV2Backbone", + "ConvNextV2ForImageClassification", + "ConvNextV2Model", + "ConvNextV2PreTrainedModel", + ] + ) + _import_structure["models.cpmant"].extend( + [ + "CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST", + "CpmAntForCausalLM", + "CpmAntModel", + "CpmAntPreTrainedModel", + ] + ) + _import_structure["models.ctrl"].extend( + [ + "CTRL_PRETRAINED_MODEL_ARCHIVE_LIST", + "CTRLForSequenceClassification", + "CTRLLMHeadModel", + "CTRLModel", + "CTRLPreTrainedModel", + ] + ) + _import_structure["models.cvt"].extend( + [ + "CVT_PRETRAINED_MODEL_ARCHIVE_LIST", + "CvtForImageClassification", + "CvtModel", + "CvtPreTrainedModel", + ] + ) + _import_structure["models.data2vec"].extend( + [ + "DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST", + "DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST", + "DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST", + "Data2VecAudioForAudioFrameClassification", + "Data2VecAudioForCTC", + "Data2VecAudioForSequenceClassification", + "Data2VecAudioForXVector", + "Data2VecAudioModel", + "Data2VecAudioPreTrainedModel", + "Data2VecTextForCausalLM", + "Data2VecTextForMaskedLM", + "Data2VecTextForMultipleChoice", + "Data2VecTextForQuestionAnswering", + "Data2VecTextForSequenceClassification", + "Data2VecTextForTokenClassification", + "Data2VecTextModel", + "Data2VecTextPreTrainedModel", + "Data2VecVisionForImageClassification", + "Data2VecVisionForSemanticSegmentation", + "Data2VecVisionModel", + "Data2VecVisionPreTrainedModel", + ] + ) + _import_structure["models.deberta"].extend( + [ + "DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "DebertaForMaskedLM", + "DebertaForQuestionAnswering", + "DebertaForSequenceClassification", + "DebertaForTokenClassification", + "DebertaModel", + "DebertaPreTrainedModel", + ] + ) + _import_structure["models.deberta_v2"].extend( + [ + "DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST", + "DebertaV2ForMaskedLM", + "DebertaV2ForMultipleChoice", + "DebertaV2ForQuestionAnswering", + "DebertaV2ForSequenceClassification", + "DebertaV2ForTokenClassification", + "DebertaV2Model", + "DebertaV2PreTrainedModel", + ] + ) + _import_structure["models.decision_transformer"].extend( + [ + "DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "DecisionTransformerGPT2Model", + "DecisionTransformerGPT2PreTrainedModel", + "DecisionTransformerModel", + "DecisionTransformerPreTrainedModel", + ] + ) + _import_structure["models.deformable_detr"].extend( + [ + "DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST", + "DeformableDetrForObjectDetection", + "DeformableDetrModel", + "DeformableDetrPreTrainedModel", + ] + ) + _import_structure["models.deit"].extend( + [ + "DEIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "DeiTForImageClassification", + "DeiTForImageClassificationWithTeacher", + "DeiTForMaskedImageModeling", + "DeiTModel", + "DeiTPreTrainedModel", + ] + ) + _import_structure["models.deprecated.mctct"].extend( + [ + "MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST", + "MCTCTForCTC", + "MCTCTModel", + "MCTCTPreTrainedModel", + ] + ) + _import_structure["models.deprecated.mmbt"].extend(["MMBTForClassification", "MMBTModel", "ModalEmbeddings"]) + _import_structure["models.deprecated.open_llama"].extend( + ["OpenLlamaForCausalLM", "OpenLlamaForSequenceClassification", "OpenLlamaModel", "OpenLlamaPreTrainedModel"] + ) + _import_structure["models.deprecated.retribert"].extend( + ["RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST", "RetriBertModel", "RetriBertPreTrainedModel"] + ) + _import_structure["models.deprecated.trajectory_transformer"].extend( + [ + "TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TrajectoryTransformerModel", + "TrajectoryTransformerPreTrainedModel", + ] + ) + _import_structure["models.deprecated.van"].extend( + [ + "VAN_PRETRAINED_MODEL_ARCHIVE_LIST", + "VanForImageClassification", + "VanModel", + "VanPreTrainedModel", + ] + ) + _import_structure["models.deta"].extend( + [ + "DETA_PRETRAINED_MODEL_ARCHIVE_LIST", + "DetaForObjectDetection", + "DetaModel", + "DetaPreTrainedModel", + ] + ) + _import_structure["models.detr"].extend( + [ + "DETR_PRETRAINED_MODEL_ARCHIVE_LIST", + "DetrForObjectDetection", + "DetrForSegmentation", + "DetrModel", + "DetrPreTrainedModel", + ] + ) + _import_structure["models.dinat"].extend( + [ + "DINAT_PRETRAINED_MODEL_ARCHIVE_LIST", + "DinatBackbone", + "DinatForImageClassification", + "DinatModel", + "DinatPreTrainedModel", + ] + ) + _import_structure["models.dinov2"].extend( + [ + "DINOV2_PRETRAINED_MODEL_ARCHIVE_LIST", + "Dinov2Backbone", + "Dinov2ForImageClassification", + "Dinov2Model", + "Dinov2PreTrainedModel", + ] + ) + _import_structure["models.distilbert"].extend( + [ + "DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "DistilBertForMaskedLM", + "DistilBertForMultipleChoice", + "DistilBertForQuestionAnswering", + "DistilBertForSequenceClassification", + "DistilBertForTokenClassification", + "DistilBertModel", + "DistilBertPreTrainedModel", + ] + ) + _import_structure["models.donut"].extend( + [ + "DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST", + "DonutSwinModel", + "DonutSwinPreTrainedModel", + ] + ) + _import_structure["models.dpr"].extend( + [ + "DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST", + "DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST", + "DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST", + "DPRContextEncoder", + "DPRPretrainedContextEncoder", + "DPRPreTrainedModel", + "DPRPretrainedQuestionEncoder", + "DPRPretrainedReader", + "DPRQuestionEncoder", + "DPRReader", + ] + ) + _import_structure["models.dpt"].extend( + [ + "DPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "DPTForDepthEstimation", + "DPTForSemanticSegmentation", + "DPTModel", + "DPTPreTrainedModel", + ] + ) + _import_structure["models.efficientformer"].extend( + [ + "EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "EfficientFormerForImageClassification", + "EfficientFormerForImageClassificationWithTeacher", + "EfficientFormerModel", + "EfficientFormerPreTrainedModel", + ] + ) + _import_structure["models.efficientnet"].extend( + [ + "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "EfficientNetForImageClassification", + "EfficientNetModel", + "EfficientNetPreTrainedModel", + ] + ) + _import_structure["models.electra"].extend( + [ + "ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST", + "ElectraForCausalLM", + "ElectraForMaskedLM", + "ElectraForMultipleChoice", + "ElectraForPreTraining", + "ElectraForQuestionAnswering", + "ElectraForSequenceClassification", + "ElectraForTokenClassification", + "ElectraModel", + "ElectraPreTrainedModel", + "load_tf_weights_in_electra", + ] + ) + _import_structure["models.encodec"].extend( + [ + "ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST", + "EncodecModel", + "EncodecPreTrainedModel", + ] + ) + _import_structure["models.encoder_decoder"].append("EncoderDecoderModel") + _import_structure["models.ernie"].extend( + [ + "ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST", + "ErnieForCausalLM", + "ErnieForMaskedLM", + "ErnieForMultipleChoice", + "ErnieForNextSentencePrediction", + "ErnieForPreTraining", + "ErnieForQuestionAnswering", + "ErnieForSequenceClassification", + "ErnieForTokenClassification", + "ErnieModel", + "ErniePreTrainedModel", + ] + ) + _import_structure["models.ernie_m"].extend( + [ + "ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST", + "ErnieMForInformationExtraction", + "ErnieMForMultipleChoice", + "ErnieMForQuestionAnswering", + "ErnieMForSequenceClassification", + "ErnieMForTokenClassification", + "ErnieMModel", + "ErnieMPreTrainedModel", + ] + ) + _import_structure["models.esm"].extend( + [ + "ESM_PRETRAINED_MODEL_ARCHIVE_LIST", + "EsmFoldPreTrainedModel", + "EsmForMaskedLM", + "EsmForProteinFolding", + "EsmForSequenceClassification", + "EsmForTokenClassification", + "EsmModel", + "EsmPreTrainedModel", + ] + ) + _import_structure["models.falcon"].extend( + [ + "FALCON_PRETRAINED_MODEL_ARCHIVE_LIST", + "FalconForCausalLM", + "FalconForQuestionAnswering", + "FalconForSequenceClassification", + "FalconForTokenClassification", + "FalconModel", + "FalconPreTrainedModel", + ] + ) + _import_structure["models.flaubert"].extend( + [ + "FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "FlaubertForMultipleChoice", + "FlaubertForQuestionAnswering", + "FlaubertForQuestionAnsweringSimple", + "FlaubertForSequenceClassification", + "FlaubertForTokenClassification", + "FlaubertModel", + "FlaubertPreTrainedModel", + "FlaubertWithLMHeadModel", + ] + ) + _import_structure["models.flava"].extend( + [ + "FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST", + "FlavaForPreTraining", + "FlavaImageCodebook", + "FlavaImageModel", + "FlavaModel", + "FlavaMultimodalModel", + "FlavaPreTrainedModel", + "FlavaTextModel", + ] + ) + _import_structure["models.fnet"].extend( + [ + "FNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "FNetForMaskedLM", + "FNetForMultipleChoice", + "FNetForNextSentencePrediction", + "FNetForPreTraining", + "FNetForQuestionAnswering", + "FNetForSequenceClassification", + "FNetForTokenClassification", + "FNetLayer", + "FNetModel", + "FNetPreTrainedModel", + ] + ) + _import_structure["models.focalnet"].extend( + [ + "FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "FocalNetBackbone", + "FocalNetForImageClassification", + "FocalNetForMaskedImageModeling", + "FocalNetModel", + "FocalNetPreTrainedModel", + ] + ) + _import_structure["models.fsmt"].extend(["FSMTForConditionalGeneration", "FSMTModel", "PretrainedFSMTModel"]) + _import_structure["models.funnel"].extend( + [ + "FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST", + "FunnelBaseModel", + "FunnelForMaskedLM", + "FunnelForMultipleChoice", + "FunnelForPreTraining", + "FunnelForQuestionAnswering", + "FunnelForSequenceClassification", + "FunnelForTokenClassification", + "FunnelModel", + "FunnelPreTrainedModel", + "load_tf_weights_in_funnel", + ] + ) + _import_structure["models.git"].extend( + [ + "GIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "GitForCausalLM", + "GitModel", + "GitPreTrainedModel", + "GitVisionModel", + ] + ) + _import_structure["models.glpn"].extend( + [ + "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST", + "GLPNForDepthEstimation", + "GLPNModel", + "GLPNPreTrainedModel", + ] + ) + _import_structure["models.gpt2"].extend( + [ + "GPT2_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPT2DoubleHeadsModel", + "GPT2ForQuestionAnswering", + "GPT2ForSequenceClassification", + "GPT2ForTokenClassification", + "GPT2LMHeadModel", + "GPT2Model", + "GPT2PreTrainedModel", + "load_tf_weights_in_gpt2", + ] + ) + _import_structure["models.gpt_bigcode"].extend( + [ + "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTBigCodeForCausalLM", + "GPTBigCodeForSequenceClassification", + "GPTBigCodeForTokenClassification", + "GPTBigCodeModel", + "GPTBigCodePreTrainedModel", + ] + ) + _import_structure["models.gpt_neo"].extend( + [ + "GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTNeoForCausalLM", + "GPTNeoForQuestionAnswering", + "GPTNeoForSequenceClassification", + "GPTNeoForTokenClassification", + "GPTNeoModel", + "GPTNeoPreTrainedModel", + "load_tf_weights_in_gpt_neo", + ] + ) + _import_structure["models.gpt_neox"].extend( + [ + "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTNeoXForCausalLM", + "GPTNeoXForQuestionAnswering", + "GPTNeoXForSequenceClassification", + "GPTNeoXForTokenClassification", + "GPTNeoXLayer", + "GPTNeoXModel", + "GPTNeoXPreTrainedModel", + ] + ) + _import_structure["models.gpt_neox_japanese"].extend( + [ + "GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTNeoXJapaneseForCausalLM", + "GPTNeoXJapaneseLayer", + "GPTNeoXJapaneseModel", + "GPTNeoXJapanesePreTrainedModel", + ] + ) + _import_structure["models.gptj"].extend( + [ + "GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTJForCausalLM", + "GPTJForQuestionAnswering", + "GPTJForSequenceClassification", + "GPTJModel", + "GPTJPreTrainedModel", + ] + ) + _import_structure["models.gptsan_japanese"].extend( + [ + "GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST", + "GPTSanJapaneseForConditionalGeneration", + "GPTSanJapaneseModel", + "GPTSanJapanesePreTrainedModel", + ] + ) + _import_structure["models.graphormer"].extend( + [ + "GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "GraphormerForGraphClassification", + "GraphormerModel", + "GraphormerPreTrainedModel", + ] + ) + _import_structure["models.groupvit"].extend( + [ + "GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "GroupViTModel", + "GroupViTPreTrainedModel", + "GroupViTTextModel", + "GroupViTVisionModel", + ] + ) + _import_structure["models.hubert"].extend( + [ + "HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "HubertForCTC", + "HubertForSequenceClassification", + "HubertModel", + "HubertPreTrainedModel", + ] + ) + _import_structure["models.ibert"].extend( + [ + "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "IBertForMaskedLM", + "IBertForMultipleChoice", + "IBertForQuestionAnswering", + "IBertForSequenceClassification", + "IBertForTokenClassification", + "IBertModel", + "IBertPreTrainedModel", + ] + ) + _import_structure["models.idefics"].extend( + [ + "IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST", + "IdeficsForVisionText2Text", + "IdeficsModel", + "IdeficsPreTrainedModel", + "IdeficsProcessor", + ] + ) + _import_structure["models.imagegpt"].extend( + [ + "IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "ImageGPTForCausalImageModeling", + "ImageGPTForImageClassification", + "ImageGPTModel", + "ImageGPTPreTrainedModel", + "load_tf_weights_in_imagegpt", + ] + ) + _import_structure["models.informer"].extend( + [ + "INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "InformerForPrediction", + "InformerModel", + "InformerPreTrainedModel", + ] + ) + _import_structure["models.instructblip"].extend( + [ + "INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "InstructBlipForConditionalGeneration", + "InstructBlipPreTrainedModel", + "InstructBlipQFormerModel", + "InstructBlipVisionModel", + ] + ) + _import_structure["models.jukebox"].extend( + [ + "JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST", + "JukeboxModel", + "JukeboxPreTrainedModel", + "JukeboxPrior", + "JukeboxVQVAE", + ] + ) + _import_structure["models.layoutlm"].extend( + [ + "LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "LayoutLMForMaskedLM", + "LayoutLMForQuestionAnswering", + "LayoutLMForSequenceClassification", + "LayoutLMForTokenClassification", + "LayoutLMModel", + "LayoutLMPreTrainedModel", + ] + ) + _import_structure["models.layoutlmv2"].extend( + [ + "LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST", + "LayoutLMv2ForQuestionAnswering", + "LayoutLMv2ForSequenceClassification", + "LayoutLMv2ForTokenClassification", + "LayoutLMv2Model", + "LayoutLMv2PreTrainedModel", + ] + ) + _import_structure["models.layoutlmv3"].extend( + [ + "LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST", + "LayoutLMv3ForQuestionAnswering", + "LayoutLMv3ForSequenceClassification", + "LayoutLMv3ForTokenClassification", + "LayoutLMv3Model", + "LayoutLMv3PreTrainedModel", + ] + ) + _import_structure["models.led"].extend( + [ + "LED_PRETRAINED_MODEL_ARCHIVE_LIST", + "LEDForConditionalGeneration", + "LEDForQuestionAnswering", + "LEDForSequenceClassification", + "LEDModel", + "LEDPreTrainedModel", + ] + ) + _import_structure["models.levit"].extend( + [ + "LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "LevitForImageClassification", + "LevitForImageClassificationWithTeacher", + "LevitModel", + "LevitPreTrainedModel", + ] + ) + _import_structure["models.lilt"].extend( + [ + "LILT_PRETRAINED_MODEL_ARCHIVE_LIST", + "LiltForQuestionAnswering", + "LiltForSequenceClassification", + "LiltForTokenClassification", + "LiltModel", + "LiltPreTrainedModel", + ] + ) + _import_structure["models.llama"].extend( + ["LlamaForCausalLM", "LlamaForSequenceClassification", "LlamaModel", "LlamaPreTrainedModel"] + ) + _import_structure["models.longformer"].extend( + [ + "LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "LongformerForMaskedLM", + "LongformerForMultipleChoice", + "LongformerForQuestionAnswering", + "LongformerForSequenceClassification", + "LongformerForTokenClassification", + "LongformerModel", + "LongformerPreTrainedModel", + "LongformerSelfAttention", + ] + ) + _import_structure["models.longt5"].extend( + [ + "LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST", + "LongT5EncoderModel", + "LongT5ForConditionalGeneration", + "LongT5Model", + "LongT5PreTrainedModel", + ] + ) + _import_structure["models.luke"].extend( + [ + "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST", + "LukeForEntityClassification", + "LukeForEntityPairClassification", + "LukeForEntitySpanClassification", + "LukeForMaskedLM", + "LukeForMultipleChoice", + "LukeForQuestionAnswering", + "LukeForSequenceClassification", + "LukeForTokenClassification", + "LukeModel", + "LukePreTrainedModel", + ] + ) + _import_structure["models.lxmert"].extend( + [ + "LxmertEncoder", + "LxmertForPreTraining", + "LxmertForQuestionAnswering", + "LxmertModel", + "LxmertPreTrainedModel", + "LxmertVisualFeatureEncoder", + "LxmertXLayer", + ] + ) + _import_structure["models.m2m_100"].extend( + [ + "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST", + "M2M100ForConditionalGeneration", + "M2M100Model", + "M2M100PreTrainedModel", + ] + ) + _import_structure["models.marian"].extend(["MarianForCausalLM", "MarianModel", "MarianMTModel"]) + _import_structure["models.markuplm"].extend( + [ + "MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "MarkupLMForQuestionAnswering", + "MarkupLMForSequenceClassification", + "MarkupLMForTokenClassification", + "MarkupLMModel", + "MarkupLMPreTrainedModel", + ] + ) + _import_structure["models.mask2former"].extend( + [ + "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "Mask2FormerForUniversalSegmentation", + "Mask2FormerModel", + "Mask2FormerPreTrainedModel", + ] + ) + _import_structure["models.maskformer"].extend( + [ + "MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "MaskFormerForInstanceSegmentation", + "MaskFormerModel", + "MaskFormerPreTrainedModel", + "MaskFormerSwinBackbone", + ] + ) + _import_structure["models.mbart"].extend( + [ + "MBartForCausalLM", + "MBartForConditionalGeneration", + "MBartForQuestionAnswering", + "MBartForSequenceClassification", + "MBartModel", + "MBartPreTrainedModel", + ] + ) + _import_structure["models.mega"].extend( + [ + "MEGA_PRETRAINED_MODEL_ARCHIVE_LIST", + "MegaForCausalLM", + "MegaForMaskedLM", + "MegaForMultipleChoice", + "MegaForQuestionAnswering", + "MegaForSequenceClassification", + "MegaForTokenClassification", + "MegaModel", + "MegaPreTrainedModel", + ] + ) + _import_structure["models.megatron_bert"].extend( + [ + "MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "MegatronBertForCausalLM", + "MegatronBertForMaskedLM", + "MegatronBertForMultipleChoice", + "MegatronBertForNextSentencePrediction", + "MegatronBertForPreTraining", + "MegatronBertForQuestionAnswering", + "MegatronBertForSequenceClassification", + "MegatronBertForTokenClassification", + "MegatronBertModel", + "MegatronBertPreTrainedModel", + ] + ) + _import_structure["models.mgp_str"].extend( + [ + "MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST", + "MgpstrForSceneTextRecognition", + "MgpstrModel", + "MgpstrPreTrainedModel", + ] + ) + _import_structure["models.mistral"].extend( + ["MistralForCausalLM", "MistralForSequenceClassification", "MistralModel", "MistralPreTrainedModel"] + ) + _import_structure["models.mobilebert"].extend( + [ + "MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "MobileBertForMaskedLM", + "MobileBertForMultipleChoice", + "MobileBertForNextSentencePrediction", + "MobileBertForPreTraining", + "MobileBertForQuestionAnswering", + "MobileBertForSequenceClassification", + "MobileBertForTokenClassification", + "MobileBertLayer", + "MobileBertModel", + "MobileBertPreTrainedModel", + "load_tf_weights_in_mobilebert", + ] + ) + _import_structure["models.mobilenet_v1"].extend( + [ + "MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST", + "MobileNetV1ForImageClassification", + "MobileNetV1Model", + "MobileNetV1PreTrainedModel", + "load_tf_weights_in_mobilenet_v1", + ] + ) + _import_structure["models.mobilenet_v2"].extend( + [ + "MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST", + "MobileNetV2ForImageClassification", + "MobileNetV2ForSemanticSegmentation", + "MobileNetV2Model", + "MobileNetV2PreTrainedModel", + "load_tf_weights_in_mobilenet_v2", + ] + ) + _import_structure["models.mobilevit"].extend( + [ + "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "MobileViTForImageClassification", + "MobileViTForSemanticSegmentation", + "MobileViTModel", + "MobileViTPreTrainedModel", + ] + ) + _import_structure["models.mobilevitv2"].extend( + [ + "MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST", + "MobileViTV2ForImageClassification", + "MobileViTV2ForSemanticSegmentation", + "MobileViTV2Model", + "MobileViTV2PreTrainedModel", + ] + ) + _import_structure["models.mpnet"].extend( + [ + "MPNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "MPNetForMaskedLM", + "MPNetForMultipleChoice", + "MPNetForQuestionAnswering", + "MPNetForSequenceClassification", + "MPNetForTokenClassification", + "MPNetLayer", + "MPNetModel", + "MPNetPreTrainedModel", + ] + ) + _import_structure["models.mpt"].extend( + [ + "MPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "MptForCausalLM", + "MptForQuestionAnswering", + "MptForSequenceClassification", + "MptForTokenClassification", + "MptModel", + "MptPreTrainedModel", + ] + ) + _import_structure["models.mra"].extend( + [ + "MRA_PRETRAINED_MODEL_ARCHIVE_LIST", + "MraForMaskedLM", + "MraForMultipleChoice", + "MraForQuestionAnswering", + "MraForSequenceClassification", + "MraForTokenClassification", + "MraModel", + "MraPreTrainedModel", + ] + ) + _import_structure["models.mt5"].extend( + [ + "MT5EncoderModel", + "MT5ForConditionalGeneration", + "MT5ForQuestionAnswering", + "MT5ForSequenceClassification", + "MT5Model", + "MT5PreTrainedModel", + ] + ) + _import_structure["models.musicgen"].extend( + [ + "MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST", + "MusicgenForCausalLM", + "MusicgenForConditionalGeneration", + "MusicgenModel", + "MusicgenPreTrainedModel", + "MusicgenProcessor", + ] + ) + _import_structure["models.mvp"].extend( + [ + "MVP_PRETRAINED_MODEL_ARCHIVE_LIST", + "MvpForCausalLM", + "MvpForConditionalGeneration", + "MvpForQuestionAnswering", + "MvpForSequenceClassification", + "MvpModel", + "MvpPreTrainedModel", + ] + ) + _import_structure["models.nat"].extend( + [ + "NAT_PRETRAINED_MODEL_ARCHIVE_LIST", + "NatBackbone", + "NatForImageClassification", + "NatModel", + "NatPreTrainedModel", + ] + ) + _import_structure["models.nezha"].extend( + [ + "NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST", + "NezhaForMaskedLM", + "NezhaForMultipleChoice", + "NezhaForNextSentencePrediction", + "NezhaForPreTraining", + "NezhaForQuestionAnswering", + "NezhaForSequenceClassification", + "NezhaForTokenClassification", + "NezhaModel", + "NezhaPreTrainedModel", + ] + ) + _import_structure["models.nllb_moe"].extend( + [ + "NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST", + "NllbMoeForConditionalGeneration", + "NllbMoeModel", + "NllbMoePreTrainedModel", + "NllbMoeSparseMLP", + "NllbMoeTop2Router", + ] + ) + _import_structure["models.nystromformer"].extend( + [ + "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "NystromformerForMaskedLM", + "NystromformerForMultipleChoice", + "NystromformerForQuestionAnswering", + "NystromformerForSequenceClassification", + "NystromformerForTokenClassification", + "NystromformerLayer", + "NystromformerModel", + "NystromformerPreTrainedModel", + ] + ) + _import_structure["models.oneformer"].extend( + [ + "ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "OneFormerForUniversalSegmentation", + "OneFormerModel", + "OneFormerPreTrainedModel", + ] + ) + _import_structure["models.openai"].extend( + [ + "OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "OpenAIGPTDoubleHeadsModel", + "OpenAIGPTForSequenceClassification", + "OpenAIGPTLMHeadModel", + "OpenAIGPTModel", + "OpenAIGPTPreTrainedModel", + "load_tf_weights_in_openai_gpt", + ] + ) + _import_structure["models.opt"].extend( + [ + "OPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "OPTForCausalLM", + "OPTForQuestionAnswering", + "OPTForSequenceClassification", + "OPTModel", + "OPTPreTrainedModel", + ] + ) + _import_structure["models.owlvit"].extend( + [ + "OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "OwlViTForObjectDetection", + "OwlViTModel", + "OwlViTPreTrainedModel", + "OwlViTTextModel", + "OwlViTVisionModel", + ] + ) + _import_structure["models.pegasus"].extend( + ["PegasusForCausalLM", "PegasusForConditionalGeneration", "PegasusModel", "PegasusPreTrainedModel"] + ) + _import_structure["models.pegasus_x"].extend( + [ + "PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST", + "PegasusXForConditionalGeneration", + "PegasusXModel", + "PegasusXPreTrainedModel", + ] + ) + _import_structure["models.perceiver"].extend( + [ + "PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST", + "PerceiverForImageClassificationConvProcessing", + "PerceiverForImageClassificationFourier", + "PerceiverForImageClassificationLearned", + "PerceiverForMaskedLM", + "PerceiverForMultimodalAutoencoding", + "PerceiverForOpticalFlow", + "PerceiverForSequenceClassification", + "PerceiverLayer", + "PerceiverModel", + "PerceiverPreTrainedModel", + ] + ) + _import_structure["models.persimmon"].extend( + ["PersimmonForCausalLM", "PersimmonForSequenceClassification", "PersimmonModel", "PersimmonPreTrainedModel"] + ) + _import_structure["models.pix2struct"].extend( + [ + "PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST", + "Pix2StructForConditionalGeneration", + "Pix2StructPreTrainedModel", + "Pix2StructTextModel", + "Pix2StructVisionModel", + ] + ) + _import_structure["models.plbart"].extend( + [ + "PLBART_PRETRAINED_MODEL_ARCHIVE_LIST", + "PLBartForCausalLM", + "PLBartForConditionalGeneration", + "PLBartForSequenceClassification", + "PLBartModel", + "PLBartPreTrainedModel", + ] + ) + _import_structure["models.poolformer"].extend( + [ + "POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "PoolFormerForImageClassification", + "PoolFormerModel", + "PoolFormerPreTrainedModel", + ] + ) + _import_structure["models.pop2piano"].extend( + [ + "POP2PIANO_PRETRAINED_MODEL_ARCHIVE_LIST", + "Pop2PianoForConditionalGeneration", + "Pop2PianoPreTrainedModel", + ] + ) + _import_structure["models.prophetnet"].extend( + [ + "PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "ProphetNetDecoder", + "ProphetNetEncoder", + "ProphetNetForCausalLM", + "ProphetNetForConditionalGeneration", + "ProphetNetModel", + "ProphetNetPreTrainedModel", + ] + ) + _import_structure["models.pvt"].extend( + [ + "PVT_PRETRAINED_MODEL_ARCHIVE_LIST", + "PvtForImageClassification", + "PvtModel", + "PvtPreTrainedModel", + ] + ) + _import_structure["models.qdqbert"].extend( + [ + "QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "QDQBertForMaskedLM", + "QDQBertForMultipleChoice", + "QDQBertForNextSentencePrediction", + "QDQBertForQuestionAnswering", + "QDQBertForSequenceClassification", + "QDQBertForTokenClassification", + "QDQBertLayer", + "QDQBertLMHeadModel", + "QDQBertModel", + "QDQBertPreTrainedModel", + "load_tf_weights_in_qdqbert", + ] + ) + _import_structure["models.rag"].extend( + ["RagModel", "RagPreTrainedModel", "RagSequenceForGeneration", "RagTokenForGeneration"] + ) + _import_structure["models.realm"].extend( + [ + "REALM_PRETRAINED_MODEL_ARCHIVE_LIST", + "RealmEmbedder", + "RealmForOpenQA", + "RealmKnowledgeAugEncoder", + "RealmPreTrainedModel", + "RealmReader", + "RealmRetriever", + "RealmScorer", + "load_tf_weights_in_realm", + ] + ) + _import_structure["models.reformer"].extend( + [ + "REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "ReformerAttention", + "ReformerForMaskedLM", + "ReformerForQuestionAnswering", + "ReformerForSequenceClassification", + "ReformerLayer", + "ReformerModel", + "ReformerModelWithLMHead", + "ReformerPreTrainedModel", + ] + ) + _import_structure["models.regnet"].extend( + [ + "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "RegNetForImageClassification", + "RegNetModel", + "RegNetPreTrainedModel", + ] + ) + _import_structure["models.rembert"].extend( + [ + "REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "RemBertForCausalLM", + "RemBertForMaskedLM", + "RemBertForMultipleChoice", + "RemBertForQuestionAnswering", + "RemBertForSequenceClassification", + "RemBertForTokenClassification", + "RemBertLayer", + "RemBertModel", + "RemBertPreTrainedModel", + "load_tf_weights_in_rembert", + ] + ) + _import_structure["models.resnet"].extend( + [ + "RESNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "ResNetBackbone", + "ResNetForImageClassification", + "ResNetModel", + "ResNetPreTrainedModel", + ] + ) + _import_structure["models.roberta"].extend( + [ + "ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "RobertaForCausalLM", + "RobertaForMaskedLM", + "RobertaForMultipleChoice", + "RobertaForQuestionAnswering", + "RobertaForSequenceClassification", + "RobertaForTokenClassification", + "RobertaModel", + "RobertaPreTrainedModel", + ] + ) + _import_structure["models.roberta_prelayernorm"].extend( + [ + "ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST", + "RobertaPreLayerNormForCausalLM", + "RobertaPreLayerNormForMaskedLM", + "RobertaPreLayerNormForMultipleChoice", + "RobertaPreLayerNormForQuestionAnswering", + "RobertaPreLayerNormForSequenceClassification", + "RobertaPreLayerNormForTokenClassification", + "RobertaPreLayerNormModel", + "RobertaPreLayerNormPreTrainedModel", + ] + ) + _import_structure["models.roc_bert"].extend( + [ + "ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "RoCBertForCausalLM", + "RoCBertForMaskedLM", + "RoCBertForMultipleChoice", + "RoCBertForPreTraining", + "RoCBertForQuestionAnswering", + "RoCBertForSequenceClassification", + "RoCBertForTokenClassification", + "RoCBertLayer", + "RoCBertModel", + "RoCBertPreTrainedModel", + "load_tf_weights_in_roc_bert", + ] + ) + _import_structure["models.roformer"].extend( + [ + "ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "RoFormerForCausalLM", + "RoFormerForMaskedLM", + "RoFormerForMultipleChoice", + "RoFormerForQuestionAnswering", + "RoFormerForSequenceClassification", + "RoFormerForTokenClassification", + "RoFormerLayer", + "RoFormerModel", + "RoFormerPreTrainedModel", + "load_tf_weights_in_roformer", + ] + ) + _import_structure["models.rwkv"].extend( + [ + "RWKV_PRETRAINED_MODEL_ARCHIVE_LIST", + "RwkvForCausalLM", + "RwkvModel", + "RwkvPreTrainedModel", + ] + ) + _import_structure["models.sam"].extend( + [ + "SAM_PRETRAINED_MODEL_ARCHIVE_LIST", + "SamModel", + "SamPreTrainedModel", + ] + ) + _import_structure["models.segformer"].extend( + [ + "SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "SegformerDecodeHead", + "SegformerForImageClassification", + "SegformerForSemanticSegmentation", + "SegformerLayer", + "SegformerModel", + "SegformerPreTrainedModel", + ] + ) + _import_structure["models.sew"].extend( + [ + "SEW_PRETRAINED_MODEL_ARCHIVE_LIST", + "SEWForCTC", + "SEWForSequenceClassification", + "SEWModel", + "SEWPreTrainedModel", + ] + ) + _import_structure["models.sew_d"].extend( + [ + "SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST", + "SEWDForCTC", + "SEWDForSequenceClassification", + "SEWDModel", + "SEWDPreTrainedModel", + ] + ) + _import_structure["models.speech_encoder_decoder"].extend(["SpeechEncoderDecoderModel"]) + _import_structure["models.speech_to_text"].extend( + [ + "SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST", + "Speech2TextForConditionalGeneration", + "Speech2TextModel", + "Speech2TextPreTrainedModel", + ] + ) + _import_structure["models.speech_to_text_2"].extend(["Speech2Text2ForCausalLM", "Speech2Text2PreTrainedModel"]) + _import_structure["models.speecht5"].extend( + [ + "SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST", + "SpeechT5ForSpeechToSpeech", + "SpeechT5ForSpeechToText", + "SpeechT5ForTextToSpeech", + "SpeechT5HifiGan", + "SpeechT5Model", + "SpeechT5PreTrainedModel", + ] + ) + _import_structure["models.splinter"].extend( + [ + "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST", + "SplinterForPreTraining", + "SplinterForQuestionAnswering", + "SplinterLayer", + "SplinterModel", + "SplinterPreTrainedModel", + ] + ) + _import_structure["models.squeezebert"].extend( + [ + "SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "SqueezeBertForMaskedLM", + "SqueezeBertForMultipleChoice", + "SqueezeBertForQuestionAnswering", + "SqueezeBertForSequenceClassification", + "SqueezeBertForTokenClassification", + "SqueezeBertModel", + "SqueezeBertModule", + "SqueezeBertPreTrainedModel", + ] + ) + _import_structure["models.swiftformer"].extend( + [ + "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "SwiftFormerForImageClassification", + "SwiftFormerModel", + "SwiftFormerPreTrainedModel", + ] + ) + _import_structure["models.swin"].extend( + [ + "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST", + "SwinBackbone", + "SwinForImageClassification", + "SwinForMaskedImageModeling", + "SwinModel", + "SwinPreTrainedModel", + ] + ) + _import_structure["models.swin2sr"].extend( + [ + "SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST", + "Swin2SRForImageSuperResolution", + "Swin2SRModel", + "Swin2SRPreTrainedModel", + ] + ) + _import_structure["models.swinv2"].extend( + [ + "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST", + "Swinv2ForImageClassification", + "Swinv2ForMaskedImageModeling", + "Swinv2Model", + "Swinv2PreTrainedModel", + ] + ) + _import_structure["models.switch_transformers"].extend( + [ + "SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST", + "SwitchTransformersEncoderModel", + "SwitchTransformersForConditionalGeneration", + "SwitchTransformersModel", + "SwitchTransformersPreTrainedModel", + "SwitchTransformersSparseMLP", + "SwitchTransformersTop1Router", + ] + ) + _import_structure["models.t5"].extend( + [ + "T5_PRETRAINED_MODEL_ARCHIVE_LIST", + "T5EncoderModel", + "T5ForConditionalGeneration", + "T5ForQuestionAnswering", + "T5ForSequenceClassification", + "T5Model", + "T5PreTrainedModel", + "load_tf_weights_in_t5", + ] + ) + _import_structure["models.table_transformer"].extend( + [ + "TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TableTransformerForObjectDetection", + "TableTransformerModel", + "TableTransformerPreTrainedModel", + ] + ) + _import_structure["models.tapas"].extend( + [ + "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST", + "TapasForMaskedLM", + "TapasForQuestionAnswering", + "TapasForSequenceClassification", + "TapasModel", + "TapasPreTrainedModel", + "load_tf_weights_in_tapas", + ] + ) + _import_structure["models.time_series_transformer"].extend( + [ + "TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TimeSeriesTransformerForPrediction", + "TimeSeriesTransformerModel", + "TimeSeriesTransformerPreTrainedModel", + ] + ) + _import_structure["models.timesformer"].extend( + [ + "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TimesformerForVideoClassification", + "TimesformerModel", + "TimesformerPreTrainedModel", + ] + ) + _import_structure["models.timm_backbone"].extend(["TimmBackbone"]) + _import_structure["models.transfo_xl"].extend( + [ + "TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST", + "AdaptiveEmbedding", + "TransfoXLForSequenceClassification", + "TransfoXLLMHeadModel", + "TransfoXLModel", + "TransfoXLPreTrainedModel", + "load_tf_weights_in_transfo_xl", + ] + ) + _import_structure["models.trocr"].extend( + ["TROCR_PRETRAINED_MODEL_ARCHIVE_LIST", "TrOCRForCausalLM", "TrOCRPreTrainedModel"] + ) + _import_structure["models.tvlt"].extend( + [ + "TVLT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TvltForAudioVisualClassification", + "TvltForPreTraining", + "TvltModel", + "TvltPreTrainedModel", + ] + ) + _import_structure["models.umt5"].extend( + [ + "UMT5EncoderModel", + "UMT5ForConditionalGeneration", + "UMT5ForQuestionAnswering", + "UMT5ForSequenceClassification", + "UMT5Model", + "UMT5PreTrainedModel", + ] + ) + _import_structure["models.unispeech"].extend( + [ + "UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST", + "UniSpeechForCTC", + "UniSpeechForPreTraining", + "UniSpeechForSequenceClassification", + "UniSpeechModel", + "UniSpeechPreTrainedModel", + ] + ) + _import_structure["models.unispeech_sat"].extend( + [ + "UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST", + "UniSpeechSatForAudioFrameClassification", + "UniSpeechSatForCTC", + "UniSpeechSatForPreTraining", + "UniSpeechSatForSequenceClassification", + "UniSpeechSatForXVector", + "UniSpeechSatModel", + "UniSpeechSatPreTrainedModel", + ] + ) + _import_structure["models.upernet"].extend( + [ + "UperNetForSemanticSegmentation", + "UperNetPreTrainedModel", + ] + ) + _import_structure["models.videomae"].extend( + [ + "VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST", + "VideoMAEForPreTraining", + "VideoMAEForVideoClassification", + "VideoMAEModel", + "VideoMAEPreTrainedModel", + ] + ) + _import_structure["models.vilt"].extend( + [ + "VILT_PRETRAINED_MODEL_ARCHIVE_LIST", + "ViltForImageAndTextRetrieval", + "ViltForImagesAndTextClassification", + "ViltForMaskedLM", + "ViltForQuestionAnswering", + "ViltForTokenClassification", + "ViltLayer", + "ViltModel", + "ViltPreTrainedModel", + ] + ) + _import_structure["models.vision_encoder_decoder"].extend(["VisionEncoderDecoderModel"]) + _import_structure["models.vision_text_dual_encoder"].extend(["VisionTextDualEncoderModel"]) + _import_structure["models.visual_bert"].extend( + [ + "VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "VisualBertForMultipleChoice", + "VisualBertForPreTraining", + "VisualBertForQuestionAnswering", + "VisualBertForRegionToPhraseAlignment", + "VisualBertForVisualReasoning", + "VisualBertLayer", + "VisualBertModel", + "VisualBertPreTrainedModel", + ] + ) + _import_structure["models.vit"].extend( + [ + "VIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "ViTForImageClassification", + "ViTForMaskedImageModeling", + "ViTModel", + "ViTPreTrainedModel", + ] + ) + _import_structure["models.vit_hybrid"].extend( + [ + "VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST", + "ViTHybridForImageClassification", + "ViTHybridModel", + "ViTHybridPreTrainedModel", + ] + ) + _import_structure["models.vit_mae"].extend( + [ + "VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST", + "ViTMAEForPreTraining", + "ViTMAELayer", + "ViTMAEModel", + "ViTMAEPreTrainedModel", + ] + ) + _import_structure["models.vit_msn"].extend( + [ + "VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST", + "ViTMSNForImageClassification", + "ViTMSNModel", + "ViTMSNPreTrainedModel", + ] + ) + _import_structure["models.vitdet"].extend( + [ + "VITDET_PRETRAINED_MODEL_ARCHIVE_LIST", + "VitDetBackbone", + "VitDetModel", + "VitDetPreTrainedModel", + ] + ) + _import_structure["models.vitmatte"].extend( + [ + "VITMATTE_PRETRAINED_MODEL_ARCHIVE_LIST", + "VitMatteForImageMatting", + "VitMattePreTrainedModel", + ] + ) + _import_structure["models.vits"].extend( + [ + "VITS_PRETRAINED_MODEL_ARCHIVE_LIST", + "VitsModel", + "VitsPreTrainedModel", + ] + ) + _import_structure["models.vivit"].extend( + [ + "VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "VivitForVideoClassification", + "VivitModel", + "VivitPreTrainedModel", + ] + ) + _import_structure["models.wav2vec2"].extend( + [ + "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST", + "Wav2Vec2ForAudioFrameClassification", + "Wav2Vec2ForCTC", + "Wav2Vec2ForMaskedLM", + "Wav2Vec2ForPreTraining", + "Wav2Vec2ForSequenceClassification", + "Wav2Vec2ForXVector", + "Wav2Vec2Model", + "Wav2Vec2PreTrainedModel", + ] + ) + _import_structure["models.wav2vec2_conformer"].extend( + [ + "WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "Wav2Vec2ConformerForAudioFrameClassification", + "Wav2Vec2ConformerForCTC", + "Wav2Vec2ConformerForPreTraining", + "Wav2Vec2ConformerForSequenceClassification", + "Wav2Vec2ConformerForXVector", + "Wav2Vec2ConformerModel", + "Wav2Vec2ConformerPreTrainedModel", + ] + ) + _import_structure["models.wavlm"].extend( + [ + "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "WavLMForAudioFrameClassification", + "WavLMForCTC", + "WavLMForSequenceClassification", + "WavLMForXVector", + "WavLMModel", + "WavLMPreTrainedModel", + ] + ) + _import_structure["models.whisper"].extend( + [ + "WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST", + "WhisperForAudioClassification", + "WhisperForConditionalGeneration", + "WhisperModel", + "WhisperPreTrainedModel", + ] + ) + _import_structure["models.x_clip"].extend( + [ + "XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "XCLIPModel", + "XCLIPPreTrainedModel", + "XCLIPTextModel", + "XCLIPVisionModel", + ] + ) + _import_structure["models.xglm"].extend( + [ + "XGLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "XGLMForCausalLM", + "XGLMModel", + "XGLMPreTrainedModel", + ] + ) + _import_structure["models.xlm"].extend( + [ + "XLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "XLMForMultipleChoice", + "XLMForQuestionAnswering", + "XLMForQuestionAnsweringSimple", + "XLMForSequenceClassification", + "XLMForTokenClassification", + "XLMModel", + "XLMPreTrainedModel", + "XLMWithLMHeadModel", + ] + ) + _import_structure["models.xlm_prophetnet"].extend( + [ + "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "XLMProphetNetDecoder", + "XLMProphetNetEncoder", + "XLMProphetNetForCausalLM", + "XLMProphetNetForConditionalGeneration", + "XLMProphetNetModel", + "XLMProphetNetPreTrainedModel", + ] + ) + _import_structure["models.xlm_roberta"].extend( + [ + "XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "XLMRobertaForCausalLM", + "XLMRobertaForMaskedLM", + "XLMRobertaForMultipleChoice", + "XLMRobertaForQuestionAnswering", + "XLMRobertaForSequenceClassification", + "XLMRobertaForTokenClassification", + "XLMRobertaModel", + "XLMRobertaPreTrainedModel", + ] + ) + _import_structure["models.xlm_roberta_xl"].extend( + [ + "XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST", + "XLMRobertaXLForCausalLM", + "XLMRobertaXLForMaskedLM", + "XLMRobertaXLForMultipleChoice", + "XLMRobertaXLForQuestionAnswering", + "XLMRobertaXLForSequenceClassification", + "XLMRobertaXLForTokenClassification", + "XLMRobertaXLModel", + "XLMRobertaXLPreTrainedModel", + ] + ) + _import_structure["models.xlnet"].extend( + [ + "XLNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "XLNetForMultipleChoice", + "XLNetForQuestionAnswering", + "XLNetForQuestionAnsweringSimple", + "XLNetForSequenceClassification", + "XLNetForTokenClassification", + "XLNetLMHeadModel", + "XLNetModel", + "XLNetPreTrainedModel", + "load_tf_weights_in_xlnet", + ] + ) + _import_structure["models.xmod"].extend( + [ + "XMOD_PRETRAINED_MODEL_ARCHIVE_LIST", + "XmodForCausalLM", + "XmodForMaskedLM", + "XmodForMultipleChoice", + "XmodForQuestionAnswering", + "XmodForSequenceClassification", + "XmodForTokenClassification", + "XmodModel", + "XmodPreTrainedModel", + ] + ) + _import_structure["models.yolos"].extend( + [ + "YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST", + "YolosForObjectDetection", + "YolosModel", + "YolosPreTrainedModel", + ] + ) + _import_structure["models.yoso"].extend( + [ + "YOSO_PRETRAINED_MODEL_ARCHIVE_LIST", + "YosoForMaskedLM", + "YosoForMultipleChoice", + "YosoForQuestionAnswering", + "YosoForSequenceClassification", + "YosoForTokenClassification", + "YosoLayer", + "YosoModel", + "YosoPreTrainedModel", + ] + ) + _import_structure["optimization"] = [ + "Adafactor", + "AdamW", + "get_constant_schedule", + "get_constant_schedule_with_warmup", + "get_cosine_schedule_with_warmup", + "get_cosine_with_hard_restarts_schedule_with_warmup", + "get_inverse_sqrt_schedule", + "get_linear_schedule_with_warmup", + "get_polynomial_decay_schedule_with_warmup", + "get_scheduler", + ] + _import_structure["pytorch_utils"] = ["Conv1D", "apply_chunking_to_forward", "prune_layer"] + _import_structure["sagemaker"] = [] + _import_structure["time_series_utils"] = [] + _import_structure["trainer"] = ["Trainer"] + _import_structure["trainer_pt_utils"] = ["torch_distributed_zero_first"] + _import_structure["trainer_seq2seq"] = ["Seq2SeqTrainer"] + +# TensorFlow-backed objects +try: + if not is_tf_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_tf_objects + + _import_structure["utils.dummy_tf_objects"] = [name for name in dir(dummy_tf_objects) if not name.startswith("_")] +else: + _import_structure["activations_tf"] = [] + _import_structure["benchmark.benchmark_args_tf"] = ["TensorFlowBenchmarkArguments"] + _import_structure["benchmark.benchmark_tf"] = ["TensorFlowBenchmark"] + _import_structure["generation"].extend( + [ + "TFForcedBOSTokenLogitsProcessor", + "TFForcedEOSTokenLogitsProcessor", + "TFForceTokensLogitsProcessor", + "TFGenerationMixin", + "TFLogitsProcessor", + "TFLogitsProcessorList", + "TFLogitsWarper", + "TFMinLengthLogitsProcessor", + "TFNoBadWordsLogitsProcessor", + "TFNoRepeatNGramLogitsProcessor", + "TFRepetitionPenaltyLogitsProcessor", + "TFSuppressTokensAtBeginLogitsProcessor", + "TFSuppressTokensLogitsProcessor", + "TFTemperatureLogitsWarper", + "TFTopKLogitsWarper", + "TFTopPLogitsWarper", + "tf_top_k_top_p_filtering", + ] + ) + _import_structure["generation_tf_utils"] = [] + _import_structure["keras_callbacks"] = ["KerasMetricCallback", "PushToHubCallback"] + _import_structure["modeling_tf_outputs"] = [] + _import_structure["modeling_tf_utils"] = [ + "TFPreTrainedModel", + "TFSequenceSummary", + "TFSharedEmbeddings", + "shape_list", + ] + # TensorFlow models structure + _import_structure["models.albert"].extend( + [ + "TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFAlbertForMaskedLM", + "TFAlbertForMultipleChoice", + "TFAlbertForPreTraining", + "TFAlbertForQuestionAnswering", + "TFAlbertForSequenceClassification", + "TFAlbertForTokenClassification", + "TFAlbertMainLayer", + "TFAlbertModel", + "TFAlbertPreTrainedModel", + ] + ) + _import_structure["models.auto"].extend( + [ + "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", + "TF_MODEL_FOR_CAUSAL_LM_MAPPING", + "TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING", + "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", + "TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING", + "TF_MODEL_FOR_MASKED_LM_MAPPING", + "TF_MODEL_FOR_MASK_GENERATION_MAPPING", + "TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING", + "TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING", + "TF_MODEL_FOR_PRETRAINING_MAPPING", + "TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING", + "TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING", + "TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING", + "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", + "TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING", + "TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING", + "TF_MODEL_FOR_TEXT_ENCODING_MAPPING", + "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", + "TF_MODEL_FOR_VISION_2_SEQ_MAPPING", + "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", + "TF_MODEL_MAPPING", + "TF_MODEL_WITH_LM_HEAD_MAPPING", + "TFAutoModel", + "TFAutoModelForAudioClassification", + "TFAutoModelForCausalLM", + "TFAutoModelForDocumentQuestionAnswering", + "TFAutoModelForImageClassification", + "TFAutoModelForMaskedImageModeling", + "TFAutoModelForMaskedLM", + "TFAutoModelForMaskGeneration", + "TFAutoModelForMultipleChoice", + "TFAutoModelForNextSentencePrediction", + "TFAutoModelForPreTraining", + "TFAutoModelForQuestionAnswering", + "TFAutoModelForSemanticSegmentation", + "TFAutoModelForSeq2SeqLM", + "TFAutoModelForSequenceClassification", + "TFAutoModelForSpeechSeq2Seq", + "TFAutoModelForTableQuestionAnswering", + "TFAutoModelForTextEncoding", + "TFAutoModelForTokenClassification", + "TFAutoModelForVision2Seq", + "TFAutoModelForZeroShotImageClassification", + "TFAutoModelWithLMHead", + ] + ) + _import_structure["models.bart"].extend( + ["TFBartForConditionalGeneration", "TFBartForSequenceClassification", "TFBartModel", "TFBartPretrainedModel"] + ) + _import_structure["models.bert"].extend( + [ + "TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFBertEmbeddings", + "TFBertForMaskedLM", + "TFBertForMultipleChoice", + "TFBertForNextSentencePrediction", + "TFBertForPreTraining", + "TFBertForQuestionAnswering", + "TFBertForSequenceClassification", + "TFBertForTokenClassification", + "TFBertLMHeadModel", + "TFBertMainLayer", + "TFBertModel", + "TFBertPreTrainedModel", + ] + ) + _import_structure["models.blenderbot"].extend( + ["TFBlenderbotForConditionalGeneration", "TFBlenderbotModel", "TFBlenderbotPreTrainedModel"] + ) + _import_structure["models.blenderbot_small"].extend( + ["TFBlenderbotSmallForConditionalGeneration", "TFBlenderbotSmallModel", "TFBlenderbotSmallPreTrainedModel"] + ) + _import_structure["models.blip"].extend( + [ + "TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFBlipForConditionalGeneration", + "TFBlipForImageTextRetrieval", + "TFBlipForQuestionAnswering", + "TFBlipModel", + "TFBlipPreTrainedModel", + "TFBlipTextModel", + "TFBlipVisionModel", + ] + ) + _import_structure["models.camembert"].extend( + [ + "TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFCamembertForCausalLM", + "TFCamembertForMaskedLM", + "TFCamembertForMultipleChoice", + "TFCamembertForQuestionAnswering", + "TFCamembertForSequenceClassification", + "TFCamembertForTokenClassification", + "TFCamembertModel", + "TFCamembertPreTrainedModel", + ] + ) + _import_structure["models.clip"].extend( + [ + "TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFCLIPModel", + "TFCLIPPreTrainedModel", + "TFCLIPTextModel", + "TFCLIPVisionModel", + ] + ) + _import_structure["models.convbert"].extend( + [ + "TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFConvBertForMaskedLM", + "TFConvBertForMultipleChoice", + "TFConvBertForQuestionAnswering", + "TFConvBertForSequenceClassification", + "TFConvBertForTokenClassification", + "TFConvBertLayer", + "TFConvBertModel", + "TFConvBertPreTrainedModel", + ] + ) + _import_structure["models.convnext"].extend( + [ + "TFConvNextForImageClassification", + "TFConvNextModel", + "TFConvNextPreTrainedModel", + ] + ) + _import_structure["models.ctrl"].extend( + [ + "TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFCTRLForSequenceClassification", + "TFCTRLLMHeadModel", + "TFCTRLModel", + "TFCTRLPreTrainedModel", + ] + ) + _import_structure["models.cvt"].extend( + [ + "TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFCvtForImageClassification", + "TFCvtModel", + "TFCvtPreTrainedModel", + ] + ) + _import_structure["models.data2vec"].extend( + [ + "TFData2VecVisionForImageClassification", + "TFData2VecVisionForSemanticSegmentation", + "TFData2VecVisionModel", + "TFData2VecVisionPreTrainedModel", + ] + ) + _import_structure["models.deberta"].extend( + [ + "TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFDebertaForMaskedLM", + "TFDebertaForQuestionAnswering", + "TFDebertaForSequenceClassification", + "TFDebertaForTokenClassification", + "TFDebertaModel", + "TFDebertaPreTrainedModel", + ] + ) + _import_structure["models.deberta_v2"].extend( + [ + "TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFDebertaV2ForMaskedLM", + "TFDebertaV2ForMultipleChoice", + "TFDebertaV2ForQuestionAnswering", + "TFDebertaV2ForSequenceClassification", + "TFDebertaV2ForTokenClassification", + "TFDebertaV2Model", + "TFDebertaV2PreTrainedModel", + ] + ) + _import_structure["models.deit"].extend( + [ + "TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFDeiTForImageClassification", + "TFDeiTForImageClassificationWithTeacher", + "TFDeiTForMaskedImageModeling", + "TFDeiTModel", + "TFDeiTPreTrainedModel", + ] + ) + _import_structure["models.distilbert"].extend( + [ + "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFDistilBertForMaskedLM", + "TFDistilBertForMultipleChoice", + "TFDistilBertForQuestionAnswering", + "TFDistilBertForSequenceClassification", + "TFDistilBertForTokenClassification", + "TFDistilBertMainLayer", + "TFDistilBertModel", + "TFDistilBertPreTrainedModel", + ] + ) + _import_structure["models.dpr"].extend( + [ + "TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFDPRContextEncoder", + "TFDPRPretrainedContextEncoder", + "TFDPRPretrainedQuestionEncoder", + "TFDPRPretrainedReader", + "TFDPRQuestionEncoder", + "TFDPRReader", + ] + ) + _import_structure["models.efficientformer"].extend( + [ + "TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFEfficientFormerForImageClassification", + "TFEfficientFormerForImageClassificationWithTeacher", + "TFEfficientFormerModel", + "TFEfficientFormerPreTrainedModel", + ] + ) + _import_structure["models.electra"].extend( + [ + "TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFElectraForMaskedLM", + "TFElectraForMultipleChoice", + "TFElectraForPreTraining", + "TFElectraForQuestionAnswering", + "TFElectraForSequenceClassification", + "TFElectraForTokenClassification", + "TFElectraModel", + "TFElectraPreTrainedModel", + ] + ) + _import_structure["models.encoder_decoder"].append("TFEncoderDecoderModel") + _import_structure["models.esm"].extend( + [ + "ESM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFEsmForMaskedLM", + "TFEsmForSequenceClassification", + "TFEsmForTokenClassification", + "TFEsmModel", + "TFEsmPreTrainedModel", + ] + ) + _import_structure["models.flaubert"].extend( + [ + "TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFFlaubertForMultipleChoice", + "TFFlaubertForQuestionAnsweringSimple", + "TFFlaubertForSequenceClassification", + "TFFlaubertForTokenClassification", + "TFFlaubertModel", + "TFFlaubertPreTrainedModel", + "TFFlaubertWithLMHeadModel", + ] + ) + _import_structure["models.funnel"].extend( + [ + "TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFFunnelBaseModel", + "TFFunnelForMaskedLM", + "TFFunnelForMultipleChoice", + "TFFunnelForPreTraining", + "TFFunnelForQuestionAnswering", + "TFFunnelForSequenceClassification", + "TFFunnelForTokenClassification", + "TFFunnelModel", + "TFFunnelPreTrainedModel", + ] + ) + _import_structure["models.gpt2"].extend( + [ + "TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFGPT2DoubleHeadsModel", + "TFGPT2ForSequenceClassification", + "TFGPT2LMHeadModel", + "TFGPT2MainLayer", + "TFGPT2Model", + "TFGPT2PreTrainedModel", + ] + ) + _import_structure["models.gptj"].extend( + [ + "TFGPTJForCausalLM", + "TFGPTJForQuestionAnswering", + "TFGPTJForSequenceClassification", + "TFGPTJModel", + "TFGPTJPreTrainedModel", + ] + ) + _import_structure["models.groupvit"].extend( + [ + "TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFGroupViTModel", + "TFGroupViTPreTrainedModel", + "TFGroupViTTextModel", + "TFGroupViTVisionModel", + ] + ) + _import_structure["models.hubert"].extend( + [ + "TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFHubertForCTC", + "TFHubertModel", + "TFHubertPreTrainedModel", + ] + ) + _import_structure["models.layoutlm"].extend( + [ + "TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFLayoutLMForMaskedLM", + "TFLayoutLMForQuestionAnswering", + "TFLayoutLMForSequenceClassification", + "TFLayoutLMForTokenClassification", + "TFLayoutLMMainLayer", + "TFLayoutLMModel", + "TFLayoutLMPreTrainedModel", + ] + ) + _import_structure["models.layoutlmv3"].extend( + [ + "TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFLayoutLMv3ForQuestionAnswering", + "TFLayoutLMv3ForSequenceClassification", + "TFLayoutLMv3ForTokenClassification", + "TFLayoutLMv3Model", + "TFLayoutLMv3PreTrainedModel", + ] + ) + _import_structure["models.led"].extend(["TFLEDForConditionalGeneration", "TFLEDModel", "TFLEDPreTrainedModel"]) + _import_structure["models.longformer"].extend( + [ + "TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFLongformerForMaskedLM", + "TFLongformerForMultipleChoice", + "TFLongformerForQuestionAnswering", + "TFLongformerForSequenceClassification", + "TFLongformerForTokenClassification", + "TFLongformerModel", + "TFLongformerPreTrainedModel", + "TFLongformerSelfAttention", + ] + ) + _import_structure["models.lxmert"].extend( + [ + "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFLxmertForPreTraining", + "TFLxmertMainLayer", + "TFLxmertModel", + "TFLxmertPreTrainedModel", + "TFLxmertVisualFeatureEncoder", + ] + ) + _import_structure["models.marian"].extend(["TFMarianModel", "TFMarianMTModel", "TFMarianPreTrainedModel"]) + _import_structure["models.mbart"].extend( + ["TFMBartForConditionalGeneration", "TFMBartModel", "TFMBartPreTrainedModel"] + ) + _import_structure["models.mobilebert"].extend( + [ + "TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFMobileBertForMaskedLM", + "TFMobileBertForMultipleChoice", + "TFMobileBertForNextSentencePrediction", + "TFMobileBertForPreTraining", + "TFMobileBertForQuestionAnswering", + "TFMobileBertForSequenceClassification", + "TFMobileBertForTokenClassification", + "TFMobileBertMainLayer", + "TFMobileBertModel", + "TFMobileBertPreTrainedModel", + ] + ) + _import_structure["models.mobilevit"].extend( + [ + "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFMobileViTForImageClassification", + "TFMobileViTForSemanticSegmentation", + "TFMobileViTModel", + "TFMobileViTPreTrainedModel", + ] + ) + _import_structure["models.mpnet"].extend( + [ + "TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFMPNetForMaskedLM", + "TFMPNetForMultipleChoice", + "TFMPNetForQuestionAnswering", + "TFMPNetForSequenceClassification", + "TFMPNetForTokenClassification", + "TFMPNetMainLayer", + "TFMPNetModel", + "TFMPNetPreTrainedModel", + ] + ) + _import_structure["models.mt5"].extend(["TFMT5EncoderModel", "TFMT5ForConditionalGeneration", "TFMT5Model"]) + _import_structure["models.openai"].extend( + [ + "TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFOpenAIGPTDoubleHeadsModel", + "TFOpenAIGPTForSequenceClassification", + "TFOpenAIGPTLMHeadModel", + "TFOpenAIGPTMainLayer", + "TFOpenAIGPTModel", + "TFOpenAIGPTPreTrainedModel", + ] + ) + _import_structure["models.opt"].extend( + [ + "TFOPTForCausalLM", + "TFOPTModel", + "TFOPTPreTrainedModel", + ] + ) + _import_structure["models.pegasus"].extend( + ["TFPegasusForConditionalGeneration", "TFPegasusModel", "TFPegasusPreTrainedModel"] + ) + _import_structure["models.rag"].extend( + [ + "TFRagModel", + "TFRagPreTrainedModel", + "TFRagSequenceForGeneration", + "TFRagTokenForGeneration", + ] + ) + _import_structure["models.regnet"].extend( + [ + "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFRegNetForImageClassification", + "TFRegNetModel", + "TFRegNetPreTrainedModel", + ] + ) + _import_structure["models.rembert"].extend( + [ + "TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFRemBertForCausalLM", + "TFRemBertForMaskedLM", + "TFRemBertForMultipleChoice", + "TFRemBertForQuestionAnswering", + "TFRemBertForSequenceClassification", + "TFRemBertForTokenClassification", + "TFRemBertLayer", + "TFRemBertModel", + "TFRemBertPreTrainedModel", + ] + ) + _import_structure["models.resnet"].extend( + [ + "TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFResNetForImageClassification", + "TFResNetModel", + "TFResNetPreTrainedModel", + ] + ) + _import_structure["models.roberta"].extend( + [ + "TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFRobertaForCausalLM", + "TFRobertaForMaskedLM", + "TFRobertaForMultipleChoice", + "TFRobertaForQuestionAnswering", + "TFRobertaForSequenceClassification", + "TFRobertaForTokenClassification", + "TFRobertaMainLayer", + "TFRobertaModel", + "TFRobertaPreTrainedModel", + ] + ) + _import_structure["models.roberta_prelayernorm"].extend( + [ + "TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFRobertaPreLayerNormForCausalLM", + "TFRobertaPreLayerNormForMaskedLM", + "TFRobertaPreLayerNormForMultipleChoice", + "TFRobertaPreLayerNormForQuestionAnswering", + "TFRobertaPreLayerNormForSequenceClassification", + "TFRobertaPreLayerNormForTokenClassification", + "TFRobertaPreLayerNormMainLayer", + "TFRobertaPreLayerNormModel", + "TFRobertaPreLayerNormPreTrainedModel", + ] + ) + _import_structure["models.roformer"].extend( + [ + "TF_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFRoFormerForCausalLM", + "TFRoFormerForMaskedLM", + "TFRoFormerForMultipleChoice", + "TFRoFormerForQuestionAnswering", + "TFRoFormerForSequenceClassification", + "TFRoFormerForTokenClassification", + "TFRoFormerLayer", + "TFRoFormerModel", + "TFRoFormerPreTrainedModel", + ] + ) + _import_structure["models.sam"].extend( + [ + "TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFSamModel", + "TFSamPreTrainedModel", + ] + ) + _import_structure["models.segformer"].extend( + [ + "TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFSegformerDecodeHead", + "TFSegformerForImageClassification", + "TFSegformerForSemanticSegmentation", + "TFSegformerModel", + "TFSegformerPreTrainedModel", + ] + ) + _import_structure["models.speech_to_text"].extend( + [ + "TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFSpeech2TextForConditionalGeneration", + "TFSpeech2TextModel", + "TFSpeech2TextPreTrainedModel", + ] + ) + _import_structure["models.swin"].extend( + [ + "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFSwinForImageClassification", + "TFSwinForMaskedImageModeling", + "TFSwinModel", + "TFSwinPreTrainedModel", + ] + ) + _import_structure["models.t5"].extend( + [ + "TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFT5EncoderModel", + "TFT5ForConditionalGeneration", + "TFT5Model", + "TFT5PreTrainedModel", + ] + ) + _import_structure["models.tapas"].extend( + [ + "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFTapasForMaskedLM", + "TFTapasForQuestionAnswering", + "TFTapasForSequenceClassification", + "TFTapasModel", + "TFTapasPreTrainedModel", + ] + ) + _import_structure["models.transfo_xl"].extend( + [ + "TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFAdaptiveEmbedding", + "TFTransfoXLForSequenceClassification", + "TFTransfoXLLMHeadModel", + "TFTransfoXLMainLayer", + "TFTransfoXLModel", + "TFTransfoXLPreTrainedModel", + ] + ) + _import_structure["models.vision_encoder_decoder"].extend(["TFVisionEncoderDecoderModel"]) + _import_structure["models.vision_text_dual_encoder"].extend(["TFVisionTextDualEncoderModel"]) + _import_structure["models.vit"].extend( + [ + "TFViTForImageClassification", + "TFViTModel", + "TFViTPreTrainedModel", + ] + ) + _import_structure["models.vit_mae"].extend( + [ + "TFViTMAEForPreTraining", + "TFViTMAEModel", + "TFViTMAEPreTrainedModel", + ] + ) + _import_structure["models.wav2vec2"].extend( + [ + "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFWav2Vec2ForCTC", + "TFWav2Vec2ForSequenceClassification", + "TFWav2Vec2Model", + "TFWav2Vec2PreTrainedModel", + ] + ) + _import_structure["models.whisper"].extend( + [ + "TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFWhisperForConditionalGeneration", + "TFWhisperModel", + "TFWhisperPreTrainedModel", + ] + ) + _import_structure["models.xglm"].extend( + [ + "TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFXGLMForCausalLM", + "TFXGLMModel", + "TFXGLMPreTrainedModel", + ] + ) + _import_structure["models.xlm"].extend( + [ + "TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFXLMForMultipleChoice", + "TFXLMForQuestionAnsweringSimple", + "TFXLMForSequenceClassification", + "TFXLMForTokenClassification", + "TFXLMMainLayer", + "TFXLMModel", + "TFXLMPreTrainedModel", + "TFXLMWithLMHeadModel", + ] + ) + _import_structure["models.xlm_roberta"].extend( + [ + "TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFXLMRobertaForCausalLM", + "TFXLMRobertaForMaskedLM", + "TFXLMRobertaForMultipleChoice", + "TFXLMRobertaForQuestionAnswering", + "TFXLMRobertaForSequenceClassification", + "TFXLMRobertaForTokenClassification", + "TFXLMRobertaModel", + "TFXLMRobertaPreTrainedModel", + ] + ) + _import_structure["models.xlnet"].extend( + [ + "TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST", + "TFXLNetForMultipleChoice", + "TFXLNetForQuestionAnsweringSimple", + "TFXLNetForSequenceClassification", + "TFXLNetForTokenClassification", + "TFXLNetLMHeadModel", + "TFXLNetMainLayer", + "TFXLNetModel", + "TFXLNetPreTrainedModel", + ] + ) + _import_structure["optimization_tf"] = ["AdamWeightDecay", "GradientAccumulator", "WarmUp", "create_optimizer"] + _import_structure["tf_utils"] = [] + _import_structure["trainer_tf"] = ["TFTrainer"] + + +try: + if not ( + is_librosa_available() + and is_essentia_available() + and is_scipy_available() + and is_torch_available() + and is_pretty_midi_available() + ): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects + + _import_structure["utils.dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects"] = [ + name + for name in dir(dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects) + if not name.startswith("_") + ] +else: + _import_structure["models.pop2piano"].append("Pop2PianoFeatureExtractor") + _import_structure["models.pop2piano"].append("Pop2PianoTokenizer") + _import_structure["models.pop2piano"].append("Pop2PianoProcessor") + + +# FLAX-backed objects +try: + if not is_flax_available(): + raise OptionalDependencyNotAvailable() +except OptionalDependencyNotAvailable: + from .utils import dummy_flax_objects + + _import_structure["utils.dummy_flax_objects"] = [ + name for name in dir(dummy_flax_objects) if not name.startswith("_") + ] +else: + _import_structure["generation"].extend( + [ + "FlaxForcedBOSTokenLogitsProcessor", + "FlaxForcedEOSTokenLogitsProcessor", + "FlaxForceTokensLogitsProcessor", + "FlaxGenerationMixin", + "FlaxLogitsProcessor", + "FlaxLogitsProcessorList", + "FlaxLogitsWarper", + "FlaxMinLengthLogitsProcessor", + "FlaxTemperatureLogitsWarper", + "FlaxSuppressTokensAtBeginLogitsProcessor", + "FlaxSuppressTokensLogitsProcessor", + "FlaxTopKLogitsWarper", + "FlaxTopPLogitsWarper", + "FlaxWhisperTimeStampLogitsProcessor", + ] + ) + _import_structure["generation_flax_utils"] = [] + _import_structure["modeling_flax_outputs"] = [] + _import_structure["modeling_flax_utils"] = ["FlaxPreTrainedModel"] + _import_structure["models.albert"].extend( + [ + "FlaxAlbertForMaskedLM", + "FlaxAlbertForMultipleChoice", + "FlaxAlbertForPreTraining", + "FlaxAlbertForQuestionAnswering", + "FlaxAlbertForSequenceClassification", + "FlaxAlbertForTokenClassification", + "FlaxAlbertModel", + "FlaxAlbertPreTrainedModel", + ] + ) + _import_structure["models.auto"].extend( + [ + "FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", + "FLAX_MODEL_FOR_CAUSAL_LM_MAPPING", + "FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", + "FLAX_MODEL_FOR_MASKED_LM_MAPPING", + "FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING", + "FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING", + "FLAX_MODEL_FOR_PRETRAINING_MAPPING", + "FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING", + "FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING", + "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", + "FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING", + "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", + "FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING", + "FLAX_MODEL_MAPPING", + "FlaxAutoModel", + "FlaxAutoModelForCausalLM", + "FlaxAutoModelForImageClassification", + "FlaxAutoModelForMaskedLM", + "FlaxAutoModelForMultipleChoice", + "FlaxAutoModelForNextSentencePrediction", + "FlaxAutoModelForPreTraining", + "FlaxAutoModelForQuestionAnswering", + "FlaxAutoModelForSeq2SeqLM", + "FlaxAutoModelForSequenceClassification", + "FlaxAutoModelForSpeechSeq2Seq", + "FlaxAutoModelForTokenClassification", + "FlaxAutoModelForVision2Seq", + ] + ) + + # Flax models structure + + _import_structure["models.bart"].extend( + [ + "FlaxBartDecoderPreTrainedModel", + "FlaxBartForCausalLM", + "FlaxBartForConditionalGeneration", + "FlaxBartForQuestionAnswering", + "FlaxBartForSequenceClassification", + "FlaxBartModel", + "FlaxBartPreTrainedModel", + ] + ) + _import_structure["models.beit"].extend( + [ + "FlaxBeitForImageClassification", + "FlaxBeitForMaskedImageModeling", + "FlaxBeitModel", + "FlaxBeitPreTrainedModel", + ] + ) + + _import_structure["models.bert"].extend( + [ + "FlaxBertForCausalLM", + "FlaxBertForMaskedLM", + "FlaxBertForMultipleChoice", + "FlaxBertForNextSentencePrediction", + "FlaxBertForPreTraining", + "FlaxBertForQuestionAnswering", + "FlaxBertForSequenceClassification", + "FlaxBertForTokenClassification", + "FlaxBertModel", + "FlaxBertPreTrainedModel", + ] + ) + _import_structure["models.big_bird"].extend( + [ + "FlaxBigBirdForCausalLM", + "FlaxBigBirdForMaskedLM", + "FlaxBigBirdForMultipleChoice", + "FlaxBigBirdForPreTraining", + "FlaxBigBirdForQuestionAnswering", + "FlaxBigBirdForSequenceClassification", + "FlaxBigBirdForTokenClassification", + "FlaxBigBirdModel", + "FlaxBigBirdPreTrainedModel", + ] + ) + _import_structure["models.blenderbot"].extend( + ["FlaxBlenderbotForConditionalGeneration", "FlaxBlenderbotModel", "FlaxBlenderbotPreTrainedModel"] + ) + _import_structure["models.blenderbot_small"].extend( + [ + "FlaxBlenderbotSmallForConditionalGeneration", + "FlaxBlenderbotSmallModel", + "FlaxBlenderbotSmallPreTrainedModel", + ] + ) + _import_structure["models.bloom"].extend( + [ + "FlaxBloomForCausalLM", + "FlaxBloomModel", + "FlaxBloomPreTrainedModel", + ] + ) + _import_structure["models.clip"].extend( + [ + "FlaxCLIPModel", + "FlaxCLIPPreTrainedModel", + "FlaxCLIPTextModel", + "FlaxCLIPTextPreTrainedModel", + "FlaxCLIPTextModelWithProjection", + "FlaxCLIPVisionModel", + "FlaxCLIPVisionPreTrainedModel", + ] + ) + _import_structure["models.distilbert"].extend( + [ + "FlaxDistilBertForMaskedLM", + "FlaxDistilBertForMultipleChoice", + "FlaxDistilBertForQuestionAnswering", + "FlaxDistilBertForSequenceClassification", + "FlaxDistilBertForTokenClassification", + "FlaxDistilBertModel", + "FlaxDistilBertPreTrainedModel", + ] + ) + _import_structure["models.electra"].extend( + [ + "FlaxElectraForCausalLM", + "FlaxElectraForMaskedLM", + "FlaxElectraForMultipleChoice", + "FlaxElectraForPreTraining", + "FlaxElectraForQuestionAnswering", + "FlaxElectraForSequenceClassification", + "FlaxElectraForTokenClassification", + "FlaxElectraModel", + "FlaxElectraPreTrainedModel", + ] + ) + _import_structure["models.encoder_decoder"].append("FlaxEncoderDecoderModel") + _import_structure["models.gpt2"].extend(["FlaxGPT2LMHeadModel", "FlaxGPT2Model", "FlaxGPT2PreTrainedModel"]) + _import_structure["models.gpt_neo"].extend( + ["FlaxGPTNeoForCausalLM", "FlaxGPTNeoModel", "FlaxGPTNeoPreTrainedModel"] + ) + _import_structure["models.gptj"].extend(["FlaxGPTJForCausalLM", "FlaxGPTJModel", "FlaxGPTJPreTrainedModel"]) + _import_structure["models.longt5"].extend( + ["FlaxLongT5ForConditionalGeneration", "FlaxLongT5Model", "FlaxLongT5PreTrainedModel"] + ) + _import_structure["models.marian"].extend( + [ + "FlaxMarianModel", + "FlaxMarianMTModel", + "FlaxMarianPreTrainedModel", + ] + ) + _import_structure["models.mbart"].extend( + [ + "FlaxMBartForConditionalGeneration", + "FlaxMBartForQuestionAnswering", + "FlaxMBartForSequenceClassification", + "FlaxMBartModel", + "FlaxMBartPreTrainedModel", + ] + ) + _import_structure["models.mt5"].extend(["FlaxMT5EncoderModel", "FlaxMT5ForConditionalGeneration", "FlaxMT5Model"]) + _import_structure["models.opt"].extend( + [ + "FlaxOPTForCausalLM", + "FlaxOPTModel", + "FlaxOPTPreTrainedModel", + ] + ) + _import_structure["models.pegasus"].extend( + [ + "FlaxPegasusForConditionalGeneration", + "FlaxPegasusModel", + "FlaxPegasusPreTrainedModel", + ] + ) + _import_structure["models.regnet"].extend( + ["FlaxRegNetForImageClassification", "FlaxRegNetModel", "FlaxRegNetPreTrainedModel"] + ) + _import_structure["models.resnet"].extend( + ["FlaxResNetForImageClassification", "FlaxResNetModel", "FlaxResNetPreTrainedModel"] + ) + _import_structure["models.roberta"].extend( + [ + "FlaxRobertaForCausalLM", + "FlaxRobertaForMaskedLM", + "FlaxRobertaForMultipleChoice", + "FlaxRobertaForQuestionAnswering", + "FlaxRobertaForSequenceClassification", + "FlaxRobertaForTokenClassification", + "FlaxRobertaModel", + "FlaxRobertaPreTrainedModel", + ] + ) + _import_structure["models.roberta_prelayernorm"].extend( + [ + "FlaxRobertaPreLayerNormForCausalLM", + "FlaxRobertaPreLayerNormForMaskedLM", + "FlaxRobertaPreLayerNormForMultipleChoice", + "FlaxRobertaPreLayerNormForQuestionAnswering", + "FlaxRobertaPreLayerNormForSequenceClassification", + "FlaxRobertaPreLayerNormForTokenClassification", + "FlaxRobertaPreLayerNormModel", + "FlaxRobertaPreLayerNormPreTrainedModel", + ] + ) + _import_structure["models.roformer"].extend( + [ + "FlaxRoFormerForMaskedLM", + "FlaxRoFormerForMultipleChoice", + "FlaxRoFormerForQuestionAnswering", + "FlaxRoFormerForSequenceClassification", + "FlaxRoFormerForTokenClassification", + "FlaxRoFormerModel", + "FlaxRoFormerPreTrainedModel", + ] + ) + _import_structure["models.speech_encoder_decoder"].append("FlaxSpeechEncoderDecoderModel") + _import_structure["models.t5"].extend( + ["FlaxT5EncoderModel", "FlaxT5ForConditionalGeneration", "FlaxT5Model", "FlaxT5PreTrainedModel"] + ) + _import_structure["models.vision_encoder_decoder"].append("FlaxVisionEncoderDecoderModel") + _import_structure["models.vision_text_dual_encoder"].extend(["FlaxVisionTextDualEncoderModel"]) + _import_structure["models.vit"].extend(["FlaxViTForImageClassification", "FlaxViTModel", "FlaxViTPreTrainedModel"]) + _import_structure["models.wav2vec2"].extend( + ["FlaxWav2Vec2ForCTC", "FlaxWav2Vec2ForPreTraining", "FlaxWav2Vec2Model", "FlaxWav2Vec2PreTrainedModel"] + ) + _import_structure["models.whisper"].extend( + [ + "FlaxWhisperForConditionalGeneration", + "FlaxWhisperModel", + "FlaxWhisperPreTrainedModel", + "FlaxWhisperForAudioClassification", + ] + ) + _import_structure["models.xglm"].extend( + [ + "FlaxXGLMForCausalLM", + "FlaxXGLMModel", + "FlaxXGLMPreTrainedModel", + ] + ) + _import_structure["models.xlm_roberta"].extend( + [ + "FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST", + "FlaxXLMRobertaForMaskedLM", + "FlaxXLMRobertaForMultipleChoice", + "FlaxXLMRobertaForQuestionAnswering", + "FlaxXLMRobertaForSequenceClassification", + "FlaxXLMRobertaForTokenClassification", + "FlaxXLMRobertaModel", + "FlaxXLMRobertaForCausalLM", + "FlaxXLMRobertaPreTrainedModel", + ] + ) + + +# Direct imports for type-checking +if TYPE_CHECKING: + # Configuration + from .configuration_utils import PretrainedConfig + + # Data + from .data import ( + DataProcessor, + InputExample, + InputFeatures, + SingleSentenceClassificationProcessor, + SquadExample, + SquadFeatures, + SquadV1Processor, + SquadV2Processor, + glue_compute_metrics, + glue_convert_examples_to_features, + glue_output_modes, + glue_processors, + glue_tasks_num_labels, + squad_convert_examples_to_features, + xnli_compute_metrics, + xnli_output_modes, + xnli_processors, + xnli_tasks_num_labels, + ) + from .data.data_collator import ( + DataCollator, + DataCollatorForLanguageModeling, + DataCollatorForPermutationLanguageModeling, + DataCollatorForSeq2Seq, + DataCollatorForSOP, + DataCollatorForTokenClassification, + DataCollatorForWholeWordMask, + DataCollatorWithPadding, + DefaultDataCollator, + default_data_collator, + ) + from .feature_extraction_sequence_utils import SequenceFeatureExtractor + + # Feature Extractor + from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin + + # Generation + from .generation import GenerationConfig, TextIteratorStreamer, TextStreamer + from .hf_argparser import HfArgumentParser + + # Integrations + from .integrations import ( + is_clearml_available, + is_comet_available, + is_neptune_available, + is_optuna_available, + is_ray_available, + is_ray_tune_available, + is_sigopt_available, + is_tensorboard_available, + is_wandb_available, + ) + + # Model Cards + from .modelcard import ModelCard + + # TF 2.0 <=> PyTorch conversion utilities + from .modeling_tf_pytorch_utils import ( + convert_tf_weight_name_to_pt_weight_name, + load_pytorch_checkpoint_in_tf2_model, + load_pytorch_model_in_tf2_model, + load_pytorch_weights_in_tf2_model, + load_tf2_checkpoint_in_pytorch_model, + load_tf2_model_in_pytorch_model, + load_tf2_weights_in_pytorch_model, + ) + from .models.albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig + from .models.align import ( + ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP, + AlignConfig, + AlignProcessor, + AlignTextConfig, + AlignVisionConfig, + ) + from .models.altclip import ( + ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + AltCLIPConfig, + AltCLIPProcessor, + AltCLIPTextConfig, + AltCLIPVisionConfig, + ) + from .models.audio_spectrogram_transformer import ( + AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, + ASTConfig, + ) + from .models.auto import ( + ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, + CONFIG_MAPPING, + FEATURE_EXTRACTOR_MAPPING, + IMAGE_PROCESSOR_MAPPING, + MODEL_NAMES_MAPPING, + PROCESSOR_MAPPING, + TOKENIZER_MAPPING, + AutoConfig, + AutoFeatureExtractor, + AutoImageProcessor, + AutoProcessor, + AutoTokenizer, + ) + from .models.autoformer import ( + AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, + AutoformerConfig, + ) + from .models.bark import ( + BarkCoarseConfig, + BarkConfig, + BarkFineConfig, + BarkProcessor, + BarkSemanticConfig, + ) + from .models.bart import BartConfig, BartTokenizer + from .models.beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig + from .models.bert import ( + BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, + BasicTokenizer, + BertConfig, + BertTokenizer, + WordpieceTokenizer, + ) + from .models.bert_generation import BertGenerationConfig + from .models.bert_japanese import BertJapaneseTokenizer, CharacterTokenizer, MecabTokenizer + from .models.bertweet import BertweetTokenizer + from .models.big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig + from .models.bigbird_pegasus import BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdPegasusConfig + from .models.biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig, BioGptTokenizer + from .models.bit import BIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BitConfig + from .models.blenderbot import BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP, BlenderbotConfig, BlenderbotTokenizer + from .models.blenderbot_small import ( + BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP, + BlenderbotSmallConfig, + BlenderbotSmallTokenizer, + ) + from .models.blip import ( + BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + BlipConfig, + BlipProcessor, + BlipTextConfig, + BlipVisionConfig, + ) + from .models.blip_2 import ( + BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP, + Blip2Config, + Blip2Processor, + Blip2QFormerConfig, + Blip2VisionConfig, + ) + from .models.bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig + from .models.bridgetower import ( + BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP, + BridgeTowerConfig, + BridgeTowerProcessor, + BridgeTowerTextConfig, + BridgeTowerVisionConfig, + ) + from .models.bros import BROS_PRETRAINED_CONFIG_ARCHIVE_MAP, BrosConfig, BrosProcessor + from .models.byt5 import ByT5Tokenizer + from .models.camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig + from .models.canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig, CanineTokenizer + from .models.chinese_clip import ( + CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + ChineseCLIPConfig, + ChineseCLIPProcessor, + ChineseCLIPTextConfig, + ChineseCLIPVisionConfig, + ) + from .models.clap import ( + CLAP_PRETRAINED_MODEL_ARCHIVE_LIST, + ClapAudioConfig, + ClapConfig, + ClapProcessor, + ClapTextConfig, + ) + from .models.clip import ( + CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + CLIPConfig, + CLIPProcessor, + CLIPTextConfig, + CLIPTokenizer, + CLIPVisionConfig, + ) + from .models.clipseg import ( + CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP, + CLIPSegConfig, + CLIPSegProcessor, + CLIPSegTextConfig, + CLIPSegVisionConfig, + ) + from .models.codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenTokenizer + from .models.conditional_detr import CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, ConditionalDetrConfig + from .models.convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertTokenizer + from .models.convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig + from .models.convnextv2 import CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextV2Config + from .models.cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig, CpmAntTokenizer + from .models.ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig, CTRLTokenizer + from .models.cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig + from .models.data2vec import ( + DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, + DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP, + Data2VecAudioConfig, + Data2VecTextConfig, + Data2VecVisionConfig, + ) + from .models.deberta import DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaConfig, DebertaTokenizer + from .models.deberta_v2 import DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaV2Config + from .models.decision_transformer import ( + DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, + DecisionTransformerConfig, + ) + from .models.deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig + from .models.deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig + from .models.deprecated.mctct import ( + MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, + MCTCTConfig, + MCTCTFeatureExtractor, + MCTCTProcessor, + ) + from .models.deprecated.mmbt import MMBTConfig + from .models.deprecated.open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig + from .models.deprecated.retribert import ( + RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, + RetriBertConfig, + RetriBertTokenizer, + ) + from .models.deprecated.tapex import TapexTokenizer + from .models.deprecated.trajectory_transformer import ( + TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, + TrajectoryTransformerConfig, + ) + from .models.deprecated.van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig + from .models.deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig + from .models.detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig + from .models.dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig + from .models.dinov2 import DINOV2_PRETRAINED_CONFIG_ARCHIVE_MAP, Dinov2Config + from .models.distilbert import DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, DistilBertConfig, DistilBertTokenizer + from .models.donut import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutProcessor, DonutSwinConfig + from .models.dpr import ( + DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, + DPRConfig, + DPRContextEncoderTokenizer, + DPRQuestionEncoderTokenizer, + DPRReaderOutput, + DPRReaderTokenizer, + ) + from .models.dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig + from .models.efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig + from .models.efficientnet import EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientNetConfig + from .models.electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraTokenizer + from .models.encodec import ( + ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP, + EncodecConfig, + EncodecFeatureExtractor, + ) + from .models.encoder_decoder import EncoderDecoderConfig + from .models.ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig + from .models.ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig + from .models.esm import ESM_PRETRAINED_CONFIG_ARCHIVE_MAP, EsmConfig, EsmTokenizer + from .models.falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig + from .models.flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertTokenizer + from .models.flava import ( + FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP, + FlavaConfig, + FlavaImageCodebookConfig, + FlavaImageConfig, + FlavaMultimodalConfig, + FlavaTextConfig, + ) + from .models.fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig + from .models.focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig + from .models.fsmt import FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP, FSMTConfig, FSMTTokenizer + from .models.funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig, FunnelTokenizer + from .models.git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitProcessor, GitVisionConfig + from .models.glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig + from .models.gpt2 import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2Config, GPT2Tokenizer + from .models.gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig + from .models.gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig + from .models.gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig + from .models.gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig + from .models.gptj import GPTJ_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTJConfig + from .models.gptsan_japanese import ( + GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, + GPTSanJapaneseConfig, + GPTSanJapaneseTokenizer, + ) + from .models.graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig + from .models.groupvit import ( + GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, + GroupViTConfig, + GroupViTTextConfig, + GroupViTVisionConfig, + ) + from .models.herbert import HerbertTokenizer + from .models.hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig + from .models.ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig + from .models.idefics import ( + IDEFICS_PRETRAINED_CONFIG_ARCHIVE_MAP, + IdeficsConfig, + ) + from .models.imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig + from .models.informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig + from .models.instructblip import ( + INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + InstructBlipConfig, + InstructBlipProcessor, + InstructBlipQFormerConfig, + InstructBlipVisionConfig, + ) + from .models.jukebox import ( + JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP, + JukeboxConfig, + JukeboxPriorConfig, + JukeboxTokenizer, + JukeboxVQVAEConfig, + ) + from .models.layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMTokenizer + from .models.layoutlmv2 import ( + LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, + LayoutLMv2Config, + LayoutLMv2FeatureExtractor, + LayoutLMv2ImageProcessor, + LayoutLMv2Processor, + LayoutLMv2Tokenizer, + ) + from .models.layoutlmv3 import ( + LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP, + LayoutLMv3Config, + LayoutLMv3FeatureExtractor, + LayoutLMv3ImageProcessor, + LayoutLMv3Processor, + LayoutLMv3Tokenizer, + ) + from .models.layoutxlm import LayoutXLMProcessor + from .models.led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig, LEDTokenizer + from .models.levit import LEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, LevitConfig + from .models.lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig + from .models.llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig + from .models.longformer import LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, LongformerConfig, LongformerTokenizer + from .models.longt5 import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongT5Config + from .models.luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig, LukeTokenizer + from .models.lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig, LxmertTokenizer + from .models.m2m_100 import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, M2M100Config + from .models.marian import MarianConfig + from .models.markuplm import ( + MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, + MarkupLMConfig, + MarkupLMFeatureExtractor, + MarkupLMProcessor, + MarkupLMTokenizer, + ) + from .models.mask2former import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, Mask2FormerConfig + from .models.maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig, MaskFormerSwinConfig + from .models.mbart import MBartConfig + from .models.mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig + from .models.megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig + from .models.mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig, MgpstrProcessor, MgpstrTokenizer + from .models.mistral import MISTRAL_PRETRAINED_CONFIG_ARCHIVE_MAP, MistralConfig + from .models.mobilebert import MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileBertConfig, MobileBertTokenizer + from .models.mobilenet_v1 import MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileNetV1Config + from .models.mobilenet_v2 import MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileNetV2Config + from .models.mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig + from .models.mobilevitv2 import MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTV2Config + from .models.mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig, MPNetTokenizer + from .models.mpt import MPT_PRETRAINED_CONFIG_ARCHIVE_MAP, MptConfig + from .models.mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig + from .models.mt5 import MT5Config + from .models.musicgen import ( + MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, + MusicgenConfig, + MusicgenDecoderConfig, + ) + from .models.mvp import MvpConfig, MvpTokenizer + from .models.nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig + from .models.nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig + from .models.nllb_moe import NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP, NllbMoeConfig + from .models.nougat import NougatProcessor + from .models.nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig + from .models.oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig, OneFormerProcessor + from .models.openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig, OpenAIGPTTokenizer + from .models.opt import OPTConfig + from .models.owlvit import ( + OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, + OwlViTConfig, + OwlViTProcessor, + OwlViTTextConfig, + OwlViTVisionConfig, + ) + from .models.pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig, PegasusTokenizer + from .models.pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig + from .models.perceiver import PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP, PerceiverConfig, PerceiverTokenizer + from .models.persimmon import PERSIMMON_PRETRAINED_CONFIG_ARCHIVE_MAP, PersimmonConfig + from .models.phobert import PhobertTokenizer + from .models.pix2struct import ( + PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP, + Pix2StructConfig, + Pix2StructProcessor, + Pix2StructTextConfig, + Pix2StructVisionConfig, + ) + from .models.plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig + from .models.poolformer import POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, PoolFormerConfig + from .models.pop2piano import ( + POP2PIANO_PRETRAINED_CONFIG_ARCHIVE_MAP, + Pop2PianoConfig, + ) + from .models.prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig, ProphetNetTokenizer + from .models.pvt import PVT_PRETRAINED_CONFIG_ARCHIVE_MAP, PvtConfig + from .models.qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig + from .models.rag import RagConfig, RagRetriever, RagTokenizer + from .models.realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig, RealmTokenizer + from .models.reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig + from .models.regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig + from .models.rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig + from .models.resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig + from .models.roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaTokenizer + from .models.roberta_prelayernorm import ( + ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIVE_MAP, + RobertaPreLayerNormConfig, + ) + from .models.roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig, RoCBertTokenizer + from .models.roformer import ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, RoFormerConfig, RoFormerTokenizer + from .models.rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig + from .models.sam import ( + SAM_PRETRAINED_CONFIG_ARCHIVE_MAP, + SamConfig, + SamMaskDecoderConfig, + SamProcessor, + SamPromptEncoderConfig, + SamVisionConfig, + ) + from .models.segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig + from .models.sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig + from .models.sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig + from .models.speech_encoder_decoder import SpeechEncoderDecoderConfig + from .models.speech_to_text import ( + SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, + Speech2TextConfig, + Speech2TextProcessor, + ) + from .models.speech_to_text_2 import ( + SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, + Speech2Text2Config, + Speech2Text2Processor, + Speech2Text2Tokenizer, + ) + from .models.speecht5 import ( + SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP, + SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP, + SpeechT5Config, + SpeechT5FeatureExtractor, + SpeechT5HifiGanConfig, + SpeechT5Processor, + ) + from .models.splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig, SplinterTokenizer + from .models.squeezebert import SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, SqueezeBertConfig, SqueezeBertTokenizer + from .models.swiftformer import SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SwiftFormerConfig + from .models.swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig + from .models.swin2sr import SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAP, Swin2SRConfig + from .models.swinv2 import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, Swinv2Config + from .models.switch_transformers import SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP, SwitchTransformersConfig + from .models.t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config + from .models.table_transformer import TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TableTransformerConfig + from .models.tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig, TapasTokenizer + from .models.time_series_transformer import ( + TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, + TimeSeriesTransformerConfig, + ) + from .models.timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig + from .models.timm_backbone import TimmBackboneConfig + from .models.transfo_xl import ( + TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, + TransfoXLConfig, + TransfoXLCorpus, + TransfoXLTokenizer, + ) + from .models.trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig, TrOCRProcessor + from .models.tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig, TvltFeatureExtractor, TvltProcessor + from .models.umt5 import UMT5Config + from .models.unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig + from .models.unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig + from .models.upernet import UperNetConfig + from .models.videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig + from .models.vilt import ( + VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, + ViltConfig, + ViltFeatureExtractor, + ViltImageProcessor, + ViltProcessor, + ) + from .models.vision_encoder_decoder import VisionEncoderDecoderConfig + from .models.vision_text_dual_encoder import VisionTextDualEncoderConfig, VisionTextDualEncoderProcessor + from .models.visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig + from .models.vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig + from .models.vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig + from .models.vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig + from .models.vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig + from .models.vitdet import VITDET_PRETRAINED_CONFIG_ARCHIVE_MAP, VitDetConfig + from .models.vitmatte import VITMATTE_PRETRAINED_CONFIG_ARCHIVE_MAP, VitMatteConfig + from .models.vits import ( + VITS_PRETRAINED_CONFIG_ARCHIVE_MAP, + VitsConfig, + VitsTokenizer, + ) + from .models.vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig + from .models.wav2vec2 import ( + WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, + Wav2Vec2Config, + Wav2Vec2CTCTokenizer, + Wav2Vec2FeatureExtractor, + Wav2Vec2Processor, + Wav2Vec2Tokenizer, + ) + from .models.wav2vec2_conformer import WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, Wav2Vec2ConformerConfig + from .models.wav2vec2_phoneme import Wav2Vec2PhonemeCTCTokenizer + from .models.wav2vec2_with_lm import Wav2Vec2ProcessorWithLM + from .models.wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig + from .models.whisper import ( + WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, + WhisperConfig, + WhisperFeatureExtractor, + WhisperProcessor, + WhisperTokenizer, + ) + from .models.x_clip import ( + XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, + XCLIPConfig, + XCLIPProcessor, + XCLIPTextConfig, + XCLIPVisionConfig, + ) + from .models.xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig + from .models.xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig, XLMTokenizer + from .models.xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig + from .models.xlm_roberta import XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMRobertaConfig + from .models.xlm_roberta_xl import XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMRobertaXLConfig + from .models.xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig + from .models.xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig + from .models.yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig + from .models.yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig + + # Pipelines + from .pipelines import ( + AudioClassificationPipeline, + AutomaticSpeechRecognitionPipeline, + Conversation, + ConversationalPipeline, + CsvPipelineDataFormat, + DepthEstimationPipeline, + DocumentQuestionAnsweringPipeline, + FeatureExtractionPipeline, + FillMaskPipeline, + ImageClassificationPipeline, + ImageSegmentationPipeline, + ImageToImagePipeline, + ImageToTextPipeline, + JsonPipelineDataFormat, + NerPipeline, + ObjectDetectionPipeline, + PipedPipelineDataFormat, + Pipeline, + PipelineDataFormat, + QuestionAnsweringPipeline, + SummarizationPipeline, + TableQuestionAnsweringPipeline, + Text2TextGenerationPipeline, + TextClassificationPipeline, + TextGenerationPipeline, + TextToAudioPipeline, + TokenClassificationPipeline, + TranslationPipeline, + VideoClassificationPipeline, + VisualQuestionAnsweringPipeline, + ZeroShotAudioClassificationPipeline, + ZeroShotClassificationPipeline, + ZeroShotImageClassificationPipeline, + ZeroShotObjectDetectionPipeline, + pipeline, + ) + from .processing_utils import ProcessorMixin + + # Tokenization + from .tokenization_utils import PreTrainedTokenizer + from .tokenization_utils_base import ( + AddedToken, + BatchEncoding, + CharSpan, + PreTrainedTokenizerBase, + SpecialTokensMixin, + TokenSpan, + ) + + # Tools + from .tools import ( + Agent, + AzureOpenAiAgent, + HfAgent, + LocalAgent, + OpenAiAgent, + PipelineTool, + RemoteTool, + Tool, + launch_gradio_demo, + load_tool, + ) + + # Trainer + from .trainer_callback import ( + DefaultFlowCallback, + EarlyStoppingCallback, + PrinterCallback, + ProgressCallback, + TrainerCallback, + TrainerControl, + TrainerState, + ) + from .trainer_utils import EvalPrediction, IntervalStrategy, SchedulerType, enable_full_determinism, set_seed + from .training_args import TrainingArguments + from .training_args_seq2seq import Seq2SeqTrainingArguments + from .training_args_tf import TFTrainingArguments + + # Files and general utilities + from .utils import ( + CONFIG_NAME, + MODEL_CARD_NAME, + PYTORCH_PRETRAINED_BERT_CACHE, + PYTORCH_TRANSFORMERS_CACHE, + SPIECE_UNDERLINE, + TF2_WEIGHTS_NAME, + TF_WEIGHTS_NAME, + TRANSFORMERS_CACHE, + WEIGHTS_NAME, + TensorType, + add_end_docstrings, + add_start_docstrings, + is_apex_available, + is_bitsandbytes_available, + is_datasets_available, + is_decord_available, + is_faiss_available, + is_flax_available, + is_keras_nlp_available, + is_phonemizer_available, + is_psutil_available, + is_py3nvml_available, + is_pyctcdecode_available, + is_safetensors_available, + is_scipy_available, + is_sentencepiece_available, + is_sklearn_available, + is_speech_available, + is_tensorflow_text_available, + is_tf_available, + is_timm_available, + is_tokenizers_available, + is_torch_available, + is_torch_neuroncore_available, + is_torch_npu_available, + is_torch_tpu_available, + is_torch_xpu_available, + is_torchvision_available, + is_vision_available, + logging, + ) + + # bitsandbytes config + from .utils.quantization_config import BitsAndBytesConfig, GPTQConfig + + try: + if not is_sentencepiece_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_sentencepiece_objects import * + else: + from .models.albert import AlbertTokenizer + from .models.barthez import BarthezTokenizer + from .models.bartpho import BartphoTokenizer + from .models.bert_generation import BertGenerationTokenizer + from .models.big_bird import BigBirdTokenizer + from .models.camembert import CamembertTokenizer + from .models.code_llama import CodeLlamaTokenizer + from .models.cpm import CpmTokenizer + from .models.deberta_v2 import DebertaV2Tokenizer + from .models.ernie_m import ErnieMTokenizer + from .models.fnet import FNetTokenizer + from .models.gpt_sw3 import GPTSw3Tokenizer + from .models.layoutxlm import LayoutXLMTokenizer + from .models.llama import LlamaTokenizer + from .models.m2m_100 import M2M100Tokenizer + from .models.marian import MarianTokenizer + from .models.mbart import MBart50Tokenizer, MBartTokenizer + from .models.mluke import MLukeTokenizer + from .models.mt5 import MT5Tokenizer + from .models.nllb import NllbTokenizer + from .models.pegasus import PegasusTokenizer + from .models.plbart import PLBartTokenizer + from .models.reformer import ReformerTokenizer + from .models.rembert import RemBertTokenizer + from .models.speech_to_text import Speech2TextTokenizer + from .models.speecht5 import SpeechT5Tokenizer + from .models.t5 import T5Tokenizer + from .models.xglm import XGLMTokenizer + from .models.xlm_prophetnet import XLMProphetNetTokenizer + from .models.xlm_roberta import XLMRobertaTokenizer + from .models.xlnet import XLNetTokenizer + + try: + if not is_tokenizers_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_tokenizers_objects import * + else: + # Fast tokenizers imports + from .models.albert import AlbertTokenizerFast + from .models.bart import BartTokenizerFast + from .models.barthez import BarthezTokenizerFast + from .models.bert import BertTokenizerFast + from .models.big_bird import BigBirdTokenizerFast + from .models.blenderbot import BlenderbotTokenizerFast + from .models.blenderbot_small import BlenderbotSmallTokenizerFast + from .models.bloom import BloomTokenizerFast + from .models.camembert import CamembertTokenizerFast + from .models.clip import CLIPTokenizerFast + from .models.code_llama import CodeLlamaTokenizerFast + from .models.codegen import CodeGenTokenizerFast + from .models.convbert import ConvBertTokenizerFast + from .models.cpm import CpmTokenizerFast + from .models.deberta import DebertaTokenizerFast + from .models.deberta_v2 import DebertaV2TokenizerFast + from .models.deprecated.retribert import RetriBertTokenizerFast + from .models.distilbert import DistilBertTokenizerFast + from .models.dpr import DPRContextEncoderTokenizerFast, DPRQuestionEncoderTokenizerFast, DPRReaderTokenizerFast + from .models.electra import ElectraTokenizerFast + from .models.fnet import FNetTokenizerFast + from .models.funnel import FunnelTokenizerFast + from .models.gpt2 import GPT2TokenizerFast + from .models.gpt_neox import GPTNeoXTokenizerFast + from .models.gpt_neox_japanese import GPTNeoXJapaneseTokenizer + from .models.herbert import HerbertTokenizerFast + from .models.layoutlm import LayoutLMTokenizerFast + from .models.layoutlmv2 import LayoutLMv2TokenizerFast + from .models.layoutlmv3 import LayoutLMv3TokenizerFast + from .models.layoutxlm import LayoutXLMTokenizerFast + from .models.led import LEDTokenizerFast + from .models.llama import LlamaTokenizerFast + from .models.longformer import LongformerTokenizerFast + from .models.lxmert import LxmertTokenizerFast + from .models.markuplm import MarkupLMTokenizerFast + from .models.mbart import MBartTokenizerFast + from .models.mbart50 import MBart50TokenizerFast + from .models.mobilebert import MobileBertTokenizerFast + from .models.mpnet import MPNetTokenizerFast + from .models.mt5 import MT5TokenizerFast + from .models.mvp import MvpTokenizerFast + from .models.nllb import NllbTokenizerFast + from .models.nougat import NougatTokenizerFast + from .models.openai import OpenAIGPTTokenizerFast + from .models.pegasus import PegasusTokenizerFast + from .models.realm import RealmTokenizerFast + from .models.reformer import ReformerTokenizerFast + from .models.rembert import RemBertTokenizerFast + from .models.roberta import RobertaTokenizerFast + from .models.roformer import RoFormerTokenizerFast + from .models.splinter import SplinterTokenizerFast + from .models.squeezebert import SqueezeBertTokenizerFast + from .models.t5 import T5TokenizerFast + from .models.whisper import WhisperTokenizerFast + from .models.xglm import XGLMTokenizerFast + from .models.xlm_roberta import XLMRobertaTokenizerFast + from .models.xlnet import XLNetTokenizerFast + from .tokenization_utils_fast import PreTrainedTokenizerFast + + try: + if not (is_sentencepiece_available() and is_tokenizers_available()): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummies_sentencepiece_and_tokenizers_objects import * + else: + from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS, convert_slow_tokenizer + + try: + if not is_speech_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_speech_objects import * + else: + from .models.audio_spectrogram_transformer import ASTFeatureExtractor + from .models.speech_to_text import Speech2TextFeatureExtractor + + try: + if not is_tensorflow_text_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_tensorflow_text_objects import * + else: + from .models.bert import TFBertTokenizer + + try: + if not is_keras_nlp_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_keras_nlp_objects import * + else: + from .models.gpt2 import TFGPT2Tokenizer + + try: + if not is_vision_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_vision_objects import * + else: + from .image_processing_utils import ImageProcessingMixin + from .image_utils import ImageFeatureExtractionMixin + from .models.beit import BeitFeatureExtractor, BeitImageProcessor + from .models.bit import BitImageProcessor + from .models.blip import BlipImageProcessor + from .models.bridgetower import BridgeTowerImageProcessor + from .models.chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor + from .models.clip import CLIPFeatureExtractor, CLIPImageProcessor + from .models.conditional_detr import ConditionalDetrFeatureExtractor, ConditionalDetrImageProcessor + from .models.convnext import ConvNextFeatureExtractor, ConvNextImageProcessor + from .models.deformable_detr import DeformableDetrFeatureExtractor, DeformableDetrImageProcessor + from .models.deit import DeiTFeatureExtractor, DeiTImageProcessor + from .models.deta import DetaImageProcessor + from .models.detr import DetrFeatureExtractor, DetrImageProcessor + from .models.donut import DonutFeatureExtractor, DonutImageProcessor + from .models.dpt import DPTFeatureExtractor, DPTImageProcessor + from .models.efficientformer import EfficientFormerImageProcessor + from .models.efficientnet import EfficientNetImageProcessor + from .models.flava import FlavaFeatureExtractor, FlavaImageProcessor, FlavaProcessor + from .models.glpn import GLPNFeatureExtractor, GLPNImageProcessor + from .models.idefics import IdeficsImageProcessor + from .models.imagegpt import ImageGPTFeatureExtractor, ImageGPTImageProcessor + from .models.layoutlmv2 import LayoutLMv2FeatureExtractor, LayoutLMv2ImageProcessor + from .models.layoutlmv3 import LayoutLMv3FeatureExtractor, LayoutLMv3ImageProcessor + from .models.levit import LevitFeatureExtractor, LevitImageProcessor + from .models.mask2former import Mask2FormerImageProcessor + from .models.maskformer import MaskFormerFeatureExtractor, MaskFormerImageProcessor + from .models.mobilenet_v1 import MobileNetV1FeatureExtractor, MobileNetV1ImageProcessor + from .models.mobilenet_v2 import MobileNetV2FeatureExtractor, MobileNetV2ImageProcessor + from .models.mobilevit import MobileViTFeatureExtractor, MobileViTImageProcessor + from .models.nougat import NougatImageProcessor + from .models.oneformer import OneFormerImageProcessor + from .models.owlvit import OwlViTFeatureExtractor, OwlViTImageProcessor + from .models.perceiver import PerceiverFeatureExtractor, PerceiverImageProcessor + from .models.pix2struct import Pix2StructImageProcessor + from .models.poolformer import PoolFormerFeatureExtractor, PoolFormerImageProcessor + from .models.pvt import PvtImageProcessor + from .models.sam import SamImageProcessor + from .models.segformer import SegformerFeatureExtractor, SegformerImageProcessor + from .models.swin2sr import Swin2SRImageProcessor + from .models.tvlt import TvltImageProcessor + from .models.videomae import VideoMAEFeatureExtractor, VideoMAEImageProcessor + from .models.vilt import ViltFeatureExtractor, ViltImageProcessor, ViltProcessor + from .models.vit import ViTFeatureExtractor, ViTImageProcessor + from .models.vit_hybrid import ViTHybridImageProcessor + from .models.vitmatte import VitMatteImageProcessor + from .models.vivit import VivitImageProcessor + from .models.yolos import YolosFeatureExtractor, YolosImageProcessor + + # Modeling + try: + if not is_torch_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_pt_objects import * + else: + # Benchmarks + from .benchmark.benchmark import PyTorchBenchmark + from .benchmark.benchmark_args import PyTorchBenchmarkArguments + from .data.datasets import ( + GlueDataset, + GlueDataTrainingArguments, + LineByLineTextDataset, + LineByLineWithRefDataset, + LineByLineWithSOPTextDataset, + SquadDataset, + SquadDataTrainingArguments, + TextDataset, + TextDatasetForNextSentencePrediction, + ) + from .generation import ( + AlternatingCodebooksLogitsProcessor, + BeamScorer, + BeamSearchScorer, + ClassifierFreeGuidanceLogitsProcessor, + ConstrainedBeamSearchScorer, + Constraint, + ConstraintListState, + DisjunctiveConstraint, + EncoderNoRepeatNGramLogitsProcessor, + EncoderRepetitionPenaltyLogitsProcessor, + EpsilonLogitsWarper, + EtaLogitsWarper, + ExponentialDecayLengthPenalty, + ForcedBOSTokenLogitsProcessor, + ForcedEOSTokenLogitsProcessor, + ForceTokensLogitsProcessor, + GenerationMixin, + HammingDiversityLogitsProcessor, + InfNanRemoveLogitsProcessor, + LogitNormalization, + LogitsProcessor, + LogitsProcessorList, + LogitsWarper, + MaxLengthCriteria, + MaxTimeCriteria, + MinLengthLogitsProcessor, + MinNewTokensLengthLogitsProcessor, + NoBadWordsLogitsProcessor, + NoRepeatNGramLogitsProcessor, + PhrasalConstraint, + PrefixConstrainedLogitsProcessor, + RepetitionPenaltyLogitsProcessor, + SequenceBiasLogitsProcessor, + StoppingCriteria, + StoppingCriteriaList, + SuppressTokensAtBeginLogitsProcessor, + SuppressTokensLogitsProcessor, + TemperatureLogitsWarper, + TopKLogitsWarper, + TopPLogitsWarper, + TypicalLogitsWarper, + UnbatchedClassifierFreeGuidanceLogitsProcessor, + WhisperTimeStampLogitsProcessor, + top_k_top_p_filtering, + ) + from .modeling_utils import PreTrainedModel + + # PyTorch model imports + from .models.albert import ( + ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + AlbertForMaskedLM, + AlbertForMultipleChoice, + AlbertForPreTraining, + AlbertForQuestionAnswering, + AlbertForSequenceClassification, + AlbertForTokenClassification, + AlbertModel, + AlbertPreTrainedModel, + load_tf_weights_in_albert, + ) + from .models.align import ( + ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST, + AlignModel, + AlignPreTrainedModel, + AlignTextModel, + AlignVisionModel, + ) + from .models.altclip import ( + ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + AltCLIPModel, + AltCLIPPreTrainedModel, + AltCLIPTextModel, + AltCLIPVisionModel, + ) + from .models.audio_spectrogram_transformer import ( + AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + ASTForAudioClassification, + ASTModel, + ASTPreTrainedModel, + ) + from .models.auto import ( + MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, + MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING, + MODEL_FOR_AUDIO_XVECTOR_MAPPING, + MODEL_FOR_BACKBONE_MAPPING, + MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING, + MODEL_FOR_CAUSAL_LM_MAPPING, + MODEL_FOR_CTC_MAPPING, + MODEL_FOR_DEPTH_ESTIMATION_MAPPING, + MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, + MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING, + MODEL_FOR_IMAGE_SEGMENTATION_MAPPING, + MODEL_FOR_IMAGE_TO_IMAGE_MAPPING, + MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING, + MODEL_FOR_MASK_GENERATION_MAPPING, + MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING, + MODEL_FOR_MASKED_LM_MAPPING, + MODEL_FOR_MULTIPLE_CHOICE_MAPPING, + MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING, + MODEL_FOR_OBJECT_DETECTION_MAPPING, + MODEL_FOR_PRETRAINING_MAPPING, + MODEL_FOR_QUESTION_ANSWERING_MAPPING, + MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING, + MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, + MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, + MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, + MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING, + MODEL_FOR_TEXT_ENCODING_MAPPING, + MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING, + MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING, + MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, + MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING, + MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, + MODEL_FOR_VISION_2_SEQ_MAPPING, + MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, + MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING, + MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, + MODEL_MAPPING, + MODEL_WITH_LM_HEAD_MAPPING, + AutoBackbone, + AutoModel, + AutoModelForAudioClassification, + AutoModelForAudioFrameClassification, + AutoModelForAudioXVector, + AutoModelForCausalLM, + AutoModelForCTC, + AutoModelForDepthEstimation, + AutoModelForDocumentQuestionAnswering, + AutoModelForImageClassification, + AutoModelForImageSegmentation, + AutoModelForImageToImage, + AutoModelForInstanceSegmentation, + AutoModelForMaskedImageModeling, + AutoModelForMaskedLM, + AutoModelForMaskGeneration, + AutoModelForMultipleChoice, + AutoModelForNextSentencePrediction, + AutoModelForObjectDetection, + AutoModelForPreTraining, + AutoModelForQuestionAnswering, + AutoModelForSemanticSegmentation, + AutoModelForSeq2SeqLM, + AutoModelForSequenceClassification, + AutoModelForSpeechSeq2Seq, + AutoModelForTableQuestionAnswering, + AutoModelForTextEncoding, + AutoModelForTextToSpectrogram, + AutoModelForTextToWaveform, + AutoModelForTokenClassification, + AutoModelForUniversalSegmentation, + AutoModelForVideoClassification, + AutoModelForVision2Seq, + AutoModelForVisualQuestionAnswering, + AutoModelForZeroShotImageClassification, + AutoModelForZeroShotObjectDetection, + AutoModelWithLMHead, + ) + from .models.autoformer import ( + AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + AutoformerForPrediction, + AutoformerModel, + AutoformerPreTrainedModel, + ) + from .models.bark import ( + BARK_PRETRAINED_MODEL_ARCHIVE_LIST, + BarkCausalModel, + BarkCoarseModel, + BarkFineModel, + BarkModel, + BarkPreTrainedModel, + BarkSemanticModel, + ) + from .models.bart import ( + BART_PRETRAINED_MODEL_ARCHIVE_LIST, + BartForCausalLM, + BartForConditionalGeneration, + BartForQuestionAnswering, + BartForSequenceClassification, + BartModel, + BartPreTrainedModel, + BartPretrainedModel, + PretrainedBartModel, + ) + from .models.beit import ( + BEIT_PRETRAINED_MODEL_ARCHIVE_LIST, + BeitForImageClassification, + BeitForMaskedImageModeling, + BeitForSemanticSegmentation, + BeitModel, + BeitPreTrainedModel, + ) + from .models.bert import ( + BERT_PRETRAINED_MODEL_ARCHIVE_LIST, + BertForMaskedLM, + BertForMultipleChoice, + BertForNextSentencePrediction, + BertForPreTraining, + BertForQuestionAnswering, + BertForSequenceClassification, + BertForTokenClassification, + BertLayer, + BertLMHeadModel, + BertModel, + BertPreTrainedModel, + load_tf_weights_in_bert, + ) + from .models.bert_generation import ( + BertGenerationDecoder, + BertGenerationEncoder, + BertGenerationPreTrainedModel, + load_tf_weights_in_bert_generation, + ) + from .models.big_bird import ( + BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST, + BigBirdForCausalLM, + BigBirdForMaskedLM, + BigBirdForMultipleChoice, + BigBirdForPreTraining, + BigBirdForQuestionAnswering, + BigBirdForSequenceClassification, + BigBirdForTokenClassification, + BigBirdLayer, + BigBirdModel, + BigBirdPreTrainedModel, + load_tf_weights_in_big_bird, + ) + from .models.bigbird_pegasus import ( + BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST, + BigBirdPegasusForCausalLM, + BigBirdPegasusForConditionalGeneration, + BigBirdPegasusForQuestionAnswering, + BigBirdPegasusForSequenceClassification, + BigBirdPegasusModel, + BigBirdPegasusPreTrainedModel, + ) + from .models.biogpt import ( + BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST, + BioGptForCausalLM, + BioGptForSequenceClassification, + BioGptForTokenClassification, + BioGptModel, + BioGptPreTrainedModel, + ) + from .models.bit import ( + BIT_PRETRAINED_MODEL_ARCHIVE_LIST, + BitBackbone, + BitForImageClassification, + BitModel, + BitPreTrainedModel, + ) + from .models.blenderbot import ( + BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST, + BlenderbotForCausalLM, + BlenderbotForConditionalGeneration, + BlenderbotModel, + BlenderbotPreTrainedModel, + ) + from .models.blenderbot_small import ( + BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST, + BlenderbotSmallForCausalLM, + BlenderbotSmallForConditionalGeneration, + BlenderbotSmallModel, + BlenderbotSmallPreTrainedModel, + ) + from .models.blip import ( + BLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + BlipForConditionalGeneration, + BlipForImageTextRetrieval, + BlipForQuestionAnswering, + BlipModel, + BlipPreTrainedModel, + BlipTextModel, + BlipVisionModel, + ) + from .models.blip_2 import ( + BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST, + Blip2ForConditionalGeneration, + Blip2Model, + Blip2PreTrainedModel, + Blip2QFormerModel, + Blip2VisionModel, + ) + from .models.bloom import ( + BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST, + BloomForCausalLM, + BloomForQuestionAnswering, + BloomForSequenceClassification, + BloomForTokenClassification, + BloomModel, + BloomPreTrainedModel, + ) + from .models.bridgetower import ( + BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST, + BridgeTowerForContrastiveLearning, + BridgeTowerForImageAndTextRetrieval, + BridgeTowerForMaskedLM, + BridgeTowerModel, + BridgeTowerPreTrainedModel, + ) + from .models.bros import ( + BROS_PRETRAINED_MODEL_ARCHIVE_LIST, + BrosForTokenClassification, + BrosModel, + BrosPreTrainedModel, + BrosProcessor, + BrosSpadeEEForTokenClassification, + BrosSpadeELForTokenClassification, + ) + from .models.camembert import ( + CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + CamembertForCausalLM, + CamembertForMaskedLM, + CamembertForMultipleChoice, + CamembertForQuestionAnswering, + CamembertForSequenceClassification, + CamembertForTokenClassification, + CamembertModel, + CamembertPreTrainedModel, + ) + from .models.canine import ( + CANINE_PRETRAINED_MODEL_ARCHIVE_LIST, + CanineForMultipleChoice, + CanineForQuestionAnswering, + CanineForSequenceClassification, + CanineForTokenClassification, + CanineLayer, + CanineModel, + CaninePreTrainedModel, + load_tf_weights_in_canine, + ) + from .models.chinese_clip import ( + CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + ChineseCLIPModel, + ChineseCLIPPreTrainedModel, + ChineseCLIPTextModel, + ChineseCLIPVisionModel, + ) + from .models.clap import ( + CLAP_PRETRAINED_MODEL_ARCHIVE_LIST, + ClapAudioModel, + ClapAudioModelWithProjection, + ClapFeatureExtractor, + ClapModel, + ClapPreTrainedModel, + ClapTextModel, + ClapTextModelWithProjection, + ) + from .models.clip import ( + CLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + CLIPModel, + CLIPPreTrainedModel, + CLIPTextModel, + CLIPTextModelWithProjection, + CLIPVisionModel, + CLIPVisionModelWithProjection, + ) + from .models.clipseg import ( + CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST, + CLIPSegForImageSegmentation, + CLIPSegModel, + CLIPSegPreTrainedModel, + CLIPSegTextModel, + CLIPSegVisionModel, + ) + from .models.codegen import ( + CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST, + CodeGenForCausalLM, + CodeGenModel, + CodeGenPreTrainedModel, + ) + from .models.conditional_detr import ( + CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST, + ConditionalDetrForObjectDetection, + ConditionalDetrForSegmentation, + ConditionalDetrModel, + ConditionalDetrPreTrainedModel, + ) + from .models.convbert import ( + CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + ConvBertForMaskedLM, + ConvBertForMultipleChoice, + ConvBertForQuestionAnswering, + ConvBertForSequenceClassification, + ConvBertForTokenClassification, + ConvBertLayer, + ConvBertModel, + ConvBertPreTrainedModel, + load_tf_weights_in_convbert, + ) + from .models.convnext import ( + CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST, + ConvNextBackbone, + ConvNextForImageClassification, + ConvNextModel, + ConvNextPreTrainedModel, + ) + from .models.convnextv2 import ( + CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST, + ConvNextV2Backbone, + ConvNextV2ForImageClassification, + ConvNextV2Model, + ConvNextV2PreTrainedModel, + ) + from .models.cpmant import ( + CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST, + CpmAntForCausalLM, + CpmAntModel, + CpmAntPreTrainedModel, + ) + from .models.ctrl import ( + CTRL_PRETRAINED_MODEL_ARCHIVE_LIST, + CTRLForSequenceClassification, + CTRLLMHeadModel, + CTRLModel, + CTRLPreTrainedModel, + ) + from .models.cvt import ( + CVT_PRETRAINED_MODEL_ARCHIVE_LIST, + CvtForImageClassification, + CvtModel, + CvtPreTrainedModel, + ) + from .models.data2vec import ( + DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST, + DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST, + DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST, + Data2VecAudioForAudioFrameClassification, + Data2VecAudioForCTC, + Data2VecAudioForSequenceClassification, + Data2VecAudioForXVector, + Data2VecAudioModel, + Data2VecAudioPreTrainedModel, + Data2VecTextForCausalLM, + Data2VecTextForMaskedLM, + Data2VecTextForMultipleChoice, + Data2VecTextForQuestionAnswering, + Data2VecTextForSequenceClassification, + Data2VecTextForTokenClassification, + Data2VecTextModel, + Data2VecTextPreTrainedModel, + Data2VecVisionForImageClassification, + Data2VecVisionForSemanticSegmentation, + Data2VecVisionModel, + Data2VecVisionPreTrainedModel, + ) + from .models.deberta import ( + DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + DebertaForMaskedLM, + DebertaForQuestionAnswering, + DebertaForSequenceClassification, + DebertaForTokenClassification, + DebertaModel, + DebertaPreTrainedModel, + ) + from .models.deberta_v2 import ( + DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST, + DebertaV2ForMaskedLM, + DebertaV2ForMultipleChoice, + DebertaV2ForQuestionAnswering, + DebertaV2ForSequenceClassification, + DebertaV2ForTokenClassification, + DebertaV2Model, + DebertaV2PreTrainedModel, + ) + from .models.decision_transformer import ( + DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + DecisionTransformerGPT2Model, + DecisionTransformerGPT2PreTrainedModel, + DecisionTransformerModel, + DecisionTransformerPreTrainedModel, + ) + from .models.deformable_detr import ( + DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST, + DeformableDetrForObjectDetection, + DeformableDetrModel, + DeformableDetrPreTrainedModel, + ) + from .models.deit import ( + DEIT_PRETRAINED_MODEL_ARCHIVE_LIST, + DeiTForImageClassification, + DeiTForImageClassificationWithTeacher, + DeiTForMaskedImageModeling, + DeiTModel, + DeiTPreTrainedModel, + ) + from .models.deprecated.mctct import ( + MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, + MCTCTForCTC, + MCTCTModel, + MCTCTPreTrainedModel, + ) + from .models.deprecated.mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings + from .models.deprecated.open_llama import ( + OpenLlamaForCausalLM, + OpenLlamaForSequenceClassification, + OpenLlamaModel, + OpenLlamaPreTrainedModel, + ) + from .models.deprecated.retribert import ( + RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + RetriBertModel, + RetriBertPreTrainedModel, + ) + from .models.deprecated.trajectory_transformer import ( + TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TrajectoryTransformerModel, + TrajectoryTransformerPreTrainedModel, + ) + from .models.deprecated.van import ( + VAN_PRETRAINED_MODEL_ARCHIVE_LIST, + VanForImageClassification, + VanModel, + VanPreTrainedModel, + ) + from .models.deta import ( + DETA_PRETRAINED_MODEL_ARCHIVE_LIST, + DetaForObjectDetection, + DetaModel, + DetaPreTrainedModel, + ) + from .models.detr import ( + DETR_PRETRAINED_MODEL_ARCHIVE_LIST, + DetrForObjectDetection, + DetrForSegmentation, + DetrModel, + DetrPreTrainedModel, + ) + from .models.dinat import ( + DINAT_PRETRAINED_MODEL_ARCHIVE_LIST, + DinatBackbone, + DinatForImageClassification, + DinatModel, + DinatPreTrainedModel, + ) + from .models.dinov2 import ( + DINOV2_PRETRAINED_MODEL_ARCHIVE_LIST, + Dinov2Backbone, + Dinov2ForImageClassification, + Dinov2Model, + Dinov2PreTrainedModel, + ) + from .models.distilbert import ( + DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + DistilBertForMaskedLM, + DistilBertForMultipleChoice, + DistilBertForQuestionAnswering, + DistilBertForSequenceClassification, + DistilBertForTokenClassification, + DistilBertModel, + DistilBertPreTrainedModel, + ) + from .models.donut import DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST, DonutSwinModel, DonutSwinPreTrainedModel + from .models.dpr import ( + DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST, + DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST, + DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST, + DPRContextEncoder, + DPRPretrainedContextEncoder, + DPRPreTrainedModel, + DPRPretrainedQuestionEncoder, + DPRPretrainedReader, + DPRQuestionEncoder, + DPRReader, + ) + from .models.dpt import ( + DPT_PRETRAINED_MODEL_ARCHIVE_LIST, + DPTForDepthEstimation, + DPTForSemanticSegmentation, + DPTModel, + DPTPreTrainedModel, + ) + from .models.efficientformer import ( + EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + EfficientFormerForImageClassification, + EfficientFormerForImageClassificationWithTeacher, + EfficientFormerModel, + EfficientFormerPreTrainedModel, + ) + from .models.efficientnet import ( + EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST, + EfficientNetForImageClassification, + EfficientNetModel, + EfficientNetPreTrainedModel, + ) + from .models.electra import ( + ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST, + ElectraForCausalLM, + ElectraForMaskedLM, + ElectraForMultipleChoice, + ElectraForPreTraining, + ElectraForQuestionAnswering, + ElectraForSequenceClassification, + ElectraForTokenClassification, + ElectraModel, + ElectraPreTrainedModel, + load_tf_weights_in_electra, + ) + from .models.encodec import ( + ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST, + EncodecModel, + EncodecPreTrainedModel, + ) + from .models.encoder_decoder import EncoderDecoderModel + from .models.ernie import ( + ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST, + ErnieForCausalLM, + ErnieForMaskedLM, + ErnieForMultipleChoice, + ErnieForNextSentencePrediction, + ErnieForPreTraining, + ErnieForQuestionAnswering, + ErnieForSequenceClassification, + ErnieForTokenClassification, + ErnieModel, + ErniePreTrainedModel, + ) + from .models.ernie_m import ( + ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST, + ErnieMForInformationExtraction, + ErnieMForMultipleChoice, + ErnieMForQuestionAnswering, + ErnieMForSequenceClassification, + ErnieMForTokenClassification, + ErnieMModel, + ErnieMPreTrainedModel, + ) + from .models.esm import ( + ESM_PRETRAINED_MODEL_ARCHIVE_LIST, + EsmFoldPreTrainedModel, + EsmForMaskedLM, + EsmForProteinFolding, + EsmForSequenceClassification, + EsmForTokenClassification, + EsmModel, + EsmPreTrainedModel, + ) + from .models.falcon import ( + FALCON_PRETRAINED_MODEL_ARCHIVE_LIST, + FalconForCausalLM, + FalconForQuestionAnswering, + FalconForSequenceClassification, + FalconForTokenClassification, + FalconModel, + FalconPreTrainedModel, + ) + from .models.flaubert import ( + FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + FlaubertForMultipleChoice, + FlaubertForQuestionAnswering, + FlaubertForQuestionAnsweringSimple, + FlaubertForSequenceClassification, + FlaubertForTokenClassification, + FlaubertModel, + FlaubertPreTrainedModel, + FlaubertWithLMHeadModel, + ) + from .models.flava import ( + FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST, + FlavaForPreTraining, + FlavaImageCodebook, + FlavaImageModel, + FlavaModel, + FlavaMultimodalModel, + FlavaPreTrainedModel, + FlavaTextModel, + ) + from .models.fnet import ( + FNET_PRETRAINED_MODEL_ARCHIVE_LIST, + FNetForMaskedLM, + FNetForMultipleChoice, + FNetForNextSentencePrediction, + FNetForPreTraining, + FNetForQuestionAnswering, + FNetForSequenceClassification, + FNetForTokenClassification, + FNetLayer, + FNetModel, + FNetPreTrainedModel, + ) + from .models.focalnet import ( + FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST, + FocalNetBackbone, + FocalNetForImageClassification, + FocalNetForMaskedImageModeling, + FocalNetModel, + FocalNetPreTrainedModel, + ) + from .models.fsmt import FSMTForConditionalGeneration, FSMTModel, PretrainedFSMTModel + from .models.funnel import ( + FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST, + FunnelBaseModel, + FunnelForMaskedLM, + FunnelForMultipleChoice, + FunnelForPreTraining, + FunnelForQuestionAnswering, + FunnelForSequenceClassification, + FunnelForTokenClassification, + FunnelModel, + FunnelPreTrainedModel, + load_tf_weights_in_funnel, + ) + from .models.git import ( + GIT_PRETRAINED_MODEL_ARCHIVE_LIST, + GitForCausalLM, + GitModel, + GitPreTrainedModel, + GitVisionModel, + ) + from .models.glpn import ( + GLPN_PRETRAINED_MODEL_ARCHIVE_LIST, + GLPNForDepthEstimation, + GLPNModel, + GLPNPreTrainedModel, + ) + from .models.gpt2 import ( + GPT2_PRETRAINED_MODEL_ARCHIVE_LIST, + GPT2DoubleHeadsModel, + GPT2ForQuestionAnswering, + GPT2ForSequenceClassification, + GPT2ForTokenClassification, + GPT2LMHeadModel, + GPT2Model, + GPT2PreTrainedModel, + load_tf_weights_in_gpt2, + ) + from .models.gpt_bigcode import ( + GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTBigCodeForCausalLM, + GPTBigCodeForSequenceClassification, + GPTBigCodeForTokenClassification, + GPTBigCodeModel, + GPTBigCodePreTrainedModel, + ) + from .models.gpt_neo import ( + GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTNeoForCausalLM, + GPTNeoForQuestionAnswering, + GPTNeoForSequenceClassification, + GPTNeoForTokenClassification, + GPTNeoModel, + GPTNeoPreTrainedModel, + load_tf_weights_in_gpt_neo, + ) + from .models.gpt_neox import ( + GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTNeoXForCausalLM, + GPTNeoXForQuestionAnswering, + GPTNeoXForSequenceClassification, + GPTNeoXForTokenClassification, + GPTNeoXLayer, + GPTNeoXModel, + GPTNeoXPreTrainedModel, + ) + from .models.gpt_neox_japanese import ( + GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTNeoXJapaneseForCausalLM, + GPTNeoXJapaneseLayer, + GPTNeoXJapaneseModel, + GPTNeoXJapanesePreTrainedModel, + ) + from .models.gptj import ( + GPTJ_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTJForCausalLM, + GPTJForQuestionAnswering, + GPTJForSequenceClassification, + GPTJModel, + GPTJPreTrainedModel, + ) + from .models.gptsan_japanese import ( + GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST, + GPTSanJapaneseForConditionalGeneration, + GPTSanJapaneseModel, + GPTSanJapanesePreTrainedModel, + ) + from .models.graphormer import ( + GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + GraphormerForGraphClassification, + GraphormerModel, + GraphormerPreTrainedModel, + ) + from .models.groupvit import ( + GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + GroupViTModel, + GroupViTPreTrainedModel, + GroupViTTextModel, + GroupViTVisionModel, + ) + from .models.hubert import ( + HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + HubertForCTC, + HubertForSequenceClassification, + HubertModel, + HubertPreTrainedModel, + ) + from .models.ibert import ( + IBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + IBertForMaskedLM, + IBertForMultipleChoice, + IBertForQuestionAnswering, + IBertForSequenceClassification, + IBertForTokenClassification, + IBertModel, + IBertPreTrainedModel, + ) + from .models.idefics import ( + IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST, + IdeficsForVisionText2Text, + IdeficsModel, + IdeficsPreTrainedModel, + IdeficsProcessor, + ) + from .models.imagegpt import ( + IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST, + ImageGPTForCausalImageModeling, + ImageGPTForImageClassification, + ImageGPTModel, + ImageGPTPreTrainedModel, + load_tf_weights_in_imagegpt, + ) + from .models.informer import ( + INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + InformerForPrediction, + InformerModel, + InformerPreTrainedModel, + ) + from .models.instructblip import ( + INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + InstructBlipForConditionalGeneration, + InstructBlipPreTrainedModel, + InstructBlipQFormerModel, + InstructBlipVisionModel, + ) + from .models.jukebox import ( + JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST, + JukeboxModel, + JukeboxPreTrainedModel, + JukeboxPrior, + JukeboxVQVAE, + ) + from .models.layoutlm import ( + LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST, + LayoutLMForMaskedLM, + LayoutLMForQuestionAnswering, + LayoutLMForSequenceClassification, + LayoutLMForTokenClassification, + LayoutLMModel, + LayoutLMPreTrainedModel, + ) + from .models.layoutlmv2 import ( + LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST, + LayoutLMv2ForQuestionAnswering, + LayoutLMv2ForSequenceClassification, + LayoutLMv2ForTokenClassification, + LayoutLMv2Model, + LayoutLMv2PreTrainedModel, + ) + from .models.layoutlmv3 import ( + LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST, + LayoutLMv3ForQuestionAnswering, + LayoutLMv3ForSequenceClassification, + LayoutLMv3ForTokenClassification, + LayoutLMv3Model, + LayoutLMv3PreTrainedModel, + ) + from .models.led import ( + LED_PRETRAINED_MODEL_ARCHIVE_LIST, + LEDForConditionalGeneration, + LEDForQuestionAnswering, + LEDForSequenceClassification, + LEDModel, + LEDPreTrainedModel, + ) + from .models.levit import ( + LEVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + LevitForImageClassification, + LevitForImageClassificationWithTeacher, + LevitModel, + LevitPreTrainedModel, + ) + from .models.lilt import ( + LILT_PRETRAINED_MODEL_ARCHIVE_LIST, + LiltForQuestionAnswering, + LiltForSequenceClassification, + LiltForTokenClassification, + LiltModel, + LiltPreTrainedModel, + ) + from .models.llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel + from .models.longformer import ( + LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + LongformerForMaskedLM, + LongformerForMultipleChoice, + LongformerForQuestionAnswering, + LongformerForSequenceClassification, + LongformerForTokenClassification, + LongformerModel, + LongformerPreTrainedModel, + LongformerSelfAttention, + ) + from .models.longt5 import ( + LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST, + LongT5EncoderModel, + LongT5ForConditionalGeneration, + LongT5Model, + LongT5PreTrainedModel, + ) + from .models.luke import ( + LUKE_PRETRAINED_MODEL_ARCHIVE_LIST, + LukeForEntityClassification, + LukeForEntityPairClassification, + LukeForEntitySpanClassification, + LukeForMaskedLM, + LukeForMultipleChoice, + LukeForQuestionAnswering, + LukeForSequenceClassification, + LukeForTokenClassification, + LukeModel, + LukePreTrainedModel, + ) + from .models.lxmert import ( + LxmertEncoder, + LxmertForPreTraining, + LxmertForQuestionAnswering, + LxmertModel, + LxmertPreTrainedModel, + LxmertVisualFeatureEncoder, + LxmertXLayer, + ) + from .models.m2m_100 import ( + M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST, + M2M100ForConditionalGeneration, + M2M100Model, + M2M100PreTrainedModel, + ) + from .models.marian import MarianForCausalLM, MarianModel, MarianMTModel + from .models.markuplm import ( + MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST, + MarkupLMForQuestionAnswering, + MarkupLMForSequenceClassification, + MarkupLMForTokenClassification, + MarkupLMModel, + MarkupLMPreTrainedModel, + ) + from .models.mask2former import ( + MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + Mask2FormerForUniversalSegmentation, + Mask2FormerModel, + Mask2FormerPreTrainedModel, + ) + from .models.maskformer import ( + MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + MaskFormerForInstanceSegmentation, + MaskFormerModel, + MaskFormerPreTrainedModel, + MaskFormerSwinBackbone, + ) + from .models.mbart import ( + MBartForCausalLM, + MBartForConditionalGeneration, + MBartForQuestionAnswering, + MBartForSequenceClassification, + MBartModel, + MBartPreTrainedModel, + ) + from .models.mega import ( + MEGA_PRETRAINED_MODEL_ARCHIVE_LIST, + MegaForCausalLM, + MegaForMaskedLM, + MegaForMultipleChoice, + MegaForQuestionAnswering, + MegaForSequenceClassification, + MegaForTokenClassification, + MegaModel, + MegaPreTrainedModel, + ) + from .models.megatron_bert import ( + MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST, + MegatronBertForCausalLM, + MegatronBertForMaskedLM, + MegatronBertForMultipleChoice, + MegatronBertForNextSentencePrediction, + MegatronBertForPreTraining, + MegatronBertForQuestionAnswering, + MegatronBertForSequenceClassification, + MegatronBertForTokenClassification, + MegatronBertModel, + MegatronBertPreTrainedModel, + ) + from .models.mgp_str import ( + MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST, + MgpstrForSceneTextRecognition, + MgpstrModel, + MgpstrPreTrainedModel, + ) + from .models.mistral import ( + MistralForCausalLM, + MistralForSequenceClassification, + MistralModel, + MistralPreTrainedModel, + ) + from .models.mobilebert import ( + MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + MobileBertForMaskedLM, + MobileBertForMultipleChoice, + MobileBertForNextSentencePrediction, + MobileBertForPreTraining, + MobileBertForQuestionAnswering, + MobileBertForSequenceClassification, + MobileBertForTokenClassification, + MobileBertLayer, + MobileBertModel, + MobileBertPreTrainedModel, + load_tf_weights_in_mobilebert, + ) + from .models.mobilenet_v1 import ( + MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST, + MobileNetV1ForImageClassification, + MobileNetV1Model, + MobileNetV1PreTrainedModel, + load_tf_weights_in_mobilenet_v1, + ) + from .models.mobilenet_v2 import ( + MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST, + MobileNetV2ForImageClassification, + MobileNetV2ForSemanticSegmentation, + MobileNetV2Model, + MobileNetV2PreTrainedModel, + load_tf_weights_in_mobilenet_v2, + ) + from .models.mobilevit import ( + MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + MobileViTForImageClassification, + MobileViTForSemanticSegmentation, + MobileViTModel, + MobileViTPreTrainedModel, + ) + from .models.mobilevitv2 import ( + MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST, + MobileViTV2ForImageClassification, + MobileViTV2ForSemanticSegmentation, + MobileViTV2Model, + MobileViTV2PreTrainedModel, + ) + from .models.mpnet import ( + MPNET_PRETRAINED_MODEL_ARCHIVE_LIST, + MPNetForMaskedLM, + MPNetForMultipleChoice, + MPNetForQuestionAnswering, + MPNetForSequenceClassification, + MPNetForTokenClassification, + MPNetLayer, + MPNetModel, + MPNetPreTrainedModel, + ) + from .models.mpt import ( + MPT_PRETRAINED_MODEL_ARCHIVE_LIST, + MptForCausalLM, + MptForQuestionAnswering, + MptForSequenceClassification, + MptForTokenClassification, + MptModel, + MptPreTrainedModel, + ) + from .models.mra import ( + MRA_PRETRAINED_MODEL_ARCHIVE_LIST, + MraForMaskedLM, + MraForMultipleChoice, + MraForQuestionAnswering, + MraForSequenceClassification, + MraForTokenClassification, + MraModel, + MraPreTrainedModel, + ) + from .models.mt5 import ( + MT5EncoderModel, + MT5ForConditionalGeneration, + MT5ForQuestionAnswering, + MT5ForSequenceClassification, + MT5Model, + MT5PreTrainedModel, + ) + from .models.musicgen import ( + MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST, + MusicgenForCausalLM, + MusicgenForConditionalGeneration, + MusicgenModel, + MusicgenPreTrainedModel, + MusicgenProcessor, + ) + from .models.mvp import ( + MVP_PRETRAINED_MODEL_ARCHIVE_LIST, + MvpForCausalLM, + MvpForConditionalGeneration, + MvpForQuestionAnswering, + MvpForSequenceClassification, + MvpModel, + MvpPreTrainedModel, + ) + from .models.nat import ( + NAT_PRETRAINED_MODEL_ARCHIVE_LIST, + NatBackbone, + NatForImageClassification, + NatModel, + NatPreTrainedModel, + ) + from .models.nezha import ( + NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST, + NezhaForMaskedLM, + NezhaForMultipleChoice, + NezhaForNextSentencePrediction, + NezhaForPreTraining, + NezhaForQuestionAnswering, + NezhaForSequenceClassification, + NezhaForTokenClassification, + NezhaModel, + NezhaPreTrainedModel, + ) + from .models.nllb_moe import ( + NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST, + NllbMoeForConditionalGeneration, + NllbMoeModel, + NllbMoePreTrainedModel, + NllbMoeSparseMLP, + NllbMoeTop2Router, + ) + from .models.nystromformer import ( + NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + NystromformerForMaskedLM, + NystromformerForMultipleChoice, + NystromformerForQuestionAnswering, + NystromformerForSequenceClassification, + NystromformerForTokenClassification, + NystromformerLayer, + NystromformerModel, + NystromformerPreTrainedModel, + ) + from .models.oneformer import ( + ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + OneFormerForUniversalSegmentation, + OneFormerModel, + OneFormerPreTrainedModel, + ) + from .models.openai import ( + OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST, + OpenAIGPTDoubleHeadsModel, + OpenAIGPTForSequenceClassification, + OpenAIGPTLMHeadModel, + OpenAIGPTModel, + OpenAIGPTPreTrainedModel, + load_tf_weights_in_openai_gpt, + ) + from .models.opt import ( + OPT_PRETRAINED_MODEL_ARCHIVE_LIST, + OPTForCausalLM, + OPTForQuestionAnswering, + OPTForSequenceClassification, + OPTModel, + OPTPreTrainedModel, + ) + from .models.owlvit import ( + OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + OwlViTForObjectDetection, + OwlViTModel, + OwlViTPreTrainedModel, + OwlViTTextModel, + OwlViTVisionModel, + ) + from .models.pegasus import ( + PegasusForCausalLM, + PegasusForConditionalGeneration, + PegasusModel, + PegasusPreTrainedModel, + ) + from .models.pegasus_x import ( + PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST, + PegasusXForConditionalGeneration, + PegasusXModel, + PegasusXPreTrainedModel, + ) + from .models.perceiver import ( + PERCEIVER_PRETRAINED_MODEL_ARCHIVE_LIST, + PerceiverForImageClassificationConvProcessing, + PerceiverForImageClassificationFourier, + PerceiverForImageClassificationLearned, + PerceiverForMaskedLM, + PerceiverForMultimodalAutoencoding, + PerceiverForOpticalFlow, + PerceiverForSequenceClassification, + PerceiverLayer, + PerceiverModel, + PerceiverPreTrainedModel, + ) + from .models.persimmon import ( + PersimmonForCausalLM, + PersimmonForSequenceClassification, + PersimmonModel, + PersimmonPreTrainedModel, + ) + from .models.pix2struct import ( + PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST, + Pix2StructForConditionalGeneration, + Pix2StructPreTrainedModel, + Pix2StructTextModel, + Pix2StructVisionModel, + ) + from .models.plbart import ( + PLBART_PRETRAINED_MODEL_ARCHIVE_LIST, + PLBartForCausalLM, + PLBartForConditionalGeneration, + PLBartForSequenceClassification, + PLBartModel, + PLBartPreTrainedModel, + ) + from .models.poolformer import ( + POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + PoolFormerForImageClassification, + PoolFormerModel, + PoolFormerPreTrainedModel, + ) + from .models.pop2piano import ( + POP2PIANO_PRETRAINED_MODEL_ARCHIVE_LIST, + Pop2PianoForConditionalGeneration, + Pop2PianoPreTrainedModel, + ) + from .models.prophetnet import ( + PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST, + ProphetNetDecoder, + ProphetNetEncoder, + ProphetNetForCausalLM, + ProphetNetForConditionalGeneration, + ProphetNetModel, + ProphetNetPreTrainedModel, + ) + from .models.pvt import ( + PVT_PRETRAINED_MODEL_ARCHIVE_LIST, + PvtForImageClassification, + PvtModel, + PvtPreTrainedModel, + ) + from .models.qdqbert import ( + QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + QDQBertForMaskedLM, + QDQBertForMultipleChoice, + QDQBertForNextSentencePrediction, + QDQBertForQuestionAnswering, + QDQBertForSequenceClassification, + QDQBertForTokenClassification, + QDQBertLayer, + QDQBertLMHeadModel, + QDQBertModel, + QDQBertPreTrainedModel, + load_tf_weights_in_qdqbert, + ) + from .models.rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration + from .models.realm import ( + REALM_PRETRAINED_MODEL_ARCHIVE_LIST, + RealmEmbedder, + RealmForOpenQA, + RealmKnowledgeAugEncoder, + RealmPreTrainedModel, + RealmReader, + RealmRetriever, + RealmScorer, + load_tf_weights_in_realm, + ) + from .models.reformer import ( + REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + ReformerAttention, + ReformerForMaskedLM, + ReformerForQuestionAnswering, + ReformerForSequenceClassification, + ReformerLayer, + ReformerModel, + ReformerModelWithLMHead, + ReformerPreTrainedModel, + ) + from .models.regnet import ( + REGNET_PRETRAINED_MODEL_ARCHIVE_LIST, + RegNetForImageClassification, + RegNetModel, + RegNetPreTrainedModel, + ) + from .models.rembert import ( + REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + RemBertForCausalLM, + RemBertForMaskedLM, + RemBertForMultipleChoice, + RemBertForQuestionAnswering, + RemBertForSequenceClassification, + RemBertForTokenClassification, + RemBertLayer, + RemBertModel, + RemBertPreTrainedModel, + load_tf_weights_in_rembert, + ) + from .models.resnet import ( + RESNET_PRETRAINED_MODEL_ARCHIVE_LIST, + ResNetBackbone, + ResNetForImageClassification, + ResNetModel, + ResNetPreTrainedModel, + ) + from .models.roberta import ( + ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + RobertaForCausalLM, + RobertaForMaskedLM, + RobertaForMultipleChoice, + RobertaForQuestionAnswering, + RobertaForSequenceClassification, + RobertaForTokenClassification, + RobertaModel, + RobertaPreTrainedModel, + ) + from .models.roberta_prelayernorm import ( + ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST, + RobertaPreLayerNormForCausalLM, + RobertaPreLayerNormForMaskedLM, + RobertaPreLayerNormForMultipleChoice, + RobertaPreLayerNormForQuestionAnswering, + RobertaPreLayerNormForSequenceClassification, + RobertaPreLayerNormForTokenClassification, + RobertaPreLayerNormModel, + RobertaPreLayerNormPreTrainedModel, + ) + from .models.roc_bert import ( + ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST, + RoCBertForCausalLM, + RoCBertForMaskedLM, + RoCBertForMultipleChoice, + RoCBertForPreTraining, + RoCBertForQuestionAnswering, + RoCBertForSequenceClassification, + RoCBertForTokenClassification, + RoCBertLayer, + RoCBertModel, + RoCBertPreTrainedModel, + load_tf_weights_in_roc_bert, + ) + from .models.roformer import ( + ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + RoFormerForCausalLM, + RoFormerForMaskedLM, + RoFormerForMultipleChoice, + RoFormerForQuestionAnswering, + RoFormerForSequenceClassification, + RoFormerForTokenClassification, + RoFormerLayer, + RoFormerModel, + RoFormerPreTrainedModel, + load_tf_weights_in_roformer, + ) + from .models.rwkv import ( + RWKV_PRETRAINED_MODEL_ARCHIVE_LIST, + RwkvForCausalLM, + RwkvModel, + RwkvPreTrainedModel, + ) + from .models.sam import ( + SAM_PRETRAINED_MODEL_ARCHIVE_LIST, + SamModel, + SamPreTrainedModel, + ) + from .models.segformer import ( + SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + SegformerDecodeHead, + SegformerForImageClassification, + SegformerForSemanticSegmentation, + SegformerLayer, + SegformerModel, + SegformerPreTrainedModel, + ) + from .models.sew import ( + SEW_PRETRAINED_MODEL_ARCHIVE_LIST, + SEWForCTC, + SEWForSequenceClassification, + SEWModel, + SEWPreTrainedModel, + ) + from .models.sew_d import ( + SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST, + SEWDForCTC, + SEWDForSequenceClassification, + SEWDModel, + SEWDPreTrainedModel, + ) + from .models.speech_encoder_decoder import SpeechEncoderDecoderModel + from .models.speech_to_text import ( + SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST, + Speech2TextForConditionalGeneration, + Speech2TextModel, + Speech2TextPreTrainedModel, + ) + from .models.speech_to_text_2 import Speech2Text2ForCausalLM, Speech2Text2PreTrainedModel + from .models.speecht5 import ( + SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST, + SpeechT5ForSpeechToSpeech, + SpeechT5ForSpeechToText, + SpeechT5ForTextToSpeech, + SpeechT5HifiGan, + SpeechT5Model, + SpeechT5PreTrainedModel, + ) + from .models.splinter import ( + SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST, + SplinterForPreTraining, + SplinterForQuestionAnswering, + SplinterLayer, + SplinterModel, + SplinterPreTrainedModel, + ) + from .models.squeezebert import ( + SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + SqueezeBertForMaskedLM, + SqueezeBertForMultipleChoice, + SqueezeBertForQuestionAnswering, + SqueezeBertForSequenceClassification, + SqueezeBertForTokenClassification, + SqueezeBertModel, + SqueezeBertModule, + SqueezeBertPreTrainedModel, + ) + from .models.swiftformer import ( + SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + SwiftFormerForImageClassification, + SwiftFormerModel, + SwiftFormerPreTrainedModel, + ) + from .models.swin import ( + SWIN_PRETRAINED_MODEL_ARCHIVE_LIST, + SwinBackbone, + SwinForImageClassification, + SwinForMaskedImageModeling, + SwinModel, + SwinPreTrainedModel, + ) + from .models.swin2sr import ( + SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST, + Swin2SRForImageSuperResolution, + Swin2SRModel, + Swin2SRPreTrainedModel, + ) + from .models.swinv2 import ( + SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST, + Swinv2ForImageClassification, + Swinv2ForMaskedImageModeling, + Swinv2Model, + Swinv2PreTrainedModel, + ) + from .models.switch_transformers import ( + SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST, + SwitchTransformersEncoderModel, + SwitchTransformersForConditionalGeneration, + SwitchTransformersModel, + SwitchTransformersPreTrainedModel, + SwitchTransformersSparseMLP, + SwitchTransformersTop1Router, + ) + from .models.t5 import ( + T5_PRETRAINED_MODEL_ARCHIVE_LIST, + T5EncoderModel, + T5ForConditionalGeneration, + T5ForQuestionAnswering, + T5ForSequenceClassification, + T5Model, + T5PreTrainedModel, + load_tf_weights_in_t5, + ) + from .models.table_transformer import ( + TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TableTransformerForObjectDetection, + TableTransformerModel, + TableTransformerPreTrainedModel, + ) + from .models.tapas import ( + TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST, + TapasForMaskedLM, + TapasForQuestionAnswering, + TapasForSequenceClassification, + TapasModel, + TapasPreTrainedModel, + load_tf_weights_in_tapas, + ) + from .models.time_series_transformer import ( + TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TimeSeriesTransformerForPrediction, + TimeSeriesTransformerModel, + TimeSeriesTransformerPreTrainedModel, + ) + from .models.timesformer import ( + TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TimesformerForVideoClassification, + TimesformerModel, + TimesformerPreTrainedModel, + ) + from .models.timm_backbone import TimmBackbone + from .models.transfo_xl import ( + TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST, + AdaptiveEmbedding, + TransfoXLForSequenceClassification, + TransfoXLLMHeadModel, + TransfoXLModel, + TransfoXLPreTrainedModel, + load_tf_weights_in_transfo_xl, + ) + from .models.trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel + from .models.tvlt import ( + TVLT_PRETRAINED_MODEL_ARCHIVE_LIST, + TvltForAudioVisualClassification, + TvltForPreTraining, + TvltModel, + TvltPreTrainedModel, + ) + from .models.umt5 import ( + UMT5EncoderModel, + UMT5ForConditionalGeneration, + UMT5ForQuestionAnswering, + UMT5ForSequenceClassification, + UMT5Model, + UMT5PreTrainedModel, + ) + from .models.unispeech import ( + UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST, + UniSpeechForCTC, + UniSpeechForPreTraining, + UniSpeechForSequenceClassification, + UniSpeechModel, + UniSpeechPreTrainedModel, + ) + from .models.unispeech_sat import ( + UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST, + UniSpeechSatForAudioFrameClassification, + UniSpeechSatForCTC, + UniSpeechSatForPreTraining, + UniSpeechSatForSequenceClassification, + UniSpeechSatForXVector, + UniSpeechSatModel, + UniSpeechSatPreTrainedModel, + ) + from .models.upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel + from .models.videomae import ( + VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST, + VideoMAEForPreTraining, + VideoMAEForVideoClassification, + VideoMAEModel, + VideoMAEPreTrainedModel, + ) + from .models.vilt import ( + VILT_PRETRAINED_MODEL_ARCHIVE_LIST, + ViltForImageAndTextRetrieval, + ViltForImagesAndTextClassification, + ViltForMaskedLM, + ViltForQuestionAnswering, + ViltForTokenClassification, + ViltLayer, + ViltModel, + ViltPreTrainedModel, + ) + from .models.vision_encoder_decoder import VisionEncoderDecoderModel + from .models.vision_text_dual_encoder import VisionTextDualEncoderModel + from .models.visual_bert import ( + VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST, + VisualBertForMultipleChoice, + VisualBertForPreTraining, + VisualBertForQuestionAnswering, + VisualBertForRegionToPhraseAlignment, + VisualBertForVisualReasoning, + VisualBertLayer, + VisualBertModel, + VisualBertPreTrainedModel, + ) + from .models.vit import ( + VIT_PRETRAINED_MODEL_ARCHIVE_LIST, + ViTForImageClassification, + ViTForMaskedImageModeling, + ViTModel, + ViTPreTrainedModel, + ) + from .models.vit_hybrid import ( + VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST, + ViTHybridForImageClassification, + ViTHybridModel, + ViTHybridPreTrainedModel, + ) + from .models.vit_mae import ( + VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST, + ViTMAEForPreTraining, + ViTMAELayer, + ViTMAEModel, + ViTMAEPreTrainedModel, + ) + from .models.vit_msn import ( + VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST, + ViTMSNForImageClassification, + ViTMSNModel, + ViTMSNPreTrainedModel, + ) + from .models.vitdet import ( + VITDET_PRETRAINED_MODEL_ARCHIVE_LIST, + VitDetBackbone, + VitDetModel, + VitDetPreTrainedModel, + ) + from .models.vitmatte import ( + VITMATTE_PRETRAINED_MODEL_ARCHIVE_LIST, + VitMatteForImageMatting, + VitMattePreTrainedModel, + ) + from .models.vits import ( + VITS_PRETRAINED_MODEL_ARCHIVE_LIST, + VitsModel, + VitsPreTrainedModel, + ) + from .models.vivit import ( + VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + VivitForVideoClassification, + VivitModel, + VivitPreTrainedModel, + ) + from .models.wav2vec2 import ( + WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, + Wav2Vec2ForAudioFrameClassification, + Wav2Vec2ForCTC, + Wav2Vec2ForMaskedLM, + Wav2Vec2ForPreTraining, + Wav2Vec2ForSequenceClassification, + Wav2Vec2ForXVector, + Wav2Vec2Model, + Wav2Vec2PreTrainedModel, + ) + from .models.wav2vec2_conformer import ( + WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + Wav2Vec2ConformerForAudioFrameClassification, + Wav2Vec2ConformerForCTC, + Wav2Vec2ConformerForPreTraining, + Wav2Vec2ConformerForSequenceClassification, + Wav2Vec2ConformerForXVector, + Wav2Vec2ConformerModel, + Wav2Vec2ConformerPreTrainedModel, + ) + from .models.wavlm import ( + WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST, + WavLMForAudioFrameClassification, + WavLMForCTC, + WavLMForSequenceClassification, + WavLMForXVector, + WavLMModel, + WavLMPreTrainedModel, + ) + from .models.whisper import ( + WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST, + WhisperForAudioClassification, + WhisperForConditionalGeneration, + WhisperModel, + WhisperPreTrainedModel, + ) + from .models.x_clip import ( + XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + XCLIPModel, + XCLIPPreTrainedModel, + XCLIPTextModel, + XCLIPVisionModel, + ) + from .models.xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel + from .models.xlm import ( + XLM_PRETRAINED_MODEL_ARCHIVE_LIST, + XLMForMultipleChoice, + XLMForQuestionAnswering, + XLMForQuestionAnsweringSimple, + XLMForSequenceClassification, + XLMForTokenClassification, + XLMModel, + XLMPreTrainedModel, + XLMWithLMHeadModel, + ) + from .models.xlm_prophetnet import ( + XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST, + XLMProphetNetDecoder, + XLMProphetNetEncoder, + XLMProphetNetForCausalLM, + XLMProphetNetForConditionalGeneration, + XLMProphetNetModel, + XLMProphetNetPreTrainedModel, + ) + from .models.xlm_roberta import ( + XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + XLMRobertaForCausalLM, + XLMRobertaForMaskedLM, + XLMRobertaForMultipleChoice, + XLMRobertaForQuestionAnswering, + XLMRobertaForSequenceClassification, + XLMRobertaForTokenClassification, + XLMRobertaModel, + XLMRobertaPreTrainedModel, + ) + from .models.xlm_roberta_xl import ( + XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST, + XLMRobertaXLForCausalLM, + XLMRobertaXLForMaskedLM, + XLMRobertaXLForMultipleChoice, + XLMRobertaXLForQuestionAnswering, + XLMRobertaXLForSequenceClassification, + XLMRobertaXLForTokenClassification, + XLMRobertaXLModel, + XLMRobertaXLPreTrainedModel, + ) + from .models.xlnet import ( + XLNET_PRETRAINED_MODEL_ARCHIVE_LIST, + XLNetForMultipleChoice, + XLNetForQuestionAnswering, + XLNetForQuestionAnsweringSimple, + XLNetForSequenceClassification, + XLNetForTokenClassification, + XLNetLMHeadModel, + XLNetModel, + XLNetPreTrainedModel, + load_tf_weights_in_xlnet, + ) + from .models.xmod import ( + XMOD_PRETRAINED_MODEL_ARCHIVE_LIST, + XmodForCausalLM, + XmodForMaskedLM, + XmodForMultipleChoice, + XmodForQuestionAnswering, + XmodForSequenceClassification, + XmodForTokenClassification, + XmodModel, + XmodPreTrainedModel, + ) + from .models.yolos import ( + YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST, + YolosForObjectDetection, + YolosModel, + YolosPreTrainedModel, + ) + from .models.yoso import ( + YOSO_PRETRAINED_MODEL_ARCHIVE_LIST, + YosoForMaskedLM, + YosoForMultipleChoice, + YosoForQuestionAnswering, + YosoForSequenceClassification, + YosoForTokenClassification, + YosoLayer, + YosoModel, + YosoPreTrainedModel, + ) + + # Optimization + from .optimization import ( + Adafactor, + AdamW, + get_constant_schedule, + get_constant_schedule_with_warmup, + get_cosine_schedule_with_warmup, + get_cosine_with_hard_restarts_schedule_with_warmup, + get_inverse_sqrt_schedule, + get_linear_schedule_with_warmup, + get_polynomial_decay_schedule_with_warmup, + get_scheduler, + ) + from .pytorch_utils import Conv1D, apply_chunking_to_forward, prune_layer + + # Trainer + from .trainer import Trainer + from .trainer_pt_utils import torch_distributed_zero_first + from .trainer_seq2seq import Seq2SeqTrainer + + # TensorFlow + try: + if not is_tf_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + # Import the same objects as dummies to get them in the namespace. + # They will raise an import error if the user tries to instantiate / use them. + from .utils.dummy_tf_objects import * + else: + from .benchmark.benchmark_args_tf import TensorFlowBenchmarkArguments + + # Benchmarks + from .benchmark.benchmark_tf import TensorFlowBenchmark + from .generation import ( + TFForcedBOSTokenLogitsProcessor, + TFForcedEOSTokenLogitsProcessor, + TFForceTokensLogitsProcessor, + TFGenerationMixin, + TFLogitsProcessor, + TFLogitsProcessorList, + TFLogitsWarper, + TFMinLengthLogitsProcessor, + TFNoBadWordsLogitsProcessor, + TFNoRepeatNGramLogitsProcessor, + TFRepetitionPenaltyLogitsProcessor, + TFSuppressTokensAtBeginLogitsProcessor, + TFSuppressTokensLogitsProcessor, + TFTemperatureLogitsWarper, + TFTopKLogitsWarper, + TFTopPLogitsWarper, + tf_top_k_top_p_filtering, + ) + from .keras_callbacks import KerasMetricCallback, PushToHubCallback + from .modeling_tf_utils import TFPreTrainedModel, TFSequenceSummary, TFSharedEmbeddings, shape_list + + # TensorFlow model imports + from .models.albert import ( + TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFAlbertForMaskedLM, + TFAlbertForMultipleChoice, + TFAlbertForPreTraining, + TFAlbertForQuestionAnswering, + TFAlbertForSequenceClassification, + TFAlbertForTokenClassification, + TFAlbertMainLayer, + TFAlbertModel, + TFAlbertPreTrainedModel, + ) + from .models.auto import ( + TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, + TF_MODEL_FOR_CAUSAL_LM_MAPPING, + TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, + TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING, + TF_MODEL_FOR_MASK_GENERATION_MAPPING, + TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING, + TF_MODEL_FOR_MASKED_LM_MAPPING, + TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING, + TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING, + TF_MODEL_FOR_PRETRAINING_MAPPING, + TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING, + TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING, + TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, + TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, + TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, + TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING, + TF_MODEL_FOR_TEXT_ENCODING_MAPPING, + TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, + TF_MODEL_FOR_VISION_2_SEQ_MAPPING, + TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING, + TF_MODEL_MAPPING, + TF_MODEL_WITH_LM_HEAD_MAPPING, + TFAutoModel, + TFAutoModelForAudioClassification, + TFAutoModelForCausalLM, + TFAutoModelForDocumentQuestionAnswering, + TFAutoModelForImageClassification, + TFAutoModelForMaskedImageModeling, + TFAutoModelForMaskedLM, + TFAutoModelForMaskGeneration, + TFAutoModelForMultipleChoice, + TFAutoModelForNextSentencePrediction, + TFAutoModelForPreTraining, + TFAutoModelForQuestionAnswering, + TFAutoModelForSemanticSegmentation, + TFAutoModelForSeq2SeqLM, + TFAutoModelForSequenceClassification, + TFAutoModelForSpeechSeq2Seq, + TFAutoModelForTableQuestionAnswering, + TFAutoModelForTextEncoding, + TFAutoModelForTokenClassification, + TFAutoModelForVision2Seq, + TFAutoModelForZeroShotImageClassification, + TFAutoModelWithLMHead, + ) + from .models.bart import ( + TFBartForConditionalGeneration, + TFBartForSequenceClassification, + TFBartModel, + TFBartPretrainedModel, + ) + from .models.bert import ( + TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFBertEmbeddings, + TFBertForMaskedLM, + TFBertForMultipleChoice, + TFBertForNextSentencePrediction, + TFBertForPreTraining, + TFBertForQuestionAnswering, + TFBertForSequenceClassification, + TFBertForTokenClassification, + TFBertLMHeadModel, + TFBertMainLayer, + TFBertModel, + TFBertPreTrainedModel, + ) + from .models.blenderbot import ( + TFBlenderbotForConditionalGeneration, + TFBlenderbotModel, + TFBlenderbotPreTrainedModel, + ) + from .models.blenderbot_small import ( + TFBlenderbotSmallForConditionalGeneration, + TFBlenderbotSmallModel, + TFBlenderbotSmallPreTrainedModel, + ) + from .models.blip import ( + TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + TFBlipForConditionalGeneration, + TFBlipForImageTextRetrieval, + TFBlipForQuestionAnswering, + TFBlipModel, + TFBlipPreTrainedModel, + TFBlipTextModel, + TFBlipVisionModel, + ) + from .models.camembert import ( + TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFCamembertForCausalLM, + TFCamembertForMaskedLM, + TFCamembertForMultipleChoice, + TFCamembertForQuestionAnswering, + TFCamembertForSequenceClassification, + TFCamembertForTokenClassification, + TFCamembertModel, + TFCamembertPreTrainedModel, + ) + from .models.clip import ( + TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST, + TFCLIPModel, + TFCLIPPreTrainedModel, + TFCLIPTextModel, + TFCLIPVisionModel, + ) + from .models.convbert import ( + TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFConvBertForMaskedLM, + TFConvBertForMultipleChoice, + TFConvBertForQuestionAnswering, + TFConvBertForSequenceClassification, + TFConvBertForTokenClassification, + TFConvBertLayer, + TFConvBertModel, + TFConvBertPreTrainedModel, + ) + from .models.convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel + from .models.ctrl import ( + TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST, + TFCTRLForSequenceClassification, + TFCTRLLMHeadModel, + TFCTRLModel, + TFCTRLPreTrainedModel, + ) + from .models.cvt import ( + TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFCvtForImageClassification, + TFCvtModel, + TFCvtPreTrainedModel, + ) + from .models.data2vec import ( + TFData2VecVisionForImageClassification, + TFData2VecVisionForSemanticSegmentation, + TFData2VecVisionModel, + TFData2VecVisionPreTrainedModel, + ) + from .models.deberta import ( + TF_DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + TFDebertaForMaskedLM, + TFDebertaForQuestionAnswering, + TFDebertaForSequenceClassification, + TFDebertaForTokenClassification, + TFDebertaModel, + TFDebertaPreTrainedModel, + ) + from .models.deberta_v2 import ( + TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST, + TFDebertaV2ForMaskedLM, + TFDebertaV2ForMultipleChoice, + TFDebertaV2ForQuestionAnswering, + TFDebertaV2ForSequenceClassification, + TFDebertaV2ForTokenClassification, + TFDebertaV2Model, + TFDebertaV2PreTrainedModel, + ) + from .models.deit import ( + TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFDeiTForImageClassification, + TFDeiTForImageClassificationWithTeacher, + TFDeiTForMaskedImageModeling, + TFDeiTModel, + TFDeiTPreTrainedModel, + ) + from .models.distilbert import ( + TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFDistilBertForMaskedLM, + TFDistilBertForMultipleChoice, + TFDistilBertForQuestionAnswering, + TFDistilBertForSequenceClassification, + TFDistilBertForTokenClassification, + TFDistilBertMainLayer, + TFDistilBertModel, + TFDistilBertPreTrainedModel, + ) + from .models.dpr import ( + TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST, + TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST, + TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFDPRContextEncoder, + TFDPRPretrainedContextEncoder, + TFDPRPretrainedQuestionEncoder, + TFDPRPretrainedReader, + TFDPRQuestionEncoder, + TFDPRReader, + ) + from .models.efficientformer import ( + TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFEfficientFormerForImageClassification, + TFEfficientFormerForImageClassificationWithTeacher, + TFEfficientFormerModel, + TFEfficientFormerPreTrainedModel, + ) + from .models.electra import ( + TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST, + TFElectraForMaskedLM, + TFElectraForMultipleChoice, + TFElectraForPreTraining, + TFElectraForQuestionAnswering, + TFElectraForSequenceClassification, + TFElectraForTokenClassification, + TFElectraModel, + TFElectraPreTrainedModel, + ) + from .models.encoder_decoder import TFEncoderDecoderModel + from .models.esm import ( + ESM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFEsmForMaskedLM, + TFEsmForSequenceClassification, + TFEsmForTokenClassification, + TFEsmModel, + TFEsmPreTrainedModel, + ) + from .models.flaubert import ( + TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFFlaubertForMultipleChoice, + TFFlaubertForQuestionAnsweringSimple, + TFFlaubertForSequenceClassification, + TFFlaubertForTokenClassification, + TFFlaubertModel, + TFFlaubertPreTrainedModel, + TFFlaubertWithLMHeadModel, + ) + from .models.funnel import ( + TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST, + TFFunnelBaseModel, + TFFunnelForMaskedLM, + TFFunnelForMultipleChoice, + TFFunnelForPreTraining, + TFFunnelForQuestionAnswering, + TFFunnelForSequenceClassification, + TFFunnelForTokenClassification, + TFFunnelModel, + TFFunnelPreTrainedModel, + ) + from .models.gpt2 import ( + TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST, + TFGPT2DoubleHeadsModel, + TFGPT2ForSequenceClassification, + TFGPT2LMHeadModel, + TFGPT2MainLayer, + TFGPT2Model, + TFGPT2PreTrainedModel, + ) + from .models.gptj import ( + TFGPTJForCausalLM, + TFGPTJForQuestionAnswering, + TFGPTJForSequenceClassification, + TFGPTJModel, + TFGPTJPreTrainedModel, + ) + from .models.groupvit import ( + TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFGroupViTModel, + TFGroupViTPreTrainedModel, + TFGroupViTTextModel, + TFGroupViTVisionModel, + ) + from .models.hubert import ( + TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFHubertForCTC, + TFHubertModel, + TFHubertPreTrainedModel, + ) + from .models.layoutlm import ( + TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFLayoutLMForMaskedLM, + TFLayoutLMForQuestionAnswering, + TFLayoutLMForSequenceClassification, + TFLayoutLMForTokenClassification, + TFLayoutLMMainLayer, + TFLayoutLMModel, + TFLayoutLMPreTrainedModel, + ) + from .models.layoutlmv3 import ( + TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST, + TFLayoutLMv3ForQuestionAnswering, + TFLayoutLMv3ForSequenceClassification, + TFLayoutLMv3ForTokenClassification, + TFLayoutLMv3Model, + TFLayoutLMv3PreTrainedModel, + ) + from .models.led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel + from .models.longformer import ( + TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFLongformerForMaskedLM, + TFLongformerForMultipleChoice, + TFLongformerForQuestionAnswering, + TFLongformerForSequenceClassification, + TFLongformerForTokenClassification, + TFLongformerModel, + TFLongformerPreTrainedModel, + TFLongformerSelfAttention, + ) + from .models.lxmert import ( + TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFLxmertForPreTraining, + TFLxmertMainLayer, + TFLxmertModel, + TFLxmertPreTrainedModel, + TFLxmertVisualFeatureEncoder, + ) + from .models.marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel + from .models.mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel + from .models.mobilebert import ( + TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFMobileBertForMaskedLM, + TFMobileBertForMultipleChoice, + TFMobileBertForNextSentencePrediction, + TFMobileBertForPreTraining, + TFMobileBertForQuestionAnswering, + TFMobileBertForSequenceClassification, + TFMobileBertForTokenClassification, + TFMobileBertMainLayer, + TFMobileBertModel, + TFMobileBertPreTrainedModel, + ) + from .models.mobilevit import ( + TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFMobileViTForImageClassification, + TFMobileViTForSemanticSegmentation, + TFMobileViTModel, + TFMobileViTPreTrainedModel, + ) + from .models.mpnet import ( + TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST, + TFMPNetForMaskedLM, + TFMPNetForMultipleChoice, + TFMPNetForQuestionAnswering, + TFMPNetForSequenceClassification, + TFMPNetForTokenClassification, + TFMPNetMainLayer, + TFMPNetModel, + TFMPNetPreTrainedModel, + ) + from .models.mt5 import TFMT5EncoderModel, TFMT5ForConditionalGeneration, TFMT5Model + from .models.openai import ( + TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFOpenAIGPTDoubleHeadsModel, + TFOpenAIGPTForSequenceClassification, + TFOpenAIGPTLMHeadModel, + TFOpenAIGPTMainLayer, + TFOpenAIGPTModel, + TFOpenAIGPTPreTrainedModel, + ) + from .models.opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel + from .models.pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel + from .models.rag import TFRagModel, TFRagPreTrainedModel, TFRagSequenceForGeneration, TFRagTokenForGeneration + from .models.regnet import ( + TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST, + TFRegNetForImageClassification, + TFRegNetModel, + TFRegNetPreTrainedModel, + ) + from .models.rembert import ( + TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFRemBertForCausalLM, + TFRemBertForMaskedLM, + TFRemBertForMultipleChoice, + TFRemBertForQuestionAnswering, + TFRemBertForSequenceClassification, + TFRemBertForTokenClassification, + TFRemBertLayer, + TFRemBertModel, + TFRemBertPreTrainedModel, + ) + from .models.resnet import ( + TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST, + TFResNetForImageClassification, + TFResNetModel, + TFResNetPreTrainedModel, + ) + from .models.roberta import ( + TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + TFRobertaForCausalLM, + TFRobertaForMaskedLM, + TFRobertaForMultipleChoice, + TFRobertaForQuestionAnswering, + TFRobertaForSequenceClassification, + TFRobertaForTokenClassification, + TFRobertaMainLayer, + TFRobertaModel, + TFRobertaPreTrainedModel, + ) + from .models.roberta_prelayernorm import ( + TF_ROBERTA_PRELAYERNORM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFRobertaPreLayerNormForCausalLM, + TFRobertaPreLayerNormForMaskedLM, + TFRobertaPreLayerNormForMultipleChoice, + TFRobertaPreLayerNormForQuestionAnswering, + TFRobertaPreLayerNormForSequenceClassification, + TFRobertaPreLayerNormForTokenClassification, + TFRobertaPreLayerNormMainLayer, + TFRobertaPreLayerNormModel, + TFRobertaPreLayerNormPreTrainedModel, + ) + from .models.roformer import ( + TF_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFRoFormerForCausalLM, + TFRoFormerForMaskedLM, + TFRoFormerForMultipleChoice, + TFRoFormerForQuestionAnswering, + TFRoFormerForSequenceClassification, + TFRoFormerForTokenClassification, + TFRoFormerLayer, + TFRoFormerModel, + TFRoFormerPreTrainedModel, + ) + from .models.sam import ( + TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFSamModel, + TFSamPreTrainedModel, + ) + from .models.segformer import ( + TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFSegformerDecodeHead, + TFSegformerForImageClassification, + TFSegformerForSemanticSegmentation, + TFSegformerModel, + TFSegformerPreTrainedModel, + ) + from .models.speech_to_text import ( + TF_SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST, + TFSpeech2TextForConditionalGeneration, + TFSpeech2TextModel, + TFSpeech2TextPreTrainedModel, + ) + from .models.swin import ( + TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST, + TFSwinForImageClassification, + TFSwinForMaskedImageModeling, + TFSwinModel, + TFSwinPreTrainedModel, + ) + from .models.t5 import ( + TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST, + TFT5EncoderModel, + TFT5ForConditionalGeneration, + TFT5Model, + TFT5PreTrainedModel, + ) + from .models.tapas import ( + TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST, + TFTapasForMaskedLM, + TFTapasForQuestionAnswering, + TFTapasForSequenceClassification, + TFTapasModel, + TFTapasPreTrainedModel, + ) + from .models.transfo_xl import ( + TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST, + TFAdaptiveEmbedding, + TFTransfoXLForSequenceClassification, + TFTransfoXLLMHeadModel, + TFTransfoXLMainLayer, + TFTransfoXLModel, + TFTransfoXLPreTrainedModel, + ) + from .models.vision_encoder_decoder import TFVisionEncoderDecoderModel + from .models.vision_text_dual_encoder import TFVisionTextDualEncoderModel + from .models.vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel + from .models.vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel + from .models.wav2vec2 import ( + TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, + TFWav2Vec2ForCTC, + TFWav2Vec2ForSequenceClassification, + TFWav2Vec2Model, + TFWav2Vec2PreTrainedModel, + ) + from .models.whisper import ( + TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST, + TFWhisperForConditionalGeneration, + TFWhisperModel, + TFWhisperPreTrainedModel, + ) + from .models.xglm import ( + TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFXGLMForCausalLM, + TFXGLMModel, + TFXGLMPreTrainedModel, + ) + from .models.xlm import ( + TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST, + TFXLMForMultipleChoice, + TFXLMForQuestionAnsweringSimple, + TFXLMForSequenceClassification, + TFXLMForTokenClassification, + TFXLMMainLayer, + TFXLMModel, + TFXLMPreTrainedModel, + TFXLMWithLMHeadModel, + ) + from .models.xlm_roberta import ( + TF_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + TFXLMRobertaForCausalLM, + TFXLMRobertaForMaskedLM, + TFXLMRobertaForMultipleChoice, + TFXLMRobertaForQuestionAnswering, + TFXLMRobertaForSequenceClassification, + TFXLMRobertaForTokenClassification, + TFXLMRobertaModel, + TFXLMRobertaPreTrainedModel, + ) + from .models.xlnet import ( + TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST, + TFXLNetForMultipleChoice, + TFXLNetForQuestionAnsweringSimple, + TFXLNetForSequenceClassification, + TFXLNetForTokenClassification, + TFXLNetLMHeadModel, + TFXLNetMainLayer, + TFXLNetModel, + TFXLNetPreTrainedModel, + ) + + # Optimization + from .optimization_tf import AdamWeightDecay, GradientAccumulator, WarmUp, create_optimizer + + # Trainer + from .trainer_tf import TFTrainer + + try: + if not ( + is_librosa_available() + and is_essentia_available() + and is_scipy_available() + and is_torch_available() + and is_pretty_midi_available() + ): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + from .utils.dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects import * + else: + from .models.pop2piano import Pop2PianoFeatureExtractor, Pop2PianoProcessor, Pop2PianoTokenizer + + try: + if not is_flax_available(): + raise OptionalDependencyNotAvailable() + except OptionalDependencyNotAvailable: + # Import the same objects as dummies to get them in the namespace. + # They will raise an import error if the user tries to instantiate / use them. + from .utils.dummy_flax_objects import * + else: + from .generation import ( + FlaxForcedBOSTokenLogitsProcessor, + FlaxForcedEOSTokenLogitsProcessor, + FlaxForceTokensLogitsProcessor, + FlaxGenerationMixin, + FlaxLogitsProcessor, + FlaxLogitsProcessorList, + FlaxLogitsWarper, + FlaxMinLengthLogitsProcessor, + FlaxSuppressTokensAtBeginLogitsProcessor, + FlaxSuppressTokensLogitsProcessor, + FlaxTemperatureLogitsWarper, + FlaxTopKLogitsWarper, + FlaxTopPLogitsWarper, + FlaxWhisperTimeStampLogitsProcessor, + ) + from .modeling_flax_utils import FlaxPreTrainedModel + + # Flax model imports + from .models.albert import ( + FlaxAlbertForMaskedLM, + FlaxAlbertForMultipleChoice, + FlaxAlbertForPreTraining, + FlaxAlbertForQuestionAnswering, + FlaxAlbertForSequenceClassification, + FlaxAlbertForTokenClassification, + FlaxAlbertModel, + FlaxAlbertPreTrainedModel, + ) + from .models.auto import ( + FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, + FLAX_MODEL_FOR_CAUSAL_LM_MAPPING, + FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING, + FLAX_MODEL_FOR_MASKED_LM_MAPPING, + FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING, + FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING, + FLAX_MODEL_FOR_PRETRAINING_MAPPING, + FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING, + FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, + FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, + FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, + FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, + FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING, + FLAX_MODEL_MAPPING, + FlaxAutoModel, + FlaxAutoModelForCausalLM, + FlaxAutoModelForImageClassification, + FlaxAutoModelForMaskedLM, + FlaxAutoModelForMultipleChoice, + FlaxAutoModelForNextSentencePrediction, + FlaxAutoModelForPreTraining, + FlaxAutoModelForQuestionAnswering, + FlaxAutoModelForSeq2SeqLM, + FlaxAutoModelForSequenceClassification, + FlaxAutoModelForSpeechSeq2Seq, + FlaxAutoModelForTokenClassification, + FlaxAutoModelForVision2Seq, + ) + from .models.bart import ( + FlaxBartDecoderPreTrainedModel, + FlaxBartForCausalLM, + FlaxBartForConditionalGeneration, + FlaxBartForQuestionAnswering, + FlaxBartForSequenceClassification, + FlaxBartModel, + FlaxBartPreTrainedModel, + ) + from .models.beit import ( + FlaxBeitForImageClassification, + FlaxBeitForMaskedImageModeling, + FlaxBeitModel, + FlaxBeitPreTrainedModel, + ) + from .models.bert import ( + FlaxBertForCausalLM, + FlaxBertForMaskedLM, + FlaxBertForMultipleChoice, + FlaxBertForNextSentencePrediction, + FlaxBertForPreTraining, + FlaxBertForQuestionAnswering, + FlaxBertForSequenceClassification, + FlaxBertForTokenClassification, + FlaxBertModel, + FlaxBertPreTrainedModel, + ) + from .models.big_bird import ( + FlaxBigBirdForCausalLM, + FlaxBigBirdForMaskedLM, + FlaxBigBirdForMultipleChoice, + FlaxBigBirdForPreTraining, + FlaxBigBirdForQuestionAnswering, + FlaxBigBirdForSequenceClassification, + FlaxBigBirdForTokenClassification, + FlaxBigBirdModel, + FlaxBigBirdPreTrainedModel, + ) + from .models.blenderbot import ( + FlaxBlenderbotForConditionalGeneration, + FlaxBlenderbotModel, + FlaxBlenderbotPreTrainedModel, + ) + from .models.blenderbot_small import ( + FlaxBlenderbotSmallForConditionalGeneration, + FlaxBlenderbotSmallModel, + FlaxBlenderbotSmallPreTrainedModel, + ) + from .models.bloom import FlaxBloomForCausalLM, FlaxBloomModel, FlaxBloomPreTrainedModel + from .models.clip import ( + FlaxCLIPModel, + FlaxCLIPPreTrainedModel, + FlaxCLIPTextModel, + FlaxCLIPTextModelWithProjection, + FlaxCLIPTextPreTrainedModel, + FlaxCLIPVisionModel, + FlaxCLIPVisionPreTrainedModel, + ) + from .models.distilbert import ( + FlaxDistilBertForMaskedLM, + FlaxDistilBertForMultipleChoice, + FlaxDistilBertForQuestionAnswering, + FlaxDistilBertForSequenceClassification, + FlaxDistilBertForTokenClassification, + FlaxDistilBertModel, + FlaxDistilBertPreTrainedModel, + ) + from .models.electra import ( + FlaxElectraForCausalLM, + FlaxElectraForMaskedLM, + FlaxElectraForMultipleChoice, + FlaxElectraForPreTraining, + FlaxElectraForQuestionAnswering, + FlaxElectraForSequenceClassification, + FlaxElectraForTokenClassification, + FlaxElectraModel, + FlaxElectraPreTrainedModel, + ) + from .models.encoder_decoder import FlaxEncoderDecoderModel + from .models.gpt2 import FlaxGPT2LMHeadModel, FlaxGPT2Model, FlaxGPT2PreTrainedModel + from .models.gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel + from .models.gptj import FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel + from .models.longt5 import FlaxLongT5ForConditionalGeneration, FlaxLongT5Model, FlaxLongT5PreTrainedModel + from .models.marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel + from .models.mbart import ( + FlaxMBartForConditionalGeneration, + FlaxMBartForQuestionAnswering, + FlaxMBartForSequenceClassification, + FlaxMBartModel, + FlaxMBartPreTrainedModel, + ) + from .models.mt5 import FlaxMT5EncoderModel, FlaxMT5ForConditionalGeneration, FlaxMT5Model + from .models.opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel + from .models.pegasus import FlaxPegasusForConditionalGeneration, FlaxPegasusModel, FlaxPegasusPreTrainedModel + from .models.regnet import FlaxRegNetForImageClassification, FlaxRegNetModel, FlaxRegNetPreTrainedModel + from .models.resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel + from .models.roberta import ( + FlaxRobertaForCausalLM, + FlaxRobertaForMaskedLM, + FlaxRobertaForMultipleChoice, + FlaxRobertaForQuestionAnswering, + FlaxRobertaForSequenceClassification, + FlaxRobertaForTokenClassification, + FlaxRobertaModel, + FlaxRobertaPreTrainedModel, + ) + from .models.roberta_prelayernorm import ( + FlaxRobertaPreLayerNormForCausalLM, + FlaxRobertaPreLayerNormForMaskedLM, + FlaxRobertaPreLayerNormForMultipleChoice, + FlaxRobertaPreLayerNormForQuestionAnswering, + FlaxRobertaPreLayerNormForSequenceClassification, + FlaxRobertaPreLayerNormForTokenClassification, + FlaxRobertaPreLayerNormModel, + FlaxRobertaPreLayerNormPreTrainedModel, + ) + from .models.roformer import ( + FlaxRoFormerForMaskedLM, + FlaxRoFormerForMultipleChoice, + FlaxRoFormerForQuestionAnswering, + FlaxRoFormerForSequenceClassification, + FlaxRoFormerForTokenClassification, + FlaxRoFormerModel, + FlaxRoFormerPreTrainedModel, + ) + from .models.speech_encoder_decoder import FlaxSpeechEncoderDecoderModel + from .models.t5 import FlaxT5EncoderModel, FlaxT5ForConditionalGeneration, FlaxT5Model, FlaxT5PreTrainedModel + from .models.vision_encoder_decoder import FlaxVisionEncoderDecoderModel + from .models.vision_text_dual_encoder import FlaxVisionTextDualEncoderModel + from .models.vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel + from .models.wav2vec2 import ( + FlaxWav2Vec2ForCTC, + FlaxWav2Vec2ForPreTraining, + FlaxWav2Vec2Model, + FlaxWav2Vec2PreTrainedModel, + ) + from .models.whisper import ( + FlaxWhisperForAudioClassification, + FlaxWhisperForConditionalGeneration, + FlaxWhisperModel, + FlaxWhisperPreTrainedModel, + ) + from .models.xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel + from .models.xlm_roberta import ( + FLAX_XLM_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST, + FlaxXLMRobertaForCausalLM, + FlaxXLMRobertaForMaskedLM, + FlaxXLMRobertaForMultipleChoice, + FlaxXLMRobertaForQuestionAnswering, + FlaxXLMRobertaForSequenceClassification, + FlaxXLMRobertaForTokenClassification, + FlaxXLMRobertaModel, + FlaxXLMRobertaPreTrainedModel, + ) + + +else: + import sys + + sys.modules[__name__] = _LazyModule( + __name__, + globals()["__file__"], + _import_structure, + module_spec=__spec__, + extra_objects={"__version__": __version__}, + ) + + +if not is_tf_available() and not is_torch_available() and not is_flax_available(): + logger.warning( + "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. " + "Models won't be available and only tokenizers, configuration " + "and file/data utilities can be used." + )