# 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__ = "4.47.1" 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_g2p_en_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_torchaudio_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 = { "agents": [ "Agent", "CodeAgent", "HfApiEngine", "ManagedAgent", "PipelineTool", "ReactAgent", "ReactCodeAgent", "ReactJsonAgent", "Tool", "Toolbox", "ToolCollection", "TransformersEngine", "launch_gradio_demo", "load_tool", "stream_to_gradio", "tool", ], "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", "DataCollatorWithFlattening", "DataCollatorWithPadding", "DefaultDataCollator", "default_data_collator", ], "data.metrics": [], "data.processors": [], "debug_utils": [], "dependency_versions_check": [], "dependency_versions_table": [], "dynamic_module_utils": [], "feature_extraction_sequence_utils": ["SequenceFeatureExtractor"], "feature_extraction_utils": ["BatchFeature", "FeatureExtractionMixin"], "file_utils": [], "generation": [ "CompileConfig", "GenerationConfig", "TextIteratorStreamer", "TextStreamer", "WatermarkingConfig", ], "hf_argparser": ["HfArgumentParser"], "hyperparameter_search": [], "image_transforms": [], "integrations": [ "is_clearml_available", "is_comet_available", "is_dvclive_available", "is_neptune_available", "is_optuna_available", "is_ray_available", "is_ray_tune_available", "is_sigopt_available", "is_tensorboard_available", "is_wandb_available", ], "loss": [], "modelcard": ["ModelCard"], # Losses "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": ["AlbertConfig"], "models.align": [ "AlignConfig", "AlignProcessor", "AlignTextConfig", "AlignVisionConfig", ], "models.altclip": [ "AltCLIPConfig", "AltCLIPProcessor", "AltCLIPTextConfig", "AltCLIPVisionConfig", ], "models.audio_spectrogram_transformer": [ "ASTConfig", "ASTFeatureExtractor", ], "models.auto": [ "CONFIG_MAPPING", "FEATURE_EXTRACTOR_MAPPING", "IMAGE_PROCESSOR_MAPPING", "MODEL_NAMES_MAPPING", "PROCESSOR_MAPPING", "TOKENIZER_MAPPING", "AutoConfig", "AutoFeatureExtractor", "AutoImageProcessor", "AutoProcessor", "AutoTokenizer", ], "models.autoformer": ["AutoformerConfig"], "models.bark": [ "BarkCoarseConfig", "BarkConfig", "BarkFineConfig", "BarkProcessor", "BarkSemanticConfig", ], "models.bart": ["BartConfig", "BartTokenizer"], "models.barthez": [], "models.bartpho": [], "models.beit": ["BeitConfig"], "models.bert": [ "BasicTokenizer", "BertConfig", "BertTokenizer", "WordpieceTokenizer", ], "models.bert_generation": ["BertGenerationConfig"], "models.bert_japanese": [ "BertJapaneseTokenizer", "CharacterTokenizer", "MecabTokenizer", ], "models.bertweet": ["BertweetTokenizer"], "models.big_bird": ["BigBirdConfig"], "models.bigbird_pegasus": ["BigBirdPegasusConfig"], "models.biogpt": [ "BioGptConfig", "BioGptTokenizer", ], "models.bit": ["BitConfig"], "models.blenderbot": [ "BlenderbotConfig", "BlenderbotTokenizer", ], "models.blenderbot_small": [ "BlenderbotSmallConfig", "BlenderbotSmallTokenizer", ], "models.blip": [ "BlipConfig", "BlipProcessor", "BlipTextConfig", "BlipVisionConfig", ], "models.blip_2": [ "Blip2Config", "Blip2Processor", "Blip2QFormerConfig", "Blip2VisionConfig", ], "models.bloom": ["BloomConfig"], "models.bridgetower": [ "BridgeTowerConfig", "BridgeTowerProcessor", "BridgeTowerTextConfig", "BridgeTowerVisionConfig", ], "models.bros": [ "BrosConfig", "BrosProcessor", ], "models.byt5": ["ByT5Tokenizer"], "models.camembert": ["CamembertConfig"], "models.canine": [ "CanineConfig", "CanineTokenizer", ], "models.chameleon": [ "ChameleonConfig", "ChameleonProcessor", "ChameleonVQVAEConfig", ], "models.chinese_clip": [ "ChineseCLIPConfig", "ChineseCLIPProcessor", "ChineseCLIPTextConfig", "ChineseCLIPVisionConfig", ], "models.clap": [ "ClapAudioConfig", "ClapConfig", "ClapProcessor", "ClapTextConfig", ], "models.clip": [ "CLIPConfig", "CLIPProcessor", "CLIPTextConfig", "CLIPTokenizer", "CLIPVisionConfig", ], "models.clipseg": [ "CLIPSegConfig", "CLIPSegProcessor", "CLIPSegTextConfig", "CLIPSegVisionConfig", ], "models.clvp": [ "ClvpConfig", "ClvpDecoderConfig", "ClvpEncoderConfig", "ClvpFeatureExtractor", "ClvpProcessor", "ClvpTokenizer", ], "models.code_llama": [], "models.codegen": [ "CodeGenConfig", "CodeGenTokenizer", ], "models.cohere": ["CohereConfig"], "models.conditional_detr": ["ConditionalDetrConfig"], "models.convbert": [ "ConvBertConfig", "ConvBertTokenizer", ], "models.convnext": ["ConvNextConfig"], "models.convnextv2": ["ConvNextV2Config"], "models.cpm": [], "models.cpmant": [ "CpmAntConfig", "CpmAntTokenizer", ], "models.ctrl": [ "CTRLConfig", "CTRLTokenizer", ], "models.cvt": ["CvtConfig"], "models.dac": ["DacConfig", "DacFeatureExtractor"], "models.data2vec": [ "Data2VecAudioConfig", "Data2VecTextConfig", "Data2VecVisionConfig", ], "models.dbrx": ["DbrxConfig"], "models.deberta": [ "DebertaConfig", "DebertaTokenizer", ], "models.deberta_v2": ["DebertaV2Config"], "models.decision_transformer": ["DecisionTransformerConfig"], "models.deformable_detr": ["DeformableDetrConfig"], "models.deit": ["DeiTConfig"], "models.deprecated": [], "models.deprecated.bort": [], "models.deprecated.deta": ["DetaConfig"], "models.deprecated.efficientformer": ["EfficientFormerConfig"], "models.deprecated.ernie_m": ["ErnieMConfig"], "models.deprecated.gptsan_japanese": [ "GPTSanJapaneseConfig", "GPTSanJapaneseTokenizer", ], "models.deprecated.graphormer": ["GraphormerConfig"], "models.deprecated.jukebox": [ "JukeboxConfig", "JukeboxPriorConfig", "JukeboxTokenizer", "JukeboxVQVAEConfig", ], "models.deprecated.mctct": [ "MCTCTConfig", "MCTCTFeatureExtractor", "MCTCTProcessor", ], "models.deprecated.mega": ["MegaConfig"], "models.deprecated.mmbt": ["MMBTConfig"], "models.deprecated.nat": ["NatConfig"], "models.deprecated.nezha": ["NezhaConfig"], "models.deprecated.open_llama": ["OpenLlamaConfig"], "models.deprecated.qdqbert": ["QDQBertConfig"], "models.deprecated.realm": [ "RealmConfig", "RealmTokenizer", ], "models.deprecated.retribert": [ "RetriBertConfig", "RetriBertTokenizer", ], "models.deprecated.speech_to_text_2": [ "Speech2Text2Config", "Speech2Text2Processor", "Speech2Text2Tokenizer", ], "models.deprecated.tapex": ["TapexTokenizer"], "models.deprecated.trajectory_transformer": ["TrajectoryTransformerConfig"], "models.deprecated.transfo_xl": [ "TransfoXLConfig", "TransfoXLCorpus", "TransfoXLTokenizer", ], "models.deprecated.tvlt": [ "TvltConfig", "TvltFeatureExtractor", "TvltProcessor", ], "models.deprecated.van": ["VanConfig"], "models.deprecated.vit_hybrid": ["ViTHybridConfig"], "models.deprecated.xlm_prophetnet": ["XLMProphetNetConfig"], "models.depth_anything": ["DepthAnythingConfig"], "models.detr": ["DetrConfig"], "models.dialogpt": [], "models.dinat": ["DinatConfig"], "models.dinov2": ["Dinov2Config"], "models.distilbert": [ "DistilBertConfig", "DistilBertTokenizer", ], "models.dit": [], "models.donut": [ "DonutProcessor", "DonutSwinConfig", ], "models.dpr": [ "DPRConfig", "DPRContextEncoderTokenizer", "DPRQuestionEncoderTokenizer", "DPRReaderOutput", "DPRReaderTokenizer", ], "models.dpt": ["DPTConfig"], "models.efficientnet": ["EfficientNetConfig"], "models.electra": [ "ElectraConfig", "ElectraTokenizer", ], "models.encodec": [ "EncodecConfig", "EncodecFeatureExtractor", ], "models.encoder_decoder": ["EncoderDecoderConfig"], "models.ernie": ["ErnieConfig"], "models.esm": ["EsmConfig", "EsmTokenizer"], "models.falcon": ["FalconConfig"], "models.falcon_mamba": ["FalconMambaConfig"], "models.fastspeech2_conformer": [ "FastSpeech2ConformerConfig", "FastSpeech2ConformerHifiGanConfig", "FastSpeech2ConformerTokenizer", "FastSpeech2ConformerWithHifiGanConfig", ], "models.flaubert": ["FlaubertConfig", "FlaubertTokenizer"], "models.flava": [ "FlavaConfig", "FlavaImageCodebookConfig", "FlavaImageConfig", "FlavaMultimodalConfig", "FlavaTextConfig", ], "models.fnet": ["FNetConfig"], "models.focalnet": ["FocalNetConfig"], "models.fsmt": [ "FSMTConfig", "FSMTTokenizer", ], "models.funnel": [ "FunnelConfig", "FunnelTokenizer", ], "models.fuyu": ["FuyuConfig"], "models.gemma": ["GemmaConfig"], "models.gemma2": ["Gemma2Config"], "models.git": [ "GitConfig", "GitProcessor", "GitVisionConfig", ], "models.glm": ["GlmConfig"], "models.glpn": ["GLPNConfig"], "models.gpt2": [ "GPT2Config", "GPT2Tokenizer", ], "models.gpt_bigcode": ["GPTBigCodeConfig"], "models.gpt_neo": ["GPTNeoConfig"], "models.gpt_neox": ["GPTNeoXConfig"], "models.gpt_neox_japanese": ["GPTNeoXJapaneseConfig"], "models.gpt_sw3": [], "models.gptj": ["GPTJConfig"], "models.granite": ["GraniteConfig"], "models.granitemoe": ["GraniteMoeConfig"], "models.grounding_dino": [ "GroundingDinoConfig", "GroundingDinoProcessor", ], "models.groupvit": [ "GroupViTConfig", "GroupViTTextConfig", "GroupViTVisionConfig", ], "models.herbert": ["HerbertTokenizer"], "models.hiera": ["HieraConfig"], "models.hubert": ["HubertConfig"], "models.ibert": ["IBertConfig"], "models.idefics": ["IdeficsConfig"], "models.idefics2": ["Idefics2Config"], "models.idefics3": ["Idefics3Config"], "models.ijepa": ["IJepaConfig"], "models.imagegpt": ["ImageGPTConfig"], "models.informer": ["InformerConfig"], "models.instructblip": [ "InstructBlipConfig", "InstructBlipProcessor", "InstructBlipQFormerConfig", "InstructBlipVisionConfig", ], "models.instructblipvideo": [ "InstructBlipVideoConfig", "InstructBlipVideoProcessor", "InstructBlipVideoQFormerConfig", "InstructBlipVideoVisionConfig", ], "models.jamba": ["JambaConfig"], "models.jetmoe": ["JetMoeConfig"], "models.kosmos2": [ "Kosmos2Config", "Kosmos2Processor", ], "models.layoutlm": [ "LayoutLMConfig", "LayoutLMTokenizer", ], "models.layoutlmv2": [ "LayoutLMv2Config", "LayoutLMv2FeatureExtractor", "LayoutLMv2ImageProcessor", "LayoutLMv2Processor", "LayoutLMv2Tokenizer", ], "models.layoutlmv3": [ "LayoutLMv3Config", "LayoutLMv3FeatureExtractor", "LayoutLMv3ImageProcessor", "LayoutLMv3Processor", "LayoutLMv3Tokenizer", ], "models.layoutxlm": ["LayoutXLMProcessor"], "models.led": ["LEDConfig", "LEDTokenizer"], "models.levit": ["LevitConfig"], "models.lilt": ["LiltConfig"], "models.llama": ["LlamaConfig"], "models.llava": [ "LlavaConfig", "LlavaProcessor", ], "models.llava_next": [ "LlavaNextConfig", "LlavaNextProcessor", ], "models.llava_next_video": [ "LlavaNextVideoConfig", "LlavaNextVideoProcessor", ], "models.llava_onevision": ["LlavaOnevisionConfig", "LlavaOnevisionProcessor"], "models.longformer": [ "LongformerConfig", "LongformerTokenizer", ], "models.longt5": ["LongT5Config"], "models.luke": [ "LukeConfig", "LukeTokenizer", ], "models.lxmert": [ "LxmertConfig", "LxmertTokenizer", ], "models.m2m_100": ["M2M100Config"], "models.mamba": ["MambaConfig"], "models.mamba2": ["Mamba2Config"], "models.marian": ["MarianConfig"], "models.markuplm": [ "MarkupLMConfig", "MarkupLMFeatureExtractor", "MarkupLMProcessor", "MarkupLMTokenizer", ], "models.mask2former": ["Mask2FormerConfig"], "models.maskformer": [ "MaskFormerConfig", "MaskFormerSwinConfig", ], "models.mbart": ["MBartConfig"], "models.mbart50": [], "models.megatron_bert": ["MegatronBertConfig"], "models.megatron_gpt2": [], "models.mgp_str": [ "MgpstrConfig", "MgpstrProcessor", "MgpstrTokenizer", ], "models.mimi": ["MimiConfig"], "models.mistral": ["MistralConfig"], "models.mixtral": ["MixtralConfig"], "models.mllama": [ "MllamaConfig", "MllamaProcessor", ], "models.mluke": [], "models.mobilebert": [ "MobileBertConfig", "MobileBertTokenizer", ], "models.mobilenet_v1": ["MobileNetV1Config"], "models.mobilenet_v2": ["MobileNetV2Config"], "models.mobilevit": ["MobileViTConfig"], "models.mobilevitv2": ["MobileViTV2Config"], "models.moshi": [ "MoshiConfig", "MoshiDepthConfig", ], "models.mpnet": [ "MPNetConfig", "MPNetTokenizer", ], "models.mpt": ["MptConfig"], "models.mra": ["MraConfig"], "models.mt5": ["MT5Config"], "models.musicgen": [ "MusicgenConfig", "MusicgenDecoderConfig", ], "models.musicgen_melody": [ "MusicgenMelodyConfig", "MusicgenMelodyDecoderConfig", ], "models.mvp": ["MvpConfig", "MvpTokenizer"], "models.myt5": ["MyT5Tokenizer"], "models.nemotron": ["NemotronConfig"], "models.nllb": [], "models.nllb_moe": ["NllbMoeConfig"], "models.nougat": ["NougatProcessor"], "models.nystromformer": ["NystromformerConfig"], "models.olmo": ["OlmoConfig"], "models.olmo2": ["Olmo2Config"], "models.olmoe": ["OlmoeConfig"], "models.omdet_turbo": [ "OmDetTurboConfig", "OmDetTurboProcessor", ], "models.oneformer": [ "OneFormerConfig", "OneFormerProcessor", ], "models.openai": [ "OpenAIGPTConfig", "OpenAIGPTTokenizer", ], "models.opt": ["OPTConfig"], "models.owlv2": [ "Owlv2Config", "Owlv2Processor", "Owlv2TextConfig", "Owlv2VisionConfig", ], "models.owlvit": [ "OwlViTConfig", "OwlViTProcessor", "OwlViTTextConfig", "OwlViTVisionConfig", ], "models.paligemma": ["PaliGemmaConfig"], "models.patchtsmixer": ["PatchTSMixerConfig"], "models.patchtst": ["PatchTSTConfig"], "models.pegasus": [ "PegasusConfig", "PegasusTokenizer", ], "models.pegasus_x": ["PegasusXConfig"], "models.perceiver": [ "PerceiverConfig", "PerceiverTokenizer", ], "models.persimmon": ["PersimmonConfig"], "models.phi": ["PhiConfig"], "models.phi3": ["Phi3Config"], "models.phimoe": ["PhimoeConfig"], "models.phobert": ["PhobertTokenizer"], "models.pix2struct": [ "Pix2StructConfig", "Pix2StructProcessor", "Pix2StructTextConfig", "Pix2StructVisionConfig", ], "models.pixtral": ["PixtralProcessor", "PixtralVisionConfig"], "models.plbart": ["PLBartConfig"], "models.poolformer": ["PoolFormerConfig"], "models.pop2piano": ["Pop2PianoConfig"], "models.prophetnet": [ "ProphetNetConfig", "ProphetNetTokenizer", ], "models.pvt": ["PvtConfig"], "models.pvt_v2": ["PvtV2Config"], "models.qwen2": [ "Qwen2Config", "Qwen2Tokenizer", ], "models.qwen2_audio": [ "Qwen2AudioConfig", "Qwen2AudioEncoderConfig", "Qwen2AudioProcessor", ], "models.qwen2_moe": ["Qwen2MoeConfig"], "models.qwen2_vl": [ "Qwen2VLConfig", "Qwen2VLProcessor", ], "models.rag": ["RagConfig", "RagRetriever", "RagTokenizer"], "models.recurrent_gemma": ["RecurrentGemmaConfig"], "models.reformer": ["ReformerConfig"], "models.regnet": ["RegNetConfig"], "models.rembert": ["RemBertConfig"], "models.resnet": ["ResNetConfig"], "models.roberta": [ "RobertaConfig", "RobertaTokenizer", ], "models.roberta_prelayernorm": ["RobertaPreLayerNormConfig"], "models.roc_bert": [ "RoCBertConfig", "RoCBertTokenizer", ], "models.roformer": [ "RoFormerConfig", "RoFormerTokenizer", ], "models.rt_detr": ["RTDetrConfig", "RTDetrResNetConfig"], "models.rwkv": ["RwkvConfig"], "models.sam": [ "SamConfig", "SamMaskDecoderConfig", "SamProcessor", "SamPromptEncoderConfig", "SamVisionConfig", ], "models.seamless_m4t": [ "SeamlessM4TConfig", "SeamlessM4TFeatureExtractor", "SeamlessM4TProcessor", ], "models.seamless_m4t_v2": ["SeamlessM4Tv2Config"], "models.segformer": ["SegformerConfig"], "models.seggpt": ["SegGptConfig"], "models.sew": ["SEWConfig"], "models.sew_d": ["SEWDConfig"], "models.siglip": [ "SiglipConfig", "SiglipProcessor", "SiglipTextConfig", "SiglipVisionConfig", ], "models.speech_encoder_decoder": ["SpeechEncoderDecoderConfig"], "models.speech_to_text": [ "Speech2TextConfig", "Speech2TextFeatureExtractor", "Speech2TextProcessor", ], "models.speecht5": [ "SpeechT5Config", "SpeechT5FeatureExtractor", "SpeechT5HifiGanConfig", "SpeechT5Processor", ], "models.splinter": [ "SplinterConfig", "SplinterTokenizer", ], "models.squeezebert": [ "SqueezeBertConfig", "SqueezeBertTokenizer", ], "models.stablelm": ["StableLmConfig"], "models.starcoder2": ["Starcoder2Config"], "models.superpoint": ["SuperPointConfig"], "models.swiftformer": ["SwiftFormerConfig"], "models.swin": ["SwinConfig"], "models.swin2sr": ["Swin2SRConfig"], "models.swinv2": ["Swinv2Config"], "models.switch_transformers": ["SwitchTransformersConfig"], "models.t5": ["T5Config"], "models.table_transformer": ["TableTransformerConfig"], "models.tapas": [ "TapasConfig", "TapasTokenizer", ], "models.time_series_transformer": ["TimeSeriesTransformerConfig"], "models.timesformer": ["TimesformerConfig"], "models.timm_backbone": ["TimmBackboneConfig"], "models.trocr": [ "TrOCRConfig", "TrOCRProcessor", ], "models.tvp": [ "TvpConfig", "TvpProcessor", ], "models.udop": [ "UdopConfig", "UdopProcessor", ], "models.umt5": ["UMT5Config"], "models.unispeech": ["UniSpeechConfig"], "models.unispeech_sat": ["UniSpeechSatConfig"], "models.univnet": [ "UnivNetConfig", "UnivNetFeatureExtractor", ], "models.upernet": ["UperNetConfig"], "models.video_llava": ["VideoLlavaConfig"], "models.videomae": ["VideoMAEConfig"], "models.vilt": [ "ViltConfig", "ViltFeatureExtractor", "ViltImageProcessor", "ViltProcessor", ], "models.vipllava": ["VipLlavaConfig"], "models.vision_encoder_decoder": ["VisionEncoderDecoderConfig"], "models.vision_text_dual_encoder": [ "VisionTextDualEncoderConfig", "VisionTextDualEncoderProcessor", ], "models.visual_bert": ["VisualBertConfig"], "models.vit": ["ViTConfig"], "models.vit_mae": ["ViTMAEConfig"], "models.vit_msn": ["ViTMSNConfig"], "models.vitdet": ["VitDetConfig"], "models.vitmatte": ["VitMatteConfig"], "models.vits": [ "VitsConfig", "VitsTokenizer", ], "models.vivit": ["VivitConfig"], "models.wav2vec2": [ "Wav2Vec2Config", "Wav2Vec2CTCTokenizer", "Wav2Vec2FeatureExtractor", "Wav2Vec2Processor", "Wav2Vec2Tokenizer", ], "models.wav2vec2_bert": [ "Wav2Vec2BertConfig", "Wav2Vec2BertProcessor", ], "models.wav2vec2_conformer": ["Wav2Vec2ConformerConfig"], "models.wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"], "models.wav2vec2_with_lm": ["Wav2Vec2ProcessorWithLM"], "models.wavlm": ["WavLMConfig"], "models.whisper": [ "WhisperConfig", "WhisperFeatureExtractor", "WhisperProcessor", "WhisperTokenizer", ], "models.x_clip": [ "XCLIPConfig", "XCLIPProcessor", "XCLIPTextConfig", "XCLIPVisionConfig", ], "models.xglm": ["XGLMConfig"], "models.xlm": ["XLMConfig", "XLMTokenizer"], "models.xlm_roberta": ["XLMRobertaConfig"], "models.xlm_roberta_xl": ["XLMRobertaXLConfig"], "models.xlnet": ["XLNetConfig"], "models.xmod": ["XmodConfig"], "models.yolos": ["YolosConfig"], "models.yoso": ["YosoConfig"], "models.zamba": ["ZambaConfig"], "models.zoedepth": ["ZoeDepthConfig"], "onnx": [], "pipelines": [ "AudioClassificationPipeline", "AutomaticSpeechRecognitionPipeline", "CsvPipelineDataFormat", "DepthEstimationPipeline", "DocumentQuestionAnsweringPipeline", "FeatureExtractionPipeline", "FillMaskPipeline", "ImageClassificationPipeline", "ImageFeatureExtractionPipeline", "ImageSegmentationPipeline", "ImageTextToTextPipeline", "ImageToImagePipeline", "ImageToTextPipeline", "JsonPipelineDataFormat", "MaskGenerationPipeline", "NerPipeline", "ObjectDetectionPipeline", "PipedPipelineDataFormat", "Pipeline", "PipelineDataFormat", "QuestionAnsweringPipeline", "SummarizationPipeline", "TableQuestionAnsweringPipeline", "Text2TextGenerationPipeline", "TextClassificationPipeline", "TextGenerationPipeline", "TextToAudioPipeline", "TokenClassificationPipeline", "TranslationPipeline", "VideoClassificationPipeline", "VisualQuestionAnsweringPipeline", "ZeroShotAudioClassificationPipeline", "ZeroShotClassificationPipeline", "ZeroShotImageClassificationPipeline", "ZeroShotObjectDetectionPipeline", "pipeline", ], "processing_utils": ["ProcessorMixin"], "quantizers": [], "testing_utils": [], "tokenization_utils": ["PreTrainedTokenizer"], "tokenization_utils_base": [ "AddedToken", "BatchEncoding", "CharSpan", "PreTrainedTokenizerBase", "SpecialTokensMixin", "TokenSpan", ], "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_av_available", "is_bitsandbytes_available", "is_datasets_available", "is_faiss_available", "is_flax_available", "is_keras_nlp_available", "is_phonemizer_available", "is_psutil_available", "is_py3nvml_available", "is_pyctcdecode_available", "is_sacremoses_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_mlu_available", "is_torch_musa_available", "is_torch_neuroncore_available", "is_torch_npu_available", "is_torch_tpu_available", "is_torchvision_available", "is_torch_xla_available", "is_torch_xpu_available", "is_vision_available", "logging", ], "utils.quantization_config": [ "AqlmConfig", "AwqConfig", "BitNetConfig", "BitsAndBytesConfig", "CompressedTensorsConfig", "EetqConfig", "FbgemmFp8Config", "GPTQConfig", "HqqConfig", "QuantoConfig", "TorchAoConfig", ], } # 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.deprecated.ernie_m"].append("ErnieMTokenizer") _import_structure["models.deprecated.xlm_prophetnet"].append("XLMProphetNetTokenizer") _import_structure["models.fnet"].append("FNetTokenizer") _import_structure["models.gemma"].append("GemmaTokenizer") _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.seamless_m4t"].append("SeamlessM4TTokenizer") _import_structure["models.siglip"].append("SiglipTokenizer") _import_structure["models.speech_to_text"].append("Speech2TextTokenizer") _import_structure["models.speecht5"].append("SpeechT5Tokenizer") _import_structure["models.t5"].append("T5Tokenizer") _import_structure["models.udop"].append("UdopTokenizer") _import_structure["models.xglm"].append("XGLMTokenizer") _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.cohere"].append("CohereTokenizerFast") _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.realm"].append("RealmTokenizerFast") _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.gemma"].append("GemmaTokenizerFast") _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.qwen2"].append("Qwen2TokenizerFast") _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.seamless_m4t"].append("SeamlessM4TTokenizerFast") _import_structure["models.splinter"].append("SplinterTokenizerFast") _import_structure["models.squeezebert"].append("SqueezeBertTokenizerFast") _import_structure["models.t5"].append("T5TokenizerFast") _import_structure["models.udop"].append("UdopTokenizerFast") _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", ] # 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_base"] = ["ImageProcessingMixin"] _import_structure["image_processing_utils"] = ["BaseImageProcessor"] _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.chameleon"].append("ChameleonImageProcessor") _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.deprecated.deta"].append("DetaImageProcessor") _import_structure["models.deprecated.efficientformer"].append("EfficientFormerImageProcessor") _import_structure["models.deprecated.tvlt"].append("TvltImageProcessor") _import_structure["models.deprecated.vit_hybrid"].extend(["ViTHybridImageProcessor"]) _import_structure["models.detr"].extend(["DetrFeatureExtractor", "DetrImageProcessor"]) _import_structure["models.donut"].extend(["DonutFeatureExtractor", "DonutImageProcessor"]) _import_structure["models.dpt"].extend(["DPTFeatureExtractor", "DPTImageProcessor"]) _import_structure["models.efficientnet"].append("EfficientNetImageProcessor") _import_structure["models.flava"].extend(["FlavaFeatureExtractor", "FlavaImageProcessor", "FlavaProcessor"]) _import_structure["models.fuyu"].extend(["FuyuImageProcessor", "FuyuProcessor"]) _import_structure["models.glpn"].extend(["GLPNFeatureExtractor", "GLPNImageProcessor"]) _import_structure["models.grounding_dino"].extend(["GroundingDinoImageProcessor"]) _import_structure["models.idefics"].extend(["IdeficsImageProcessor"]) _import_structure["models.idefics2"].extend(["Idefics2ImageProcessor"]) _import_structure["models.idefics3"].extend(["Idefics3ImageProcessor"]) _import_structure["models.imagegpt"].extend(["ImageGPTFeatureExtractor", "ImageGPTImageProcessor"]) _import_structure["models.instructblipvideo"].extend(["InstructBlipVideoImageProcessor"]) _import_structure["models.layoutlmv2"].extend(["LayoutLMv2FeatureExtractor", "LayoutLMv2ImageProcessor"]) _import_structure["models.layoutlmv3"].extend(["LayoutLMv3FeatureExtractor", "LayoutLMv3ImageProcessor"]) _import_structure["models.levit"].extend(["LevitFeatureExtractor", "LevitImageProcessor"]) _import_structure["models.llava_next"].append("LlavaNextImageProcessor") _import_structure["models.llava_next_video"].append("LlavaNextVideoImageProcessor") _import_structure["models.llava_onevision"].extend( ["LlavaOnevisionImageProcessor", "LlavaOnevisionVideoProcessor"] ) _import_structure["models.mask2former"].append("Mask2FormerImageProcessor") _import_structure["models.maskformer"].extend(["MaskFormerFeatureExtractor", "MaskFormerImageProcessor"]) _import_structure["models.mllama"].extend(["MllamaImageProcessor"]) _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.owlv2"].append("Owlv2ImageProcessor") _import_structure["models.owlvit"].extend(["OwlViTFeatureExtractor", "OwlViTImageProcessor"]) _import_structure["models.perceiver"].extend(["PerceiverFeatureExtractor", "PerceiverImageProcessor"]) _import_structure["models.pix2struct"].extend(["Pix2StructImageProcessor"]) _import_structure["models.pixtral"].append("PixtralImageProcessor") _import_structure["models.poolformer"].extend(["PoolFormerFeatureExtractor", "PoolFormerImageProcessor"]) _import_structure["models.pvt"].extend(["PvtImageProcessor"]) _import_structure["models.qwen2_vl"].extend(["Qwen2VLImageProcessor"]) _import_structure["models.rt_detr"].extend(["RTDetrImageProcessor"]) _import_structure["models.sam"].extend(["SamImageProcessor"]) _import_structure["models.segformer"].extend(["SegformerFeatureExtractor", "SegformerImageProcessor"]) _import_structure["models.seggpt"].extend(["SegGptImageProcessor"]) _import_structure["models.siglip"].append("SiglipImageProcessor") _import_structure["models.superpoint"].extend(["SuperPointImageProcessor"]) _import_structure["models.swin2sr"].append("Swin2SRImageProcessor") _import_structure["models.tvp"].append("TvpImageProcessor") _import_structure["models.video_llava"].append("VideoLlavaImageProcessor") _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.vitmatte"].append("VitMatteImageProcessor") _import_structure["models.vivit"].append("VivitImageProcessor") _import_structure["models.yolos"].extend(["YolosFeatureExtractor", "YolosImageProcessor"]) _import_structure["models.zoedepth"].append("ZoeDepthImageProcessor") try: if not is_torchvision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: from .utils import dummy_torchvision_objects _import_structure["utils.dummy_torchvision_objects"] = [ name for name in dir(dummy_torchvision_objects) if not name.startswith("_") ] else: _import_structure["image_processing_utils_fast"] = ["BaseImageProcessorFast"] _import_structure["models.deformable_detr"].append("DeformableDetrImageProcessorFast") _import_structure["models.detr"].append("DetrImageProcessorFast") _import_structure["models.pixtral"].append("PixtralImageProcessorFast") _import_structure["models.rt_detr"].append("RTDetrImageProcessorFast") _import_structure["models.vit"].append("ViTImageProcessorFast") # 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["cache_utils"] = [ "Cache", "CacheConfig", "DynamicCache", "EncoderDecoderCache", "HQQQuantizedCache", "HybridCache", "MambaCache", "OffloadedCache", "OffloadedStaticCache", "QuantizedCache", "QuantizedCacheConfig", "QuantoQuantizedCache", "SinkCache", "SlidingWindowCache", "StaticCache", ] _import_structure["data.datasets"] = [ "GlueDataset", "GlueDataTrainingArguments", "LineByLineTextDataset", "LineByLineWithRefDataset", "LineByLineWithSOPTextDataset", "SquadDataset", "SquadDataTrainingArguments", "TextDataset", "TextDatasetForNextSentencePrediction", ] _import_structure["generation"].extend( [ "AlternatingCodebooksLogitsProcessor", "BayesianDetectorConfig", "BayesianDetectorModel", "BeamScorer", "BeamSearchScorer", "ClassifierFreeGuidanceLogitsProcessor", "ConstrainedBeamSearchScorer", "Constraint", "ConstraintListState", "DisjunctiveConstraint", "EncoderNoRepeatNGramLogitsProcessor", "EncoderRepetitionPenaltyLogitsProcessor", "EosTokenCriteria", "EpsilonLogitsWarper", "EtaLogitsWarper", "ExponentialDecayLengthPenalty", "ForcedBOSTokenLogitsProcessor", "ForcedEOSTokenLogitsProcessor", "GenerationMixin", "HammingDiversityLogitsProcessor", "InfNanRemoveLogitsProcessor", "LogitNormalization", "LogitsProcessor", "LogitsProcessorList", "LogitsWarper", "MaxLengthCriteria", "MaxTimeCriteria", "MinLengthLogitsProcessor", "MinNewTokensLengthLogitsProcessor", "MinPLogitsWarper", "NoBadWordsLogitsProcessor", "NoRepeatNGramLogitsProcessor", "PhrasalConstraint", "PrefixConstrainedLogitsProcessor", "RepetitionPenaltyLogitsProcessor", "SequenceBiasLogitsProcessor", "StoppingCriteria", "StoppingCriteriaList", "StopStringCriteria", "SuppressTokensAtBeginLogitsProcessor", "SuppressTokensLogitsProcessor", "SynthIDTextWatermarkDetector", "SynthIDTextWatermarkingConfig", "SynthIDTextWatermarkLogitsProcessor", "TemperatureLogitsWarper", "TopKLogitsWarper", "TopPLogitsWarper", "TypicalLogitsWarper", "UnbatchedClassifierFreeGuidanceLogitsProcessor", "WatermarkDetector", "WatermarkLogitsProcessor", "WhisperTimeStampLogitsProcessor", ] ) # PyTorch domain libraries integration _import_structure["integrations.executorch"] = [ "TorchExportableModuleWithStaticCache", "convert_and_export_with_cache", ] _import_structure["modeling_flash_attention_utils"] = [] _import_structure["modeling_outputs"] = [] _import_structure["modeling_rope_utils"] = ["ROPE_INIT_FUNCTIONS"] _import_structure["modeling_utils"] = ["PreTrainedModel"] # PyTorch models structure _import_structure["models.albert"].extend( [ "AlbertForMaskedLM", "AlbertForMultipleChoice", "AlbertForPreTraining", "AlbertForQuestionAnswering", "AlbertForSequenceClassification", "AlbertForTokenClassification", "AlbertModel", "AlbertPreTrainedModel", "load_tf_weights_in_albert", ] ) _import_structure["models.align"].extend( [ "AlignModel", "AlignPreTrainedModel", "AlignTextModel", "AlignVisionModel", ] ) _import_structure["models.altclip"].extend( [ "AltCLIPModel", "AltCLIPPreTrainedModel", "AltCLIPTextModel", "AltCLIPVisionModel", ] ) _import_structure["models.audio_spectrogram_transformer"].extend( [ "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_MAPPING", "MODEL_FOR_IMAGE_SEGMENTATION_MAPPING", "MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING", "MODEL_FOR_IMAGE_TO_IMAGE_MAPPING", "MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING", "MODEL_FOR_KEYPOINT_DETECTION_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_TIME_SERIES_CLASSIFICATION_MAPPING", "MODEL_FOR_TIME_SERIES_REGRESSION_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", "AutoModelForImageTextToText", "AutoModelForImageToImage", "AutoModelForInstanceSegmentation", "AutoModelForKeypointDetection", "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( [ "AutoformerForPrediction", "AutoformerModel", "AutoformerPreTrainedModel", ] ) _import_structure["models.bark"].extend( [ "BarkCausalModel", "BarkCoarseModel", "BarkFineModel", "BarkModel", "BarkPreTrainedModel", "BarkSemanticModel", ] ) _import_structure["models.bart"].extend( [ "BartForCausalLM", "BartForConditionalGeneration", "BartForQuestionAnswering", "BartForSequenceClassification", "BartModel", "BartPretrainedModel", "BartPreTrainedModel", "PretrainedBartModel", ] ) _import_structure["models.beit"].extend( [ "BeitBackbone", "BeitForImageClassification", "BeitForMaskedImageModeling", "BeitForSemanticSegmentation", "BeitModel", "BeitPreTrainedModel", ] ) _import_structure["models.bert"].extend( [ "BertForMaskedLM", "BertForMultipleChoice", "BertForNextSentencePrediction", "BertForPreTraining", "BertForQuestionAnswering", "BertForSequenceClassification", "BertForTokenClassification", "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( [ "BigBirdForCausalLM", "BigBirdForMaskedLM", "BigBirdForMultipleChoice", "BigBirdForPreTraining", "BigBirdForQuestionAnswering", "BigBirdForSequenceClassification", "BigBirdForTokenClassification", "BigBirdModel", "BigBirdPreTrainedModel", "load_tf_weights_in_big_bird", ] ) _import_structure["models.bigbird_pegasus"].extend( [ "BigBirdPegasusForCausalLM", "BigBirdPegasusForConditionalGeneration", "BigBirdPegasusForQuestionAnswering", "BigBirdPegasusForSequenceClassification", "BigBirdPegasusModel", "BigBirdPegasusPreTrainedModel", ] ) _import_structure["models.biogpt"].extend( [ "BioGptForCausalLM", "BioGptForSequenceClassification", "BioGptForTokenClassification", "BioGptModel", "BioGptPreTrainedModel", ] ) _import_structure["models.bit"].extend( [ "BitBackbone", "BitForImageClassification", "BitModel", "BitPreTrainedModel", ] ) _import_structure["models.blenderbot"].extend( [ "BlenderbotForCausalLM", "BlenderbotForConditionalGeneration", "BlenderbotModel", "BlenderbotPreTrainedModel", ] ) _import_structure["models.blenderbot_small"].extend( [ "BlenderbotSmallForCausalLM", "BlenderbotSmallForConditionalGeneration", "BlenderbotSmallModel", "BlenderbotSmallPreTrainedModel", ] ) _import_structure["models.blip"].extend( [ "BlipForConditionalGeneration", "BlipForImageTextRetrieval", "BlipForQuestionAnswering", "BlipModel", "BlipPreTrainedModel", "BlipTextModel", "BlipVisionModel", ] ) _import_structure["models.blip_2"].extend( [ "Blip2ForConditionalGeneration", "Blip2ForImageTextRetrieval", "Blip2Model", "Blip2PreTrainedModel", "Blip2QFormerModel", "Blip2TextModelWithProjection", "Blip2VisionModel", "Blip2VisionModelWithProjection", ] ) _import_structure["models.bloom"].extend( [ "BloomForCausalLM", "BloomForQuestionAnswering", "BloomForSequenceClassification", "BloomForTokenClassification", "BloomModel", "BloomPreTrainedModel", ] ) _import_structure["models.bridgetower"].extend( [ "BridgeTowerForContrastiveLearning", "BridgeTowerForImageAndTextRetrieval", "BridgeTowerForMaskedLM", "BridgeTowerModel", "BridgeTowerPreTrainedModel", ] ) _import_structure["models.bros"].extend( [ "BrosForTokenClassification", "BrosModel", "BrosPreTrainedModel", "BrosProcessor", "BrosSpadeEEForTokenClassification", "BrosSpadeELForTokenClassification", ] ) _import_structure["models.camembert"].extend( [ "CamembertForCausalLM", "CamembertForMaskedLM", "CamembertForMultipleChoice", "CamembertForQuestionAnswering", "CamembertForSequenceClassification", "CamembertForTokenClassification", "CamembertModel", "CamembertPreTrainedModel", ] ) _import_structure["models.canine"].extend( [ "CanineForMultipleChoice", "CanineForQuestionAnswering", "CanineForSequenceClassification", "CanineForTokenClassification", "CanineModel", "CaninePreTrainedModel", "load_tf_weights_in_canine", ] ) _import_structure["models.chameleon"].extend( [ "ChameleonForConditionalGeneration", "ChameleonModel", "ChameleonPreTrainedModel", "ChameleonProcessor", "ChameleonVQVAE", ] ) _import_structure["models.chinese_clip"].extend( [ "ChineseCLIPModel", "ChineseCLIPPreTrainedModel", "ChineseCLIPTextModel", "ChineseCLIPVisionModel", ] ) _import_structure["models.clap"].extend( [ "ClapAudioModel", "ClapAudioModelWithProjection", "ClapFeatureExtractor", "ClapModel", "ClapPreTrainedModel", "ClapTextModel", "ClapTextModelWithProjection", ] ) _import_structure["models.clip"].extend( [ "CLIPForImageClassification", "CLIPModel", "CLIPPreTrainedModel", "CLIPTextModel", "CLIPTextModelWithProjection", "CLIPVisionModel", "CLIPVisionModelWithProjection", ] ) _import_structure["models.clipseg"].extend( [ "CLIPSegForImageSegmentation", "CLIPSegModel", "CLIPSegPreTrainedModel", "CLIPSegTextModel", "CLIPSegVisionModel", ] ) _import_structure["models.clvp"].extend( [ "ClvpDecoder", "ClvpEncoder", "ClvpForCausalLM", "ClvpModel", "ClvpModelForConditionalGeneration", "ClvpPreTrainedModel", ] ) _import_structure["models.codegen"].extend( [ "CodeGenForCausalLM", "CodeGenModel", "CodeGenPreTrainedModel", ] ) _import_structure["models.cohere"].extend(["CohereForCausalLM", "CohereModel", "CoherePreTrainedModel"]) _import_structure["models.conditional_detr"].extend( [ "ConditionalDetrForObjectDetection", "ConditionalDetrForSegmentation", "ConditionalDetrModel", "ConditionalDetrPreTrainedModel", ] ) _import_structure["models.convbert"].extend( [ "ConvBertForMaskedLM", "ConvBertForMultipleChoice", "ConvBertForQuestionAnswering", "ConvBertForSequenceClassification", "ConvBertForTokenClassification", "ConvBertModel", "ConvBertPreTrainedModel", "load_tf_weights_in_convbert", ] ) _import_structure["models.convnext"].extend( [ "ConvNextBackbone", "ConvNextForImageClassification", "ConvNextModel", "ConvNextPreTrainedModel", ] ) _import_structure["models.convnextv2"].extend( [ "ConvNextV2Backbone", "ConvNextV2ForImageClassification", "ConvNextV2Model", "ConvNextV2PreTrainedModel", ] ) _import_structure["models.cpmant"].extend( [ "CpmAntForCausalLM", "CpmAntModel", "CpmAntPreTrainedModel", ] ) _import_structure["models.ctrl"].extend( [ "CTRLForSequenceClassification", "CTRLLMHeadModel", "CTRLModel", "CTRLPreTrainedModel", ] ) _import_structure["models.cvt"].extend( [ "CvtForImageClassification", "CvtModel", "CvtPreTrainedModel", ] ) _import_structure["models.dac"].extend( [ "DacModel", "DacPreTrainedModel", ] ) _import_structure["models.data2vec"].extend( [ "Data2VecAudioForAudioFrameClassification", "Data2VecAudioForCTC", "Data2VecAudioForSequenceClassification", "Data2VecAudioForXVector", "Data2VecAudioModel", "Data2VecAudioPreTrainedModel", "Data2VecTextForCausalLM", "Data2VecTextForMaskedLM", "Data2VecTextForMultipleChoice", "Data2VecTextForQuestionAnswering", "Data2VecTextForSequenceClassification", "Data2VecTextForTokenClassification", "Data2VecTextModel", "Data2VecTextPreTrainedModel", "Data2VecVisionForImageClassification", "Data2VecVisionForSemanticSegmentation", "Data2VecVisionModel", "Data2VecVisionPreTrainedModel", ] ) _import_structure["models.dbrx"].extend( [ "DbrxForCausalLM", "DbrxModel", "DbrxPreTrainedModel", ] ) _import_structure["models.deberta"].extend( [ "DebertaForMaskedLM", "DebertaForQuestionAnswering", "DebertaForSequenceClassification", "DebertaForTokenClassification", "DebertaModel", "DebertaPreTrainedModel", ] ) _import_structure["models.deberta_v2"].extend( [ "DebertaV2ForMaskedLM", "DebertaV2ForMultipleChoice", "DebertaV2ForQuestionAnswering", "DebertaV2ForSequenceClassification", "DebertaV2ForTokenClassification", "DebertaV2Model", "DebertaV2PreTrainedModel", ] ) _import_structure["models.decision_transformer"].extend( [ "DecisionTransformerGPT2Model", "DecisionTransformerGPT2PreTrainedModel", "DecisionTransformerModel", "DecisionTransformerPreTrainedModel", ] ) _import_structure["models.deformable_detr"].extend( [ "DeformableDetrForObjectDetection", "DeformableDetrModel", "DeformableDetrPreTrainedModel", ] ) _import_structure["models.deit"].extend( [ "DeiTForImageClassification", "DeiTForImageClassificationWithTeacher", "DeiTForMaskedImageModeling", "DeiTModel", "DeiTPreTrainedModel", ] ) _import_structure["models.deprecated.deta"].extend( [ "DetaForObjectDetection", "DetaModel", "DetaPreTrainedModel", ] ) _import_structure["models.deprecated.efficientformer"].extend( [ "EfficientFormerForImageClassification", "EfficientFormerForImageClassificationWithTeacher", "EfficientFormerModel", "EfficientFormerPreTrainedModel", ] ) _import_structure["models.deprecated.ernie_m"].extend( [ "ErnieMForInformationExtraction", "ErnieMForMultipleChoice", "ErnieMForQuestionAnswering", "ErnieMForSequenceClassification", "ErnieMForTokenClassification", "ErnieMModel", "ErnieMPreTrainedModel", ] ) _import_structure["models.deprecated.gptsan_japanese"].extend( [ "GPTSanJapaneseForConditionalGeneration", "GPTSanJapaneseModel", "GPTSanJapanesePreTrainedModel", ] ) _import_structure["models.deprecated.graphormer"].extend( [ "GraphormerForGraphClassification", "GraphormerModel", "GraphormerPreTrainedModel", ] ) _import_structure["models.deprecated.jukebox"].extend( [ "JukeboxModel", "JukeboxPreTrainedModel", "JukeboxPrior", "JukeboxVQVAE", ] ) _import_structure["models.deprecated.mctct"].extend( [ "MCTCTForCTC", "MCTCTModel", "MCTCTPreTrainedModel", ] ) _import_structure["models.deprecated.mega"].extend( [ "MegaForCausalLM", "MegaForMaskedLM", "MegaForMultipleChoice", "MegaForQuestionAnswering", "MegaForSequenceClassification", "MegaForTokenClassification", "MegaModel", "MegaPreTrainedModel", ] ) _import_structure["models.deprecated.mmbt"].extend(["MMBTForClassification", "MMBTModel", "ModalEmbeddings"]) _import_structure["models.deprecated.nat"].extend( [ "NatBackbone", "NatForImageClassification", "NatModel", "NatPreTrainedModel", ] ) _import_structure["models.deprecated.nezha"].extend( [ "NezhaForMaskedLM", "NezhaForMultipleChoice", "NezhaForNextSentencePrediction", "NezhaForPreTraining", "NezhaForQuestionAnswering", "NezhaForSequenceClassification", "NezhaForTokenClassification", "NezhaModel", "NezhaPreTrainedModel", ] ) _import_structure["models.deprecated.open_llama"].extend( [ "OpenLlamaForCausalLM", "OpenLlamaForSequenceClassification", "OpenLlamaModel", "OpenLlamaPreTrainedModel", ] ) _import_structure["models.deprecated.qdqbert"].extend( [ "QDQBertForMaskedLM", "QDQBertForMultipleChoice", "QDQBertForNextSentencePrediction", "QDQBertForQuestionAnswering", "QDQBertForSequenceClassification", "QDQBertForTokenClassification", "QDQBertLMHeadModel", "QDQBertModel", "QDQBertPreTrainedModel", "load_tf_weights_in_qdqbert", ] ) _import_structure["models.deprecated.realm"].extend( [ "RealmEmbedder", "RealmForOpenQA", "RealmKnowledgeAugEncoder", "RealmPreTrainedModel", "RealmReader", "RealmRetriever", "RealmScorer", "load_tf_weights_in_realm", ] ) _import_structure["models.deprecated.retribert"].extend( [ "RetriBertModel", "RetriBertPreTrainedModel", ] ) _import_structure["models.deprecated.speech_to_text_2"].extend( ["Speech2Text2ForCausalLM", "Speech2Text2PreTrainedModel"] ) _import_structure["models.deprecated.trajectory_transformer"].extend( [ "TrajectoryTransformerModel", "TrajectoryTransformerPreTrainedModel", ] ) _import_structure["models.deprecated.transfo_xl"].extend( [ "AdaptiveEmbedding", "TransfoXLForSequenceClassification", "TransfoXLLMHeadModel", "TransfoXLModel", "TransfoXLPreTrainedModel", "load_tf_weights_in_transfo_xl", ] ) _import_structure["models.deprecated.tvlt"].extend( [ "TvltForAudioVisualClassification", "TvltForPreTraining", "TvltModel", "TvltPreTrainedModel", ] ) _import_structure["models.deprecated.van"].extend( [ "VanForImageClassification", "VanModel", "VanPreTrainedModel", ] ) _import_structure["models.deprecated.vit_hybrid"].extend( [ "ViTHybridForImageClassification", "ViTHybridModel", "ViTHybridPreTrainedModel", ] ) _import_structure["models.deprecated.xlm_prophetnet"].extend( [ "XLMProphetNetDecoder", "XLMProphetNetEncoder", "XLMProphetNetForCausalLM", "XLMProphetNetForConditionalGeneration", "XLMProphetNetModel", "XLMProphetNetPreTrainedModel", ] ) _import_structure["models.depth_anything"].extend( [ "DepthAnythingForDepthEstimation", "DepthAnythingPreTrainedModel", ] ) _import_structure["models.detr"].extend( [ "DetrForObjectDetection", "DetrForSegmentation", "DetrModel", "DetrPreTrainedModel", ] ) _import_structure["models.dinat"].extend( [ "DinatBackbone", "DinatForImageClassification", "DinatModel", "DinatPreTrainedModel", ] ) _import_structure["models.dinov2"].extend( [ "Dinov2Backbone", "Dinov2ForImageClassification", "Dinov2Model", "Dinov2PreTrainedModel", ] ) _import_structure["models.distilbert"].extend( [ "DistilBertForMaskedLM", "DistilBertForMultipleChoice", "DistilBertForQuestionAnswering", "DistilBertForSequenceClassification", "DistilBertForTokenClassification", "DistilBertModel", "DistilBertPreTrainedModel", ] ) _import_structure["models.donut"].extend( [ "DonutSwinModel", "DonutSwinPreTrainedModel", ] ) _import_structure["models.dpr"].extend( [ "DPRContextEncoder", "DPRPretrainedContextEncoder", "DPRPreTrainedModel", "DPRPretrainedQuestionEncoder", "DPRPretrainedReader", "DPRQuestionEncoder", "DPRReader", ] ) _import_structure["models.dpt"].extend( [ "DPTForDepthEstimation", "DPTForSemanticSegmentation", "DPTModel", "DPTPreTrainedModel", ] ) _import_structure["models.efficientnet"].extend( [ "EfficientNetForImageClassification", "EfficientNetModel", "EfficientNetPreTrainedModel", ] ) _import_structure["models.electra"].extend( [ "ElectraForCausalLM", "ElectraForMaskedLM", "ElectraForMultipleChoice", "ElectraForPreTraining", "ElectraForQuestionAnswering", "ElectraForSequenceClassification", "ElectraForTokenClassification", "ElectraModel", "ElectraPreTrainedModel", "load_tf_weights_in_electra", ] ) _import_structure["models.encodec"].extend( [ "EncodecModel", "EncodecPreTrainedModel", ] ) _import_structure["models.encoder_decoder"].append("EncoderDecoderModel") _import_structure["models.ernie"].extend( [ "ErnieForCausalLM", "ErnieForMaskedLM", "ErnieForMultipleChoice", "ErnieForNextSentencePrediction", "ErnieForPreTraining", "ErnieForQuestionAnswering", "ErnieForSequenceClassification", "ErnieForTokenClassification", "ErnieModel", "ErniePreTrainedModel", ] ) _import_structure["models.esm"].extend( [ "EsmFoldPreTrainedModel", "EsmForMaskedLM", "EsmForProteinFolding", "EsmForSequenceClassification", "EsmForTokenClassification", "EsmModel", "EsmPreTrainedModel", ] ) _import_structure["models.falcon"].extend( [ "FalconForCausalLM", "FalconForQuestionAnswering", "FalconForSequenceClassification", "FalconForTokenClassification", "FalconModel", "FalconPreTrainedModel", ] ) _import_structure["models.falcon_mamba"].extend( [ "FalconMambaForCausalLM", "FalconMambaModel", "FalconMambaPreTrainedModel", ] ) _import_structure["models.fastspeech2_conformer"].extend( [ "FastSpeech2ConformerHifiGan", "FastSpeech2ConformerModel", "FastSpeech2ConformerPreTrainedModel", "FastSpeech2ConformerWithHifiGan", ] ) _import_structure["models.flaubert"].extend( [ "FlaubertForMultipleChoice", "FlaubertForQuestionAnswering", "FlaubertForQuestionAnsweringSimple", "FlaubertForSequenceClassification", "FlaubertForTokenClassification", "FlaubertModel", "FlaubertPreTrainedModel", "FlaubertWithLMHeadModel", ] ) _import_structure["models.flava"].extend( [ "FlavaForPreTraining", "FlavaImageCodebook", "FlavaImageModel", "FlavaModel", "FlavaMultimodalModel", "FlavaPreTrainedModel", "FlavaTextModel", ] ) _import_structure["models.fnet"].extend( [ "FNetForMaskedLM", "FNetForMultipleChoice", "FNetForNextSentencePrediction", "FNetForPreTraining", "FNetForQuestionAnswering", "FNetForSequenceClassification", "FNetForTokenClassification", "FNetModel", "FNetPreTrainedModel", ] ) _import_structure["models.focalnet"].extend( [ "FocalNetBackbone", "FocalNetForImageClassification", "FocalNetForMaskedImageModeling", "FocalNetModel", "FocalNetPreTrainedModel", ] ) _import_structure["models.fsmt"].extend(["FSMTForConditionalGeneration", "FSMTModel", "PretrainedFSMTModel"]) _import_structure["models.funnel"].extend( [ "FunnelBaseModel", "FunnelForMaskedLM", "FunnelForMultipleChoice", "FunnelForPreTraining", "FunnelForQuestionAnswering", "FunnelForSequenceClassification", "FunnelForTokenClassification", "FunnelModel", "FunnelPreTrainedModel", "load_tf_weights_in_funnel", ] ) _import_structure["models.fuyu"].extend(["FuyuForCausalLM", "FuyuPreTrainedModel"]) _import_structure["models.gemma"].extend( [ "GemmaForCausalLM", "GemmaForSequenceClassification", "GemmaForTokenClassification", "GemmaModel", "GemmaPreTrainedModel", ] ) _import_structure["models.gemma2"].extend( [ "Gemma2ForCausalLM", "Gemma2ForSequenceClassification", "Gemma2ForTokenClassification", "Gemma2Model", "Gemma2PreTrainedModel", ] ) _import_structure["models.git"].extend( [ "GitForCausalLM", "GitModel", "GitPreTrainedModel", "GitVisionModel", ] ) _import_structure["models.glm"].extend( [ "GlmForCausalLM", "GlmForSequenceClassification", "GlmForTokenClassification", "GlmModel", "GlmPreTrainedModel", ] ) _import_structure["models.glpn"].extend( [ "GLPNForDepthEstimation", "GLPNModel", "GLPNPreTrainedModel", ] ) _import_structure["models.gpt2"].extend( [ "GPT2DoubleHeadsModel", "GPT2ForQuestionAnswering", "GPT2ForSequenceClassification", "GPT2ForTokenClassification", "GPT2LMHeadModel", "GPT2Model", "GPT2PreTrainedModel", "load_tf_weights_in_gpt2", ] ) _import_structure["models.gpt_bigcode"].extend( [ "GPTBigCodeForCausalLM", "GPTBigCodeForSequenceClassification", "GPTBigCodeForTokenClassification", "GPTBigCodeModel", "GPTBigCodePreTrainedModel", ] ) _import_structure["models.gpt_neo"].extend( [ "GPTNeoForCausalLM", "GPTNeoForQuestionAnswering", "GPTNeoForSequenceClassification", "GPTNeoForTokenClassification", "GPTNeoModel", "GPTNeoPreTrainedModel", "load_tf_weights_in_gpt_neo", ] ) _import_structure["models.gpt_neox"].extend( [ "GPTNeoXForCausalLM", "GPTNeoXForQuestionAnswering", "GPTNeoXForSequenceClassification", "GPTNeoXForTokenClassification", "GPTNeoXModel", "GPTNeoXPreTrainedModel", ] ) _import_structure["models.gpt_neox_japanese"].extend( [ "GPTNeoXJapaneseForCausalLM", "GPTNeoXJapaneseModel", "GPTNeoXJapanesePreTrainedModel", ] ) _import_structure["models.gptj"].extend( [ "GPTJForCausalLM", "GPTJForQuestionAnswering", "GPTJForSequenceClassification", "GPTJModel", "GPTJPreTrainedModel", ] ) _import_structure["models.granite"].extend( [ "GraniteForCausalLM", "GraniteModel", "GranitePreTrainedModel", ] ) _import_structure["models.granitemoe"].extend( [ "GraniteMoeForCausalLM", "GraniteMoeModel", "GraniteMoePreTrainedModel", ] ) _import_structure["models.grounding_dino"].extend( [ "GroundingDinoForObjectDetection", "GroundingDinoModel", "GroundingDinoPreTrainedModel", ] ) _import_structure["models.groupvit"].extend( [ "GroupViTModel", "GroupViTPreTrainedModel", "GroupViTTextModel", "GroupViTVisionModel", ] ) _import_structure["models.hiera"].extend( [ "HieraBackbone", "HieraForImageClassification", "HieraForPreTraining", "HieraModel", "HieraPreTrainedModel", ] ) _import_structure["models.hubert"].extend( [ "HubertForCTC", "HubertForSequenceClassification", "HubertModel", "HubertPreTrainedModel", ] ) _import_structure["models.ibert"].extend( [ "IBertForMaskedLM", "IBertForMultipleChoice", "IBertForQuestionAnswering", "IBertForSequenceClassification", "IBertForTokenClassification", "IBertModel", "IBertPreTrainedModel", ] ) _import_structure["models.idefics"].extend( [ "IdeficsForVisionText2Text", "IdeficsModel", "IdeficsPreTrainedModel", "IdeficsProcessor", ] ) _import_structure["models.idefics2"].extend( [ "Idefics2ForConditionalGeneration", "Idefics2Model", "Idefics2PreTrainedModel", "Idefics2Processor", ] ) _import_structure["models.idefics3"].extend( [ "Idefics3ForConditionalGeneration", "Idefics3Model", "Idefics3PreTrainedModel", "Idefics3Processor", ] ) _import_structure["models.ijepa"].extend( [ "IJepaForImageClassification", "IJepaModel", "IJepaPreTrainedModel", ] ) _import_structure["models.imagegpt"].extend( [ "ImageGPTForCausalImageModeling", "ImageGPTForImageClassification", "ImageGPTModel", "ImageGPTPreTrainedModel", "load_tf_weights_in_imagegpt", ] ) _import_structure["models.informer"].extend( [ "InformerForPrediction", "InformerModel", "InformerPreTrainedModel", ] ) _import_structure["models.instructblip"].extend( [ "InstructBlipForConditionalGeneration", "InstructBlipPreTrainedModel", "InstructBlipQFormerModel", "InstructBlipVisionModel", ] ) _import_structure["models.instructblipvideo"].extend( [ "InstructBlipVideoForConditionalGeneration", "InstructBlipVideoPreTrainedModel", "InstructBlipVideoQFormerModel", "InstructBlipVideoVisionModel", ] ) _import_structure["models.jamba"].extend( [ "JambaForCausalLM", "JambaForSequenceClassification", "JambaModel", "JambaPreTrainedModel", ] ) _import_structure["models.jetmoe"].extend( [ "JetMoeForCausalLM", "JetMoeForSequenceClassification", "JetMoeModel", "JetMoePreTrainedModel", ] ) _import_structure["models.kosmos2"].extend( [ "Kosmos2ForConditionalGeneration", "Kosmos2Model", "Kosmos2PreTrainedModel", ] ) _import_structure["models.layoutlm"].extend( [ "LayoutLMForMaskedLM", "LayoutLMForQuestionAnswering", "LayoutLMForSequenceClassification", "LayoutLMForTokenClassification", "LayoutLMModel", "LayoutLMPreTrainedModel", ] ) _import_structure["models.layoutlmv2"].extend( [ "LayoutLMv2ForQuestionAnswering", "LayoutLMv2ForSequenceClassification", "LayoutLMv2ForTokenClassification", "LayoutLMv2Model", "LayoutLMv2PreTrainedModel", ] ) _import_structure["models.layoutlmv3"].extend( [ "LayoutLMv3ForQuestionAnswering", "LayoutLMv3ForSequenceClassification", "LayoutLMv3ForTokenClassification", "LayoutLMv3Model", "LayoutLMv3PreTrainedModel", ] ) _import_structure["models.led"].extend( [ "LEDForConditionalGeneration", "LEDForQuestionAnswering", "LEDForSequenceClassification", "LEDModel", "LEDPreTrainedModel", ] ) _import_structure["models.levit"].extend( [ "LevitForImageClassification", "LevitForImageClassificationWithTeacher", "LevitModel", "LevitPreTrainedModel", ] ) _import_structure["models.lilt"].extend( [ "LiltForQuestionAnswering", "LiltForSequenceClassification", "LiltForTokenClassification", "LiltModel", "LiltPreTrainedModel", ] ) _import_structure["models.llama"].extend( [ "LlamaForCausalLM", "LlamaForQuestionAnswering", "LlamaForSequenceClassification", "LlamaForTokenClassification", "LlamaModel", "LlamaPreTrainedModel", ] ) _import_structure["models.llava"].extend( [ "LlavaForConditionalGeneration", "LlavaPreTrainedModel", ] ) _import_structure["models.llava_next"].extend( [ "LlavaNextForConditionalGeneration", "LlavaNextPreTrainedModel", ] ) _import_structure["models.llava_next_video"].extend( [ "LlavaNextVideoForConditionalGeneration", "LlavaNextVideoPreTrainedModel", ] ) _import_structure["models.llava_onevision"].extend( [ "LlavaOnevisionForConditionalGeneration", "LlavaOnevisionPreTrainedModel", ] ) _import_structure["models.longformer"].extend( [ "LongformerForMaskedLM", "LongformerForMultipleChoice", "LongformerForQuestionAnswering", "LongformerForSequenceClassification", "LongformerForTokenClassification", "LongformerModel", "LongformerPreTrainedModel", ] ) _import_structure["models.longt5"].extend( [ "LongT5EncoderModel", "LongT5ForConditionalGeneration", "LongT5Model", "LongT5PreTrainedModel", ] ) _import_structure["models.luke"].extend( [ "LukeForEntityClassification", "LukeForEntityPairClassification", "LukeForEntitySpanClassification", "LukeForMaskedLM", "LukeForMultipleChoice", "LukeForQuestionAnswering", "LukeForSequenceClassification", "LukeForTokenClassification", "LukeModel", "LukePreTrainedModel", ] ) _import_structure["models.lxmert"].extend( [ "LxmertEncoder", "LxmertForPreTraining", "LxmertForQuestionAnswering", "LxmertModel", "LxmertPreTrainedModel", "LxmertVisualFeatureEncoder", ] ) _import_structure["models.m2m_100"].extend( [ "M2M100ForConditionalGeneration", "M2M100Model", "M2M100PreTrainedModel", ] ) _import_structure["models.mamba"].extend( [ "MambaForCausalLM", "MambaModel", "MambaPreTrainedModel", ] ) _import_structure["models.mamba2"].extend( [ "Mamba2ForCausalLM", "Mamba2Model", "Mamba2PreTrainedModel", ] ) _import_structure["models.marian"].extend( ["MarianForCausalLM", "MarianModel", "MarianMTModel", "MarianPreTrainedModel"] ) _import_structure["models.markuplm"].extend( [ "MarkupLMForQuestionAnswering", "MarkupLMForSequenceClassification", "MarkupLMForTokenClassification", "MarkupLMModel", "MarkupLMPreTrainedModel", ] ) _import_structure["models.mask2former"].extend( [ "Mask2FormerForUniversalSegmentation", "Mask2FormerModel", "Mask2FormerPreTrainedModel", ] ) _import_structure["models.maskformer"].extend( [ "MaskFormerForInstanceSegmentation", "MaskFormerModel", "MaskFormerPreTrainedModel", "MaskFormerSwinBackbone", ] ) _import_structure["models.mbart"].extend( [ "MBartForCausalLM", "MBartForConditionalGeneration", "MBartForQuestionAnswering", "MBartForSequenceClassification", "MBartModel", "MBartPreTrainedModel", ] ) _import_structure["models.megatron_bert"].extend( [ "MegatronBertForCausalLM", "MegatronBertForMaskedLM", "MegatronBertForMultipleChoice", "MegatronBertForNextSentencePrediction", "MegatronBertForPreTraining", "MegatronBertForQuestionAnswering", "MegatronBertForSequenceClassification", "MegatronBertForTokenClassification", "MegatronBertModel", "MegatronBertPreTrainedModel", ] ) _import_structure["models.mgp_str"].extend( [ "MgpstrForSceneTextRecognition", "MgpstrModel", "MgpstrPreTrainedModel", ] ) _import_structure["models.mimi"].extend( [ "MimiModel", "MimiPreTrainedModel", ] ) _import_structure["models.mistral"].extend( [ "MistralForCausalLM", "MistralForQuestionAnswering", "MistralForSequenceClassification", "MistralForTokenClassification", "MistralModel", "MistralPreTrainedModel", ] ) _import_structure["models.mixtral"].extend( [ "MixtralForCausalLM", "MixtralForQuestionAnswering", "MixtralForSequenceClassification", "MixtralForTokenClassification", "MixtralModel", "MixtralPreTrainedModel", ] ) _import_structure["models.mllama"].extend( [ "MllamaForCausalLM", "MllamaForConditionalGeneration", "MllamaPreTrainedModel", "MllamaProcessor", "MllamaTextModel", "MllamaVisionModel", ] ) _import_structure["models.mobilebert"].extend( [ "MobileBertForMaskedLM", "MobileBertForMultipleChoice", "MobileBertForNextSentencePrediction", "MobileBertForPreTraining", "MobileBertForQuestionAnswering", "MobileBertForSequenceClassification", "MobileBertForTokenClassification", "MobileBertModel", "MobileBertPreTrainedModel", "load_tf_weights_in_mobilebert", ] ) _import_structure["models.mobilenet_v1"].extend( [ "MobileNetV1ForImageClassification", "MobileNetV1Model", "MobileNetV1PreTrainedModel", "load_tf_weights_in_mobilenet_v1", ] ) _import_structure["models.mobilenet_v2"].extend( [ "MobileNetV2ForImageClassification", "MobileNetV2ForSemanticSegmentation", "MobileNetV2Model", "MobileNetV2PreTrainedModel", "load_tf_weights_in_mobilenet_v2", ] ) _import_structure["models.mobilevit"].extend( [ "MobileViTForImageClassification", "MobileViTForSemanticSegmentation", "MobileViTModel", "MobileViTPreTrainedModel", ] ) _import_structure["models.mobilevitv2"].extend( [ "MobileViTV2ForImageClassification", "MobileViTV2ForSemanticSegmentation", "MobileViTV2Model", "MobileViTV2PreTrainedModel", ] ) _import_structure["models.moshi"].extend( [ "MoshiForCausalLM", "MoshiForConditionalGeneration", "MoshiModel", "MoshiPreTrainedModel", ] ) _import_structure["models.mpnet"].extend( [ "MPNetForMaskedLM", "MPNetForMultipleChoice", "MPNetForQuestionAnswering", "MPNetForSequenceClassification", "MPNetForTokenClassification", "MPNetModel", "MPNetPreTrainedModel", ] ) _import_structure["models.mpt"].extend( [ "MptForCausalLM", "MptForQuestionAnswering", "MptForSequenceClassification", "MptForTokenClassification", "MptModel", "MptPreTrainedModel", ] ) _import_structure["models.mra"].extend( [ "MraForMaskedLM", "MraForMultipleChoice", "MraForQuestionAnswering", "MraForSequenceClassification", "MraForTokenClassification", "MraModel", "MraPreTrainedModel", ] ) _import_structure["models.mt5"].extend( [ "MT5EncoderModel", "MT5ForConditionalGeneration", "MT5ForQuestionAnswering", "MT5ForSequenceClassification", "MT5ForTokenClassification", "MT5Model", "MT5PreTrainedModel", ] ) _import_structure["models.musicgen"].extend( [ "MusicgenForCausalLM", "MusicgenForConditionalGeneration", "MusicgenModel", "MusicgenPreTrainedModel", "MusicgenProcessor", ] ) _import_structure["models.musicgen_melody"].extend( [ "MusicgenMelodyForCausalLM", "MusicgenMelodyForConditionalGeneration", "MusicgenMelodyModel", "MusicgenMelodyPreTrainedModel", ] ) _import_structure["models.mvp"].extend( [ "MvpForCausalLM", "MvpForConditionalGeneration", "MvpForQuestionAnswering", "MvpForSequenceClassification", "MvpModel", "MvpPreTrainedModel", ] ) _import_structure["models.nemotron"].extend( [ "NemotronForCausalLM", "NemotronForQuestionAnswering", "NemotronForSequenceClassification", "NemotronForTokenClassification", "NemotronModel", "NemotronPreTrainedModel", ] ) _import_structure["models.nllb_moe"].extend( [ "NllbMoeForConditionalGeneration", "NllbMoeModel", "NllbMoePreTrainedModel", "NllbMoeSparseMLP", "NllbMoeTop2Router", ] ) _import_structure["models.nystromformer"].extend( [ "NystromformerForMaskedLM", "NystromformerForMultipleChoice", "NystromformerForQuestionAnswering", "NystromformerForSequenceClassification", "NystromformerForTokenClassification", "NystromformerModel", "NystromformerPreTrainedModel", ] ) _import_structure["models.olmo"].extend( [ "OlmoForCausalLM", "OlmoModel", "OlmoPreTrainedModel", ] ) _import_structure["models.olmo2"].extend( [ "Olmo2ForCausalLM", "Olmo2Model", "Olmo2PreTrainedModel", ] ) _import_structure["models.olmoe"].extend( [ "OlmoeForCausalLM", "OlmoeModel", "OlmoePreTrainedModel", ] ) _import_structure["models.omdet_turbo"].extend( [ "OmDetTurboForObjectDetection", "OmDetTurboPreTrainedModel", ] ) _import_structure["models.oneformer"].extend( [ "OneFormerForUniversalSegmentation", "OneFormerModel", "OneFormerPreTrainedModel", ] ) _import_structure["models.openai"].extend( [ "OpenAIGPTDoubleHeadsModel", "OpenAIGPTForSequenceClassification", "OpenAIGPTLMHeadModel", "OpenAIGPTModel", "OpenAIGPTPreTrainedModel", "load_tf_weights_in_openai_gpt", ] ) _import_structure["models.opt"].extend( [ "OPTForCausalLM", "OPTForQuestionAnswering", "OPTForSequenceClassification", "OPTModel", "OPTPreTrainedModel", ] ) _import_structure["models.owlv2"].extend( [ "Owlv2ForObjectDetection", "Owlv2Model", "Owlv2PreTrainedModel", "Owlv2TextModel", "Owlv2VisionModel", ] ) _import_structure["models.owlvit"].extend( [ "OwlViTForObjectDetection", "OwlViTModel", "OwlViTPreTrainedModel", "OwlViTTextModel", "OwlViTVisionModel", ] ) _import_structure["models.paligemma"].extend( [ "PaliGemmaForConditionalGeneration", "PaliGemmaPreTrainedModel", "PaliGemmaProcessor", ] ) _import_structure["models.patchtsmixer"].extend( [ "PatchTSMixerForPrediction", "PatchTSMixerForPretraining", "PatchTSMixerForRegression", "PatchTSMixerForTimeSeriesClassification", "PatchTSMixerModel", "PatchTSMixerPreTrainedModel", ] ) _import_structure["models.patchtst"].extend( [ "PatchTSTForClassification", "PatchTSTForPrediction", "PatchTSTForPretraining", "PatchTSTForRegression", "PatchTSTModel", "PatchTSTPreTrainedModel", ] ) _import_structure["models.pegasus"].extend( [ "PegasusForCausalLM", "PegasusForConditionalGeneration", "PegasusModel", "PegasusPreTrainedModel", ] ) _import_structure["models.pegasus_x"].extend( [ "PegasusXForConditionalGeneration", "PegasusXModel", "PegasusXPreTrainedModel", ] ) _import_structure["models.perceiver"].extend( [ "PerceiverForImageClassificationConvProcessing", "PerceiverForImageClassificationFourier", "PerceiverForImageClassificationLearned", "PerceiverForMaskedLM", "PerceiverForMultimodalAutoencoding", "PerceiverForOpticalFlow", "PerceiverForSequenceClassification", "PerceiverModel", "PerceiverPreTrainedModel", ] ) _import_structure["models.persimmon"].extend( [ "PersimmonForCausalLM", "PersimmonForSequenceClassification", "PersimmonForTokenClassification", "PersimmonModel", "PersimmonPreTrainedModel", ] ) _import_structure["models.phi"].extend( [ "PhiForCausalLM", "PhiForSequenceClassification", "PhiForTokenClassification", "PhiModel", "PhiPreTrainedModel", ] ) _import_structure["models.phi3"].extend( [ "Phi3ForCausalLM", "Phi3ForSequenceClassification", "Phi3ForTokenClassification", "Phi3Model", "Phi3PreTrainedModel", ] ) _import_structure["models.phimoe"].extend( [ "PhimoeForCausalLM", "PhimoeForSequenceClassification", "PhimoeModel", "PhimoePreTrainedModel", ] ) _import_structure["models.pix2struct"].extend( [ "Pix2StructForConditionalGeneration", "Pix2StructPreTrainedModel", "Pix2StructTextModel", "Pix2StructVisionModel", ] ) _import_structure["models.pixtral"].extend(["PixtralPreTrainedModel", "PixtralVisionModel"]) _import_structure["models.plbart"].extend( [ "PLBartForCausalLM", "PLBartForConditionalGeneration", "PLBartForSequenceClassification", "PLBartModel", "PLBartPreTrainedModel", ] ) _import_structure["models.poolformer"].extend( [ "PoolFormerForImageClassification", "PoolFormerModel", "PoolFormerPreTrainedModel", ] ) _import_structure["models.pop2piano"].extend( [ "Pop2PianoForConditionalGeneration", "Pop2PianoPreTrainedModel", ] ) _import_structure["models.prophetnet"].extend( [ "ProphetNetDecoder", "ProphetNetEncoder", "ProphetNetForCausalLM", "ProphetNetForConditionalGeneration", "ProphetNetModel", "ProphetNetPreTrainedModel", ] ) _import_structure["models.pvt"].extend( [ "PvtForImageClassification", "PvtModel", "PvtPreTrainedModel", ] ) _import_structure["models.pvt_v2"].extend( [ "PvtV2Backbone", "PvtV2ForImageClassification", "PvtV2Model", "PvtV2PreTrainedModel", ] ) _import_structure["models.qwen2"].extend( [ "Qwen2ForCausalLM", "Qwen2ForQuestionAnswering", "Qwen2ForSequenceClassification", "Qwen2ForTokenClassification", "Qwen2Model", "Qwen2PreTrainedModel", ] ) _import_structure["models.qwen2_audio"].extend( [ "Qwen2AudioEncoder", "Qwen2AudioForConditionalGeneration", "Qwen2AudioPreTrainedModel", ] ) _import_structure["models.qwen2_moe"].extend( [ "Qwen2MoeForCausalLM", "Qwen2MoeForQuestionAnswering", "Qwen2MoeForSequenceClassification", "Qwen2MoeForTokenClassification", "Qwen2MoeModel", "Qwen2MoePreTrainedModel", ] ) _import_structure["models.qwen2_vl"].extend( [ "Qwen2VLForConditionalGeneration", "Qwen2VLModel", "Qwen2VLPreTrainedModel", ] ) _import_structure["models.rag"].extend( [ "RagModel", "RagPreTrainedModel", "RagSequenceForGeneration", "RagTokenForGeneration", ] ) _import_structure["models.recurrent_gemma"].extend( [ "RecurrentGemmaForCausalLM", "RecurrentGemmaModel", "RecurrentGemmaPreTrainedModel", ] ) _import_structure["models.reformer"].extend( [ "ReformerForMaskedLM", "ReformerForQuestionAnswering", "ReformerForSequenceClassification", "ReformerModel", "ReformerModelWithLMHead", "ReformerPreTrainedModel", ] ) _import_structure["models.regnet"].extend( [ "RegNetForImageClassification", "RegNetModel", "RegNetPreTrainedModel", ] ) _import_structure["models.rembert"].extend( [ "RemBertForCausalLM", "RemBertForMaskedLM", "RemBertForMultipleChoice", "RemBertForQuestionAnswering", "RemBertForSequenceClassification", "RemBertForTokenClassification", "RemBertModel", "RemBertPreTrainedModel", "load_tf_weights_in_rembert", ] ) _import_structure["models.resnet"].extend( [ "ResNetBackbone", "ResNetForImageClassification", "ResNetModel", "ResNetPreTrainedModel", ] ) _import_structure["models.roberta"].extend( [ "RobertaForCausalLM", "RobertaForMaskedLM", "RobertaForMultipleChoice", "RobertaForQuestionAnswering", "RobertaForSequenceClassification", "RobertaForTokenClassification", "RobertaModel", "RobertaPreTrainedModel", ] ) _import_structure["models.roberta_prelayernorm"].extend( [ "RobertaPreLayerNormForCausalLM", "RobertaPreLayerNormForMaskedLM", "RobertaPreLayerNormForMultipleChoice", "RobertaPreLayerNormForQuestionAnswering", "RobertaPreLayerNormForSequenceClassification", "RobertaPreLayerNormForTokenClassification", "RobertaPreLayerNormModel", "RobertaPreLayerNormPreTrainedModel", ] ) _import_structure["models.roc_bert"].extend( [ "RoCBertForCausalLM", "RoCBertForMaskedLM", "RoCBertForMultipleChoice", "RoCBertForPreTraining", "RoCBertForQuestionAnswering", "RoCBertForSequenceClassification", "RoCBertForTokenClassification", "RoCBertModel", "RoCBertPreTrainedModel", "load_tf_weights_in_roc_bert", ] ) _import_structure["models.roformer"].extend( [ "RoFormerForCausalLM", "RoFormerForMaskedLM", "RoFormerForMultipleChoice", "RoFormerForQuestionAnswering", "RoFormerForSequenceClassification", "RoFormerForTokenClassification", "RoFormerModel", "RoFormerPreTrainedModel", "load_tf_weights_in_roformer", ] ) _import_structure["models.rt_detr"].extend( [ "RTDetrForObjectDetection", "RTDetrModel", "RTDetrPreTrainedModel", "RTDetrResNetBackbone", "RTDetrResNetPreTrainedModel", ] ) _import_structure["models.rwkv"].extend( [ "RwkvForCausalLM", "RwkvModel", "RwkvPreTrainedModel", ] ) _import_structure["models.sam"].extend( [ "SamModel", "SamPreTrainedModel", ] ) _import_structure["models.seamless_m4t"].extend( [ "SeamlessM4TCodeHifiGan", "SeamlessM4TForSpeechToSpeech", "SeamlessM4TForSpeechToText", "SeamlessM4TForTextToSpeech", "SeamlessM4TForTextToText", "SeamlessM4THifiGan", "SeamlessM4TModel", "SeamlessM4TPreTrainedModel", "SeamlessM4TTextToUnitForConditionalGeneration", "SeamlessM4TTextToUnitModel", ] ) _import_structure["models.seamless_m4t_v2"].extend( [ "SeamlessM4Tv2ForSpeechToSpeech", "SeamlessM4Tv2ForSpeechToText", "SeamlessM4Tv2ForTextToSpeech", "SeamlessM4Tv2ForTextToText", "SeamlessM4Tv2Model", "SeamlessM4Tv2PreTrainedModel", ] ) _import_structure["models.segformer"].extend( [ "SegformerDecodeHead", "SegformerForImageClassification", "SegformerForSemanticSegmentation", "SegformerModel", "SegformerPreTrainedModel", ] ) _import_structure["models.seggpt"].extend( [ "SegGptForImageSegmentation", "SegGptModel", "SegGptPreTrainedModel", ] ) _import_structure["models.sew"].extend( [ "SEWForCTC", "SEWForSequenceClassification", "SEWModel", "SEWPreTrainedModel", ] ) _import_structure["models.sew_d"].extend( [ "SEWDForCTC", "SEWDForSequenceClassification", "SEWDModel", "SEWDPreTrainedModel", ] ) _import_structure["models.siglip"].extend( [ "SiglipForImageClassification", "SiglipModel", "SiglipPreTrainedModel", "SiglipTextModel", "SiglipVisionModel", ] ) _import_structure["models.speech_encoder_decoder"].extend(["SpeechEncoderDecoderModel"]) _import_structure["models.speech_to_text"].extend( [ "Speech2TextForConditionalGeneration", "Speech2TextModel", "Speech2TextPreTrainedModel", ] ) _import_structure["models.speecht5"].extend( [ "SpeechT5ForSpeechToSpeech", "SpeechT5ForSpeechToText", "SpeechT5ForTextToSpeech", "SpeechT5HifiGan", "SpeechT5Model", "SpeechT5PreTrainedModel", ] ) _import_structure["models.splinter"].extend( [ "SplinterForPreTraining", "SplinterForQuestionAnswering", "SplinterModel", "SplinterPreTrainedModel", ] ) _import_structure["models.squeezebert"].extend( [ "SqueezeBertForMaskedLM", "SqueezeBertForMultipleChoice", "SqueezeBertForQuestionAnswering", "SqueezeBertForSequenceClassification", "SqueezeBertForTokenClassification", "SqueezeBertModel", "SqueezeBertPreTrainedModel", ] ) _import_structure["models.stablelm"].extend( [ "StableLmForCausalLM", "StableLmForSequenceClassification", "StableLmForTokenClassification", "StableLmModel", "StableLmPreTrainedModel", ] ) _import_structure["models.starcoder2"].extend( [ "Starcoder2ForCausalLM", "Starcoder2ForSequenceClassification", "Starcoder2ForTokenClassification", "Starcoder2Model", "Starcoder2PreTrainedModel", ] ) _import_structure["models.superpoint"].extend( [ "SuperPointForKeypointDetection", "SuperPointPreTrainedModel", ] ) _import_structure["models.swiftformer"].extend( [ "SwiftFormerForImageClassification", "SwiftFormerModel", "SwiftFormerPreTrainedModel", ] ) _import_structure["models.swin"].extend( [ "SwinBackbone", "SwinForImageClassification", "SwinForMaskedImageModeling", "SwinModel", "SwinPreTrainedModel", ] ) _import_structure["models.swin2sr"].extend( [ "Swin2SRForImageSuperResolution", "Swin2SRModel", "Swin2SRPreTrainedModel", ] ) _import_structure["models.swinv2"].extend( [ "Swinv2Backbone", "Swinv2ForImageClassification", "Swinv2ForMaskedImageModeling", "Swinv2Model", "Swinv2PreTrainedModel", ] ) _import_structure["models.switch_transformers"].extend( [ "SwitchTransformersEncoderModel", "SwitchTransformersForConditionalGeneration", "SwitchTransformersModel", "SwitchTransformersPreTrainedModel", "SwitchTransformersSparseMLP", "SwitchTransformersTop1Router", ] ) _import_structure["models.t5"].extend( [ "T5EncoderModel", "T5ForConditionalGeneration", "T5ForQuestionAnswering", "T5ForSequenceClassification", "T5ForTokenClassification", "T5Model", "T5PreTrainedModel", "load_tf_weights_in_t5", ] ) _import_structure["models.table_transformer"].extend( [ "TableTransformerForObjectDetection", "TableTransformerModel", "TableTransformerPreTrainedModel", ] ) _import_structure["models.tapas"].extend( [ "TapasForMaskedLM", "TapasForQuestionAnswering", "TapasForSequenceClassification", "TapasModel", "TapasPreTrainedModel", "load_tf_weights_in_tapas", ] ) _import_structure["models.time_series_transformer"].extend( [ "TimeSeriesTransformerForPrediction", "TimeSeriesTransformerModel", "TimeSeriesTransformerPreTrainedModel", ] ) _import_structure["models.timesformer"].extend( [ "TimesformerForVideoClassification", "TimesformerModel", "TimesformerPreTrainedModel", ] ) _import_structure["models.timm_backbone"].extend(["TimmBackbone"]) _import_structure["models.trocr"].extend( [ "TrOCRForCausalLM", "TrOCRPreTrainedModel", ] ) _import_structure["models.tvp"].extend( [ "TvpForVideoGrounding", "TvpModel", "TvpPreTrainedModel", ] ) _import_structure["models.udop"].extend( [ "UdopEncoderModel", "UdopForConditionalGeneration", "UdopModel", "UdopPreTrainedModel", ], ) _import_structure["models.umt5"].extend( [ "UMT5EncoderModel", "UMT5ForConditionalGeneration", "UMT5ForQuestionAnswering", "UMT5ForSequenceClassification", "UMT5ForTokenClassification", "UMT5Model", "UMT5PreTrainedModel", ] ) _import_structure["models.unispeech"].extend( [ "UniSpeechForCTC", "UniSpeechForPreTraining", "UniSpeechForSequenceClassification", "UniSpeechModel", "UniSpeechPreTrainedModel", ] ) _import_structure["models.unispeech_sat"].extend( [ "UniSpeechSatForAudioFrameClassification", "UniSpeechSatForCTC", "UniSpeechSatForPreTraining", "UniSpeechSatForSequenceClassification", "UniSpeechSatForXVector", "UniSpeechSatModel", "UniSpeechSatPreTrainedModel", ] ) _import_structure["models.univnet"].extend( [ "UnivNetModel", ] ) _import_structure["models.upernet"].extend( [ "UperNetForSemanticSegmentation", "UperNetPreTrainedModel", ] ) _import_structure["models.video_llava"].extend( [ "VideoLlavaForConditionalGeneration", "VideoLlavaPreTrainedModel", "VideoLlavaProcessor", ] ) _import_structure["models.videomae"].extend( [ "VideoMAEForPreTraining", "VideoMAEForVideoClassification", "VideoMAEModel", "VideoMAEPreTrainedModel", ] ) _import_structure["models.vilt"].extend( [ "ViltForImageAndTextRetrieval", "ViltForImagesAndTextClassification", "ViltForMaskedLM", "ViltForQuestionAnswering", "ViltForTokenClassification", "ViltModel", "ViltPreTrainedModel", ] ) _import_structure["models.vipllava"].extend( [ "VipLlavaForConditionalGeneration", "VipLlavaPreTrainedModel", ] ) _import_structure["models.vision_encoder_decoder"].extend(["VisionEncoderDecoderModel"]) _import_structure["models.vision_text_dual_encoder"].extend(["VisionTextDualEncoderModel"]) _import_structure["models.visual_bert"].extend( [ "VisualBertForMultipleChoice", "VisualBertForPreTraining", "VisualBertForQuestionAnswering", "VisualBertForRegionToPhraseAlignment", "VisualBertForVisualReasoning", "VisualBertModel", "VisualBertPreTrainedModel", ] ) _import_structure["models.vit"].extend( [ "ViTForImageClassification", "ViTForMaskedImageModeling", "ViTModel", "ViTPreTrainedModel", ] ) _import_structure["models.vit_mae"].extend( [ "ViTMAEForPreTraining", "ViTMAEModel", "ViTMAEPreTrainedModel", ] ) _import_structure["models.vit_msn"].extend( [ "ViTMSNForImageClassification", "ViTMSNModel", "ViTMSNPreTrainedModel", ] ) _import_structure["models.vitdet"].extend( [ "VitDetBackbone", "VitDetModel", "VitDetPreTrainedModel", ] ) _import_structure["models.vitmatte"].extend( [ "VitMatteForImageMatting", "VitMattePreTrainedModel", ] ) _import_structure["models.vits"].extend( [ "VitsModel", "VitsPreTrainedModel", ] ) _import_structure["models.vivit"].extend( [ "VivitForVideoClassification", "VivitModel", "VivitPreTrainedModel", ] ) _import_structure["models.wav2vec2"].extend( [ "Wav2Vec2ForAudioFrameClassification", "Wav2Vec2ForCTC", "Wav2Vec2ForMaskedLM", "Wav2Vec2ForPreTraining", "Wav2Vec2ForSequenceClassification", "Wav2Vec2ForXVector", "Wav2Vec2Model", "Wav2Vec2PreTrainedModel", ] ) _import_structure["models.wav2vec2_bert"].extend( [ "Wav2Vec2BertForAudioFrameClassification", "Wav2Vec2BertForCTC", "Wav2Vec2BertForSequenceClassification", "Wav2Vec2BertForXVector", "Wav2Vec2BertModel", "Wav2Vec2BertPreTrainedModel", ] ) _import_structure["models.wav2vec2_conformer"].extend( [ "Wav2Vec2ConformerForAudioFrameClassification", "Wav2Vec2ConformerForCTC", "Wav2Vec2ConformerForPreTraining", "Wav2Vec2ConformerForSequenceClassification", "Wav2Vec2ConformerForXVector", "Wav2Vec2ConformerModel", "Wav2Vec2ConformerPreTrainedModel", ] ) _import_structure["models.wavlm"].extend( [ "WavLMForAudioFrameClassification", "WavLMForCTC", "WavLMForSequenceClassification", "WavLMForXVector", "WavLMModel", "WavLMPreTrainedModel", ] ) _import_structure["models.whisper"].extend( [ "WhisperForAudioClassification", "WhisperForCausalLM", "WhisperForConditionalGeneration", "WhisperModel", "WhisperPreTrainedModel", ] ) _import_structure["models.x_clip"].extend( [ "XCLIPModel", "XCLIPPreTrainedModel", "XCLIPTextModel", "XCLIPVisionModel", ] ) _import_structure["models.xglm"].extend( [ "XGLMForCausalLM", "XGLMModel", "XGLMPreTrainedModel", ] ) _import_structure["models.xlm"].extend( [ "XLMForMultipleChoice", "XLMForQuestionAnswering", "XLMForQuestionAnsweringSimple", "XLMForSequenceClassification", "XLMForTokenClassification", "XLMModel", "XLMPreTrainedModel", "XLMWithLMHeadModel", ] ) _import_structure["models.xlm_roberta"].extend( [ "XLMRobertaForCausalLM", "XLMRobertaForMaskedLM", "XLMRobertaForMultipleChoice", "XLMRobertaForQuestionAnswering", "XLMRobertaForSequenceClassification", "XLMRobertaForTokenClassification", "XLMRobertaModel", "XLMRobertaPreTrainedModel", ] ) _import_structure["models.xlm_roberta_xl"].extend( [ "XLMRobertaXLForCausalLM", "XLMRobertaXLForMaskedLM", "XLMRobertaXLForMultipleChoice", "XLMRobertaXLForQuestionAnswering", "XLMRobertaXLForSequenceClassification", "XLMRobertaXLForTokenClassification", "XLMRobertaXLModel", "XLMRobertaXLPreTrainedModel", ] ) _import_structure["models.xlnet"].extend( [ "XLNetForMultipleChoice", "XLNetForQuestionAnswering", "XLNetForQuestionAnsweringSimple", "XLNetForSequenceClassification", "XLNetForTokenClassification", "XLNetLMHeadModel", "XLNetModel", "XLNetPreTrainedModel", "load_tf_weights_in_xlnet", ] ) _import_structure["models.xmod"].extend( [ "XmodForCausalLM", "XmodForMaskedLM", "XmodForMultipleChoice", "XmodForQuestionAnswering", "XmodForSequenceClassification", "XmodForTokenClassification", "XmodModel", "XmodPreTrainedModel", ] ) _import_structure["models.yolos"].extend( [ "YolosForObjectDetection", "YolosModel", "YolosPreTrainedModel", ] ) _import_structure["models.yoso"].extend( [ "YosoForMaskedLM", "YosoForMultipleChoice", "YosoForQuestionAnswering", "YosoForSequenceClassification", "YosoForTokenClassification", "YosoModel", "YosoPreTrainedModel", ] ) _import_structure["models.zamba"].extend( [ "ZambaForCausalLM", "ZambaForSequenceClassification", "ZambaModel", "ZambaPreTrainedModel", ] ) _import_structure["models.zoedepth"].extend( [ "ZoeDepthForDepthEstimation", "ZoeDepthPreTrainedModel", ] ) _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", "get_wsd_schedule", ] _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", ] ) _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( [ "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( [ "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( [ "TFBlipForConditionalGeneration", "TFBlipForImageTextRetrieval", "TFBlipForQuestionAnswering", "TFBlipModel", "TFBlipPreTrainedModel", "TFBlipTextModel", "TFBlipVisionModel", ] ) _import_structure["models.camembert"].extend( [ "TFCamembertForCausalLM", "TFCamembertForMaskedLM", "TFCamembertForMultipleChoice", "TFCamembertForQuestionAnswering", "TFCamembertForSequenceClassification", "TFCamembertForTokenClassification", "TFCamembertModel", "TFCamembertPreTrainedModel", ] ) _import_structure["models.clip"].extend( [ "TFCLIPModel", "TFCLIPPreTrainedModel", "TFCLIPTextModel", "TFCLIPVisionModel", ] ) _import_structure["models.convbert"].extend( [ "TFConvBertForMaskedLM", "TFConvBertForMultipleChoice", "TFConvBertForQuestionAnswering", "TFConvBertForSequenceClassification", "TFConvBertForTokenClassification", "TFConvBertModel", "TFConvBertPreTrainedModel", ] ) _import_structure["models.convnext"].extend( [ "TFConvNextForImageClassification", "TFConvNextModel", "TFConvNextPreTrainedModel", ] ) _import_structure["models.convnextv2"].extend( [ "TFConvNextV2ForImageClassification", "TFConvNextV2Model", "TFConvNextV2PreTrainedModel", ] ) _import_structure["models.ctrl"].extend( [ "TFCTRLForSequenceClassification", "TFCTRLLMHeadModel", "TFCTRLModel", "TFCTRLPreTrainedModel", ] ) _import_structure["models.cvt"].extend( [ "TFCvtForImageClassification", "TFCvtModel", "TFCvtPreTrainedModel", ] ) _import_structure["models.data2vec"].extend( [ "TFData2VecVisionForImageClassification", "TFData2VecVisionForSemanticSegmentation", "TFData2VecVisionModel", "TFData2VecVisionPreTrainedModel", ] ) _import_structure["models.deberta"].extend( [ "TFDebertaForMaskedLM", "TFDebertaForQuestionAnswering", "TFDebertaForSequenceClassification", "TFDebertaForTokenClassification", "TFDebertaModel", "TFDebertaPreTrainedModel", ] ) _import_structure["models.deberta_v2"].extend( [ "TFDebertaV2ForMaskedLM", "TFDebertaV2ForMultipleChoice", "TFDebertaV2ForQuestionAnswering", "TFDebertaV2ForSequenceClassification", "TFDebertaV2ForTokenClassification", "TFDebertaV2Model", "TFDebertaV2PreTrainedModel", ] ) _import_structure["models.deit"].extend( [ "TFDeiTForImageClassification", "TFDeiTForImageClassificationWithTeacher", "TFDeiTForMaskedImageModeling", "TFDeiTModel", "TFDeiTPreTrainedModel", ] ) _import_structure["models.deprecated.efficientformer"].extend( [ "TFEfficientFormerForImageClassification", "TFEfficientFormerForImageClassificationWithTeacher", "TFEfficientFormerModel", "TFEfficientFormerPreTrainedModel", ] ) _import_structure["models.deprecated.transfo_xl"].extend( [ "TFAdaptiveEmbedding", "TFTransfoXLForSequenceClassification", "TFTransfoXLLMHeadModel", "TFTransfoXLMainLayer", "TFTransfoXLModel", "TFTransfoXLPreTrainedModel", ] ) _import_structure["models.distilbert"].extend( [ "TFDistilBertForMaskedLM", "TFDistilBertForMultipleChoice", "TFDistilBertForQuestionAnswering", "TFDistilBertForSequenceClassification", "TFDistilBertForTokenClassification", "TFDistilBertMainLayer", "TFDistilBertModel", "TFDistilBertPreTrainedModel", ] ) _import_structure["models.dpr"].extend( [ "TFDPRContextEncoder", "TFDPRPretrainedContextEncoder", "TFDPRPretrainedQuestionEncoder", "TFDPRPretrainedReader", "TFDPRQuestionEncoder", "TFDPRReader", ] ) _import_structure["models.electra"].extend( [ "TFElectraForMaskedLM", "TFElectraForMultipleChoice", "TFElectraForPreTraining", "TFElectraForQuestionAnswering", "TFElectraForSequenceClassification", "TFElectraForTokenClassification", "TFElectraModel", "TFElectraPreTrainedModel", ] ) _import_structure["models.encoder_decoder"].append("TFEncoderDecoderModel") _import_structure["models.esm"].extend( [ "TFEsmForMaskedLM", "TFEsmForSequenceClassification", "TFEsmForTokenClassification", "TFEsmModel", "TFEsmPreTrainedModel", ] ) _import_structure["models.flaubert"].extend( [ "TFFlaubertForMultipleChoice", "TFFlaubertForQuestionAnsweringSimple", "TFFlaubertForSequenceClassification", "TFFlaubertForTokenClassification", "TFFlaubertModel", "TFFlaubertPreTrainedModel", "TFFlaubertWithLMHeadModel", ] ) _import_structure["models.funnel"].extend( [ "TFFunnelBaseModel", "TFFunnelForMaskedLM", "TFFunnelForMultipleChoice", "TFFunnelForPreTraining", "TFFunnelForQuestionAnswering", "TFFunnelForSequenceClassification", "TFFunnelForTokenClassification", "TFFunnelModel", "TFFunnelPreTrainedModel", ] ) _import_structure["models.gpt2"].extend( [ "TFGPT2DoubleHeadsModel", "TFGPT2ForSequenceClassification", "TFGPT2LMHeadModel", "TFGPT2MainLayer", "TFGPT2Model", "TFGPT2PreTrainedModel", ] ) _import_structure["models.gptj"].extend( [ "TFGPTJForCausalLM", "TFGPTJForQuestionAnswering", "TFGPTJForSequenceClassification", "TFGPTJModel", "TFGPTJPreTrainedModel", ] ) _import_structure["models.groupvit"].extend( [ "TFGroupViTModel", "TFGroupViTPreTrainedModel", "TFGroupViTTextModel", "TFGroupViTVisionModel", ] ) _import_structure["models.hubert"].extend( [ "TFHubertForCTC", "TFHubertModel", "TFHubertPreTrainedModel", ] ) _import_structure["models.idefics"].extend( [ "TFIdeficsForVisionText2Text", "TFIdeficsModel", "TFIdeficsPreTrainedModel", ] ) _import_structure["models.layoutlm"].extend( [ "TFLayoutLMForMaskedLM", "TFLayoutLMForQuestionAnswering", "TFLayoutLMForSequenceClassification", "TFLayoutLMForTokenClassification", "TFLayoutLMMainLayer", "TFLayoutLMModel", "TFLayoutLMPreTrainedModel", ] ) _import_structure["models.layoutlmv3"].extend( [ "TFLayoutLMv3ForQuestionAnswering", "TFLayoutLMv3ForSequenceClassification", "TFLayoutLMv3ForTokenClassification", "TFLayoutLMv3Model", "TFLayoutLMv3PreTrainedModel", ] ) _import_structure["models.led"].extend(["TFLEDForConditionalGeneration", "TFLEDModel", "TFLEDPreTrainedModel"]) _import_structure["models.longformer"].extend( [ "TFLongformerForMaskedLM", "TFLongformerForMultipleChoice", "TFLongformerForQuestionAnswering", "TFLongformerForSequenceClassification", "TFLongformerForTokenClassification", "TFLongformerModel", "TFLongformerPreTrainedModel", ] ) _import_structure["models.lxmert"].extend( [ "TFLxmertForPreTraining", "TFLxmertMainLayer", "TFLxmertModel", "TFLxmertPreTrainedModel", "TFLxmertVisualFeatureEncoder", ] ) _import_structure["models.marian"].extend(["TFMarianModel", "TFMarianMTModel", "TFMarianPreTrainedModel"]) _import_structure["models.mbart"].extend( ["TFMBartForConditionalGeneration", "TFMBartModel", "TFMBartPreTrainedModel"] ) _import_structure["models.mistral"].extend( ["TFMistralForCausalLM", "TFMistralForSequenceClassification", "TFMistralModel", "TFMistralPreTrainedModel"] ) _import_structure["models.mobilebert"].extend( [ "TFMobileBertForMaskedLM", "TFMobileBertForMultipleChoice", "TFMobileBertForNextSentencePrediction", "TFMobileBertForPreTraining", "TFMobileBertForQuestionAnswering", "TFMobileBertForSequenceClassification", "TFMobileBertForTokenClassification", "TFMobileBertMainLayer", "TFMobileBertModel", "TFMobileBertPreTrainedModel", ] ) _import_structure["models.mobilevit"].extend( [ "TFMobileViTForImageClassification", "TFMobileViTForSemanticSegmentation", "TFMobileViTModel", "TFMobileViTPreTrainedModel", ] ) _import_structure["models.mpnet"].extend( [ "TFMPNetForMaskedLM", "TFMPNetForMultipleChoice", "TFMPNetForQuestionAnswering", "TFMPNetForSequenceClassification", "TFMPNetForTokenClassification", "TFMPNetMainLayer", "TFMPNetModel", "TFMPNetPreTrainedModel", ] ) _import_structure["models.mt5"].extend(["TFMT5EncoderModel", "TFMT5ForConditionalGeneration", "TFMT5Model"]) _import_structure["models.openai"].extend( [ "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( [ "TFRegNetForImageClassification", "TFRegNetModel", "TFRegNetPreTrainedModel", ] ) _import_structure["models.rembert"].extend( [ "TFRemBertForCausalLM", "TFRemBertForMaskedLM", "TFRemBertForMultipleChoice", "TFRemBertForQuestionAnswering", "TFRemBertForSequenceClassification", "TFRemBertForTokenClassification", "TFRemBertModel", "TFRemBertPreTrainedModel", ] ) _import_structure["models.resnet"].extend( [ "TFResNetForImageClassification", "TFResNetModel", "TFResNetPreTrainedModel", ] ) _import_structure["models.roberta"].extend( [ "TFRobertaForCausalLM", "TFRobertaForMaskedLM", "TFRobertaForMultipleChoice", "TFRobertaForQuestionAnswering", "TFRobertaForSequenceClassification", "TFRobertaForTokenClassification", "TFRobertaMainLayer", "TFRobertaModel", "TFRobertaPreTrainedModel", ] ) _import_structure["models.roberta_prelayernorm"].extend( [ "TFRobertaPreLayerNormForCausalLM", "TFRobertaPreLayerNormForMaskedLM", "TFRobertaPreLayerNormForMultipleChoice", "TFRobertaPreLayerNormForQuestionAnswering", "TFRobertaPreLayerNormForSequenceClassification", "TFRobertaPreLayerNormForTokenClassification", "TFRobertaPreLayerNormMainLayer", "TFRobertaPreLayerNormModel", "TFRobertaPreLayerNormPreTrainedModel", ] ) _import_structure["models.roformer"].extend( [ "TFRoFormerForCausalLM", "TFRoFormerForMaskedLM", "TFRoFormerForMultipleChoice", "TFRoFormerForQuestionAnswering", "TFRoFormerForSequenceClassification", "TFRoFormerForTokenClassification", "TFRoFormerModel", "TFRoFormerPreTrainedModel", ] ) _import_structure["models.sam"].extend( [ "TFSamModel", "TFSamPreTrainedModel", ] ) _import_structure["models.segformer"].extend( [ "TFSegformerDecodeHead", "TFSegformerForImageClassification", "TFSegformerForSemanticSegmentation", "TFSegformerModel", "TFSegformerPreTrainedModel", ] ) _import_structure["models.speech_to_text"].extend( [ "TFSpeech2TextForConditionalGeneration", "TFSpeech2TextModel", "TFSpeech2TextPreTrainedModel", ] ) _import_structure["models.swiftformer"].extend( [ "TFSwiftFormerForImageClassification", "TFSwiftFormerModel", "TFSwiftFormerPreTrainedModel", ] ) _import_structure["models.swin"].extend( [ "TFSwinForImageClassification", "TFSwinForMaskedImageModeling", "TFSwinModel", "TFSwinPreTrainedModel", ] ) _import_structure["models.t5"].extend( [ "TFT5EncoderModel", "TFT5ForConditionalGeneration", "TFT5Model", "TFT5PreTrainedModel", ] ) _import_structure["models.tapas"].extend( [ "TFTapasForMaskedLM", "TFTapasForQuestionAnswering", "TFTapasForSequenceClassification", "TFTapasModel", "TFTapasPreTrainedModel", ] ) _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( [ "TFWav2Vec2ForCTC", "TFWav2Vec2ForSequenceClassification", "TFWav2Vec2Model", "TFWav2Vec2PreTrainedModel", ] ) _import_structure["models.whisper"].extend( [ "TFWhisperForConditionalGeneration", "TFWhisperModel", "TFWhisperPreTrainedModel", ] ) _import_structure["models.xglm"].extend( [ "TFXGLMForCausalLM", "TFXGLMModel", "TFXGLMPreTrainedModel", ] ) _import_structure["models.xlm"].extend( [ "TFXLMForMultipleChoice", "TFXLMForQuestionAnsweringSimple", "TFXLMForSequenceClassification", "TFXLMForTokenClassification", "TFXLMMainLayer", "TFXLMModel", "TFXLMPreTrainedModel", "TFXLMWithLMHeadModel", ] ) _import_structure["models.xlm_roberta"].extend( [ "TFXLMRobertaForCausalLM", "TFXLMRobertaForMaskedLM", "TFXLMRobertaForMultipleChoice", "TFXLMRobertaForQuestionAnswering", "TFXLMRobertaForSequenceClassification", "TFXLMRobertaForTokenClassification", "TFXLMRobertaModel", "TFXLMRobertaPreTrainedModel", ] ) _import_structure["models.xlnet"].extend( [ "TFXLNetForMultipleChoice", "TFXLNetForQuestionAnsweringSimple", "TFXLNetForSequenceClassification", "TFXLNetForTokenClassification", "TFXLNetLMHeadModel", "TFXLNetMainLayer", "TFXLNetModel", "TFXLNetPreTrainedModel", ] ) _import_structure["optimization_tf"] = [ "AdamWeightDecay", "GradientAccumulator", "WarmUp", "create_optimizer", ] _import_structure["tf_utils"] = [] 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") try: if not is_torchaudio_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: from .utils import ( dummy_torchaudio_objects, ) _import_structure["utils.dummy_torchaudio_objects"] = [ name for name in dir(dummy_torchaudio_objects) if not name.startswith("_") ] else: _import_structure["models.musicgen_melody"].append("MusicgenMelodyFeatureExtractor") _import_structure["models.musicgen_melody"].append("MusicgenMelodyProcessor") # 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["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.dinov2"].extend( [ "FlaxDinov2Model", "FlaxDinov2ForImageClassification", "FlaxDinov2PreTrainedModel", ] ) _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.llama"].extend(["FlaxLlamaForCausalLM", "FlaxLlamaModel", "FlaxLlamaPreTrainedModel"]) _import_structure["models.gemma"].extend(["FlaxGemmaForCausalLM", "FlaxGemmaModel", "FlaxGemmaPreTrainedModel"]) _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.mistral"].extend( [ "FlaxMistralForCausalLM", "FlaxMistralModel", "FlaxMistralPreTrainedModel", ] ) _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( [ "FlaxXLMRobertaForMaskedLM", "FlaxXLMRobertaForMultipleChoice", "FlaxXLMRobertaForQuestionAnswering", "FlaxXLMRobertaForSequenceClassification", "FlaxXLMRobertaForTokenClassification", "FlaxXLMRobertaModel", "FlaxXLMRobertaForCausalLM", "FlaxXLMRobertaPreTrainedModel", ] ) # Direct imports for type-checking if TYPE_CHECKING: # Configuration # Agents from .agents import ( Agent, CodeAgent, HfApiEngine, ManagedAgent, PipelineTool, ReactAgent, ReactCodeAgent, ReactJsonAgent, Tool, Toolbox, ToolCollection, TransformersEngine, launch_gradio_demo, load_tool, stream_to_gradio, tool, ) 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, DataCollatorWithFlattening, 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 CompileConfig, GenerationConfig, TextIteratorStreamer, TextStreamer, WatermarkingConfig from .hf_argparser import HfArgumentParser # Integrations from .integrations import ( is_clearml_available, is_comet_available, is_dvclive_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 AlbertConfig from .models.align import ( AlignConfig, AlignProcessor, AlignTextConfig, AlignVisionConfig, ) from .models.altclip import ( AltCLIPConfig, AltCLIPProcessor, AltCLIPTextConfig, AltCLIPVisionConfig, ) from .models.audio_spectrogram_transformer import ( ASTConfig, ASTFeatureExtractor, ) from .models.auto import ( CONFIG_MAPPING, FEATURE_EXTRACTOR_MAPPING, IMAGE_PROCESSOR_MAPPING, MODEL_NAMES_MAPPING, PROCESSOR_MAPPING, TOKENIZER_MAPPING, AutoConfig, AutoFeatureExtractor, AutoImageProcessor, AutoProcessor, AutoTokenizer, ) from .models.autoformer import ( AutoformerConfig, ) from .models.bark import ( BarkCoarseConfig, BarkConfig, BarkFineConfig, BarkProcessor, BarkSemanticConfig, ) from .models.bart import BartConfig, BartTokenizer from .models.beit import BeitConfig from .models.bert import ( 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 BigBirdConfig from .models.bigbird_pegasus import ( BigBirdPegasusConfig, ) from .models.biogpt import ( BioGptConfig, BioGptTokenizer, ) from .models.bit import BitConfig from .models.blenderbot import ( BlenderbotConfig, BlenderbotTokenizer, ) from .models.blenderbot_small import ( BlenderbotSmallConfig, BlenderbotSmallTokenizer, ) from .models.blip import ( BlipConfig, BlipProcessor, BlipTextConfig, BlipVisionConfig, ) from .models.blip_2 import ( Blip2Config, Blip2Processor, Blip2QFormerConfig, Blip2VisionConfig, ) from .models.bloom import BloomConfig from .models.bridgetower import ( BridgeTowerConfig, BridgeTowerProcessor, BridgeTowerTextConfig, BridgeTowerVisionConfig, ) from .models.bros import ( BrosConfig, BrosProcessor, ) from .models.byt5 import ByT5Tokenizer from .models.camembert import ( CamembertConfig, ) from .models.canine import ( CanineConfig, CanineTokenizer, ) from .models.chameleon import ( ChameleonConfig, ChameleonProcessor, ChameleonVQVAEConfig, ) from .models.chinese_clip import ( ChineseCLIPConfig, ChineseCLIPProcessor, ChineseCLIPTextConfig, ChineseCLIPVisionConfig, ) from .models.clap import ( ClapAudioConfig, ClapConfig, ClapProcessor, ClapTextConfig, ) from .models.clip import ( CLIPConfig, CLIPProcessor, CLIPTextConfig, CLIPTokenizer, CLIPVisionConfig, ) from .models.clipseg import ( CLIPSegConfig, CLIPSegProcessor, CLIPSegTextConfig, CLIPSegVisionConfig, ) from .models.clvp import ( ClvpConfig, ClvpDecoderConfig, ClvpEncoderConfig, ClvpFeatureExtractor, ClvpProcessor, ClvpTokenizer, ) from .models.codegen import ( CodeGenConfig, CodeGenTokenizer, ) from .models.cohere import CohereConfig from .models.conditional_detr import ( ConditionalDetrConfig, ) from .models.convbert import ( ConvBertConfig, ConvBertTokenizer, ) from .models.convnext import ConvNextConfig from .models.convnextv2 import ( ConvNextV2Config, ) from .models.cpmant import ( CpmAntConfig, CpmAntTokenizer, ) from .models.ctrl import ( CTRLConfig, CTRLTokenizer, ) from .models.cvt import CvtConfig from .models.dac import ( DacConfig, DacFeatureExtractor, ) from .models.data2vec import ( Data2VecAudioConfig, Data2VecTextConfig, Data2VecVisionConfig, ) from .models.dbrx import DbrxConfig from .models.deberta import ( DebertaConfig, DebertaTokenizer, ) from .models.deberta_v2 import ( DebertaV2Config, ) from .models.decision_transformer import ( DecisionTransformerConfig, ) from .models.deformable_detr import ( DeformableDetrConfig, ) from .models.deit import DeiTConfig from .models.deprecated.deta import DetaConfig from .models.deprecated.efficientformer import ( EfficientFormerConfig, ) from .models.deprecated.ernie_m import ErnieMConfig from .models.deprecated.gptsan_japanese import ( GPTSanJapaneseConfig, GPTSanJapaneseTokenizer, ) from .models.deprecated.graphormer import GraphormerConfig from .models.deprecated.jukebox import ( JukeboxConfig, JukeboxPriorConfig, JukeboxTokenizer, JukeboxVQVAEConfig, ) from .models.deprecated.mctct import ( MCTCTConfig, MCTCTFeatureExtractor, MCTCTProcessor, ) from .models.deprecated.mega import MegaConfig from .models.deprecated.mmbt import MMBTConfig from .models.deprecated.nat import NatConfig from .models.deprecated.nezha import NezhaConfig from .models.deprecated.open_llama import ( OpenLlamaConfig, ) from .models.deprecated.qdqbert import QDQBertConfig from .models.deprecated.realm import ( RealmConfig, RealmTokenizer, ) from .models.deprecated.retribert import ( RetriBertConfig, RetriBertTokenizer, ) from .models.deprecated.speech_to_text_2 import ( Speech2Text2Config, Speech2Text2Processor, Speech2Text2Tokenizer, ) from .models.deprecated.tapex import TapexTokenizer from .models.deprecated.trajectory_transformer import ( TrajectoryTransformerConfig, ) from .models.deprecated.transfo_xl import ( TransfoXLConfig, TransfoXLCorpus, TransfoXLTokenizer, ) from .models.deprecated.tvlt import ( TvltConfig, TvltFeatureExtractor, TvltProcessor, ) from .models.deprecated.van import VanConfig from .models.deprecated.vit_hybrid import ( ViTHybridConfig, ) from .models.deprecated.xlm_prophetnet import ( XLMProphetNetConfig, ) from .models.depth_anything import DepthAnythingConfig from .models.detr import DetrConfig from .models.dinat import DinatConfig from .models.dinov2 import Dinov2Config from .models.distilbert import ( DistilBertConfig, DistilBertTokenizer, ) from .models.donut import ( DonutProcessor, DonutSwinConfig, ) from .models.dpr import ( DPRConfig, DPRContextEncoderTokenizer, DPRQuestionEncoderTokenizer, DPRReaderOutput, DPRReaderTokenizer, ) from .models.dpt import DPTConfig from .models.efficientnet import ( EfficientNetConfig, ) from .models.electra import ( ElectraConfig, ElectraTokenizer, ) from .models.encodec import ( EncodecConfig, EncodecFeatureExtractor, ) from .models.encoder_decoder import EncoderDecoderConfig from .models.ernie import ErnieConfig from .models.esm import EsmConfig, EsmTokenizer from .models.falcon import FalconConfig from .models.falcon_mamba import FalconMambaConfig from .models.fastspeech2_conformer import ( FastSpeech2ConformerConfig, FastSpeech2ConformerHifiGanConfig, FastSpeech2ConformerTokenizer, FastSpeech2ConformerWithHifiGanConfig, ) from .models.flaubert import FlaubertConfig, FlaubertTokenizer from .models.flava import ( FlavaConfig, FlavaImageCodebookConfig, FlavaImageConfig, FlavaMultimodalConfig, FlavaTextConfig, ) from .models.fnet import FNetConfig from .models.focalnet import FocalNetConfig from .models.fsmt import ( FSMTConfig, FSMTTokenizer, ) from .models.funnel import ( FunnelConfig, FunnelTokenizer, ) from .models.fuyu import FuyuConfig from .models.gemma import GemmaConfig from .models.gemma2 import Gemma2Config from .models.git import ( GitConfig, GitProcessor, GitVisionConfig, ) from .models.glm import GlmConfig from .models.glpn import GLPNConfig from .models.gpt2 import ( GPT2Config, GPT2Tokenizer, ) from .models.gpt_bigcode import ( GPTBigCodeConfig, ) from .models.gpt_neo import GPTNeoConfig from .models.gpt_neox import GPTNeoXConfig from .models.gpt_neox_japanese import ( GPTNeoXJapaneseConfig, ) from .models.gptj import GPTJConfig from .models.granite import GraniteConfig from .models.granitemoe import GraniteMoeConfig from .models.grounding_dino import ( GroundingDinoConfig, GroundingDinoProcessor, ) from .models.groupvit import ( GroupViTConfig, GroupViTTextConfig, GroupViTVisionConfig, ) from .models.herbert import HerbertTokenizer from .models.hiera import HieraConfig from .models.hubert import HubertConfig from .models.ibert import IBertConfig from .models.idefics import ( IdeficsConfig, ) from .models.idefics2 import Idefics2Config from .models.idefics3 import Idefics3Config from .models.ijepa import IJepaConfig from .models.imagegpt import ImageGPTConfig from .models.informer import InformerConfig from .models.instructblip import ( InstructBlipConfig, InstructBlipProcessor, InstructBlipQFormerConfig, InstructBlipVisionConfig, ) from .models.instructblipvideo import ( InstructBlipVideoConfig, InstructBlipVideoProcessor, InstructBlipVideoQFormerConfig, InstructBlipVideoVisionConfig, ) from .models.jamba import JambaConfig from .models.jetmoe import JetMoeConfig from .models.kosmos2 import ( Kosmos2Config, Kosmos2Processor, ) from .models.layoutlm import ( LayoutLMConfig, LayoutLMTokenizer, ) from .models.layoutlmv2 import ( LayoutLMv2Config, LayoutLMv2FeatureExtractor, LayoutLMv2ImageProcessor, LayoutLMv2Processor, LayoutLMv2Tokenizer, ) from .models.layoutlmv3 import ( LayoutLMv3Config, LayoutLMv3FeatureExtractor, LayoutLMv3ImageProcessor, LayoutLMv3Processor, LayoutLMv3Tokenizer, ) from .models.layoutxlm import LayoutXLMProcessor from .models.led import LEDConfig, LEDTokenizer from .models.levit import LevitConfig from .models.lilt import LiltConfig from .models.llama import LlamaConfig from .models.llava import ( LlavaConfig, LlavaProcessor, ) from .models.llava_next import ( LlavaNextConfig, LlavaNextProcessor, ) from .models.llava_next_video import ( LlavaNextVideoConfig, LlavaNextVideoProcessor, ) from .models.llava_onevision import ( LlavaOnevisionConfig, LlavaOnevisionProcessor, ) from .models.longformer import ( LongformerConfig, LongformerTokenizer, ) from .models.longt5 import LongT5Config from .models.luke import ( LukeConfig, LukeTokenizer, ) from .models.lxmert import ( LxmertConfig, LxmertTokenizer, ) from .models.m2m_100 import M2M100Config from .models.mamba import MambaConfig from .models.mamba2 import Mamba2Config from .models.marian import MarianConfig from .models.markuplm import ( MarkupLMConfig, MarkupLMFeatureExtractor, MarkupLMProcessor, MarkupLMTokenizer, ) from .models.mask2former import ( Mask2FormerConfig, ) from .models.maskformer import ( MaskFormerConfig, MaskFormerSwinConfig, ) from .models.mbart import MBartConfig from .models.megatron_bert import ( MegatronBertConfig, ) from .models.mgp_str import ( MgpstrConfig, MgpstrProcessor, MgpstrTokenizer, ) from .models.mimi import ( MimiConfig, ) from .models.mistral import MistralConfig from .models.mixtral import MixtralConfig from .models.mllama import ( MllamaConfig, MllamaProcessor, ) from .models.mobilebert import ( MobileBertConfig, MobileBertTokenizer, ) from .models.mobilenet_v1 import ( MobileNetV1Config, ) from .models.mobilenet_v2 import ( MobileNetV2Config, ) from .models.mobilevit import ( MobileViTConfig, ) from .models.mobilevitv2 import ( MobileViTV2Config, ) from .models.moshi import ( MoshiConfig, MoshiDepthConfig, ) from .models.mpnet import ( MPNetConfig, MPNetTokenizer, ) from .models.mpt import MptConfig from .models.mra import MraConfig from .models.mt5 import MT5Config from .models.musicgen import ( MusicgenConfig, MusicgenDecoderConfig, ) from .models.musicgen_melody import ( MusicgenMelodyConfig, MusicgenMelodyDecoderConfig, ) from .models.mvp import MvpConfig, MvpTokenizer from .models.myt5 import MyT5Tokenizer from .models.nemotron import NemotronConfig from .models.nllb_moe import NllbMoeConfig from .models.nougat import NougatProcessor from .models.nystromformer import ( NystromformerConfig, ) from .models.olmo import OlmoConfig from .models.olmo2 import Olmo2Config from .models.olmoe import OlmoeConfig from .models.omdet_turbo import ( OmDetTurboConfig, OmDetTurboProcessor, ) from .models.oneformer import ( OneFormerConfig, OneFormerProcessor, ) from .models.openai import ( OpenAIGPTConfig, OpenAIGPTTokenizer, ) from .models.opt import OPTConfig from .models.owlv2 import ( Owlv2Config, Owlv2Processor, Owlv2TextConfig, Owlv2VisionConfig, ) from .models.owlvit import ( OwlViTConfig, OwlViTProcessor, OwlViTTextConfig, OwlViTVisionConfig, ) from .models.paligemma import ( PaliGemmaConfig, ) from .models.patchtsmixer import ( PatchTSMixerConfig, ) from .models.patchtst import PatchTSTConfig from .models.pegasus import ( PegasusConfig, PegasusTokenizer, ) from .models.pegasus_x import ( PegasusXConfig, ) from .models.perceiver import ( PerceiverConfig, PerceiverTokenizer, ) from .models.persimmon import ( PersimmonConfig, ) from .models.phi import PhiConfig from .models.phi3 import Phi3Config from .models.phimoe import PhimoeConfig from .models.phobert import PhobertTokenizer from .models.pix2struct import ( Pix2StructConfig, Pix2StructProcessor, Pix2StructTextConfig, Pix2StructVisionConfig, ) from .models.pixtral import ( PixtralProcessor, PixtralVisionConfig, ) from .models.plbart import PLBartConfig from .models.poolformer import ( PoolFormerConfig, ) from .models.pop2piano import ( Pop2PianoConfig, ) from .models.prophetnet import ( ProphetNetConfig, ProphetNetTokenizer, ) from .models.pvt import PvtConfig from .models.pvt_v2 import PvtV2Config from .models.qwen2 import Qwen2Config, Qwen2Tokenizer from .models.qwen2_audio import ( Qwen2AudioConfig, Qwen2AudioEncoderConfig, Qwen2AudioProcessor, ) from .models.qwen2_moe import Qwen2MoeConfig from .models.qwen2_vl import ( Qwen2VLConfig, Qwen2VLProcessor, ) from .models.rag import RagConfig, RagRetriever, RagTokenizer from .models.recurrent_gemma import RecurrentGemmaConfig from .models.reformer import ReformerConfig from .models.regnet import RegNetConfig from .models.rembert import RemBertConfig from .models.resnet import ResNetConfig from .models.roberta import ( RobertaConfig, RobertaTokenizer, ) from .models.roberta_prelayernorm import ( RobertaPreLayerNormConfig, ) from .models.roc_bert import ( RoCBertConfig, RoCBertTokenizer, ) from .models.roformer import ( RoFormerConfig, RoFormerTokenizer, ) from .models.rt_detr import ( RTDetrConfig, RTDetrResNetConfig, ) from .models.rwkv import RwkvConfig from .models.sam import ( SamConfig, SamMaskDecoderConfig, SamProcessor, SamPromptEncoderConfig, SamVisionConfig, ) from .models.seamless_m4t import ( SeamlessM4TConfig, SeamlessM4TFeatureExtractor, SeamlessM4TProcessor, ) from .models.seamless_m4t_v2 import ( SeamlessM4Tv2Config, ) from .models.segformer import SegformerConfig from .models.seggpt import SegGptConfig from .models.sew import SEWConfig from .models.sew_d import SEWDConfig from .models.siglip import ( SiglipConfig, SiglipProcessor, SiglipTextConfig, SiglipVisionConfig, ) from .models.speech_encoder_decoder import SpeechEncoderDecoderConfig from .models.speech_to_text import ( Speech2TextConfig, Speech2TextFeatureExtractor, Speech2TextProcessor, ) from .models.speecht5 import ( SpeechT5Config, SpeechT5FeatureExtractor, SpeechT5HifiGanConfig, SpeechT5Processor, ) from .models.splinter import ( SplinterConfig, SplinterTokenizer, ) from .models.squeezebert import ( SqueezeBertConfig, SqueezeBertTokenizer, ) from .models.stablelm import StableLmConfig from .models.starcoder2 import Starcoder2Config from .models.superpoint import SuperPointConfig from .models.swiftformer import ( SwiftFormerConfig, ) from .models.swin import SwinConfig from .models.swin2sr import Swin2SRConfig from .models.swinv2 import Swinv2Config from .models.switch_transformers import ( SwitchTransformersConfig, ) from .models.t5 import T5Config from .models.table_transformer import ( TableTransformerConfig, ) from .models.tapas import ( TapasConfig, TapasTokenizer, ) from .models.time_series_transformer import ( TimeSeriesTransformerConfig, ) from .models.timesformer import ( TimesformerConfig, ) from .models.timm_backbone import TimmBackboneConfig from .models.trocr import ( TrOCRConfig, TrOCRProcessor, ) from .models.tvp import ( TvpConfig, TvpProcessor, ) from .models.udop import UdopConfig, UdopProcessor from .models.umt5 import UMT5Config from .models.unispeech import ( UniSpeechConfig, ) from .models.unispeech_sat import ( UniSpeechSatConfig, ) from .models.univnet import ( UnivNetConfig, UnivNetFeatureExtractor, ) from .models.upernet import UperNetConfig from .models.video_llava import VideoLlavaConfig from .models.videomae import VideoMAEConfig from .models.vilt import ( ViltConfig, ViltFeatureExtractor, ViltImageProcessor, ViltProcessor, ) from .models.vipllava import ( VipLlavaConfig, ) from .models.vision_encoder_decoder import VisionEncoderDecoderConfig from .models.vision_text_dual_encoder import ( VisionTextDualEncoderConfig, VisionTextDualEncoderProcessor, ) from .models.visual_bert import ( VisualBertConfig, ) from .models.vit import ViTConfig from .models.vit_mae import ViTMAEConfig from .models.vit_msn import ViTMSNConfig from .models.vitdet import VitDetConfig from .models.vitmatte import VitMatteConfig from .models.vits import ( VitsConfig, VitsTokenizer, ) from .models.vivit import VivitConfig from .models.wav2vec2 import ( Wav2Vec2Config, Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor, Wav2Vec2Processor, Wav2Vec2Tokenizer, ) from .models.wav2vec2_bert import ( Wav2Vec2BertConfig, Wav2Vec2BertProcessor, ) from .models.wav2vec2_conformer import ( Wav2Vec2ConformerConfig, ) from .models.wav2vec2_phoneme import Wav2Vec2PhonemeCTCTokenizer from .models.wav2vec2_with_lm import Wav2Vec2ProcessorWithLM from .models.wavlm import WavLMConfig from .models.whisper import ( WhisperConfig, WhisperFeatureExtractor, WhisperProcessor, WhisperTokenizer, ) from .models.x_clip import ( XCLIPConfig, XCLIPProcessor, XCLIPTextConfig, XCLIPVisionConfig, ) from .models.xglm import XGLMConfig from .models.xlm import XLMConfig, XLMTokenizer from .models.xlm_roberta import ( XLMRobertaConfig, ) from .models.xlm_roberta_xl import ( XLMRobertaXLConfig, ) from .models.xlnet import XLNetConfig from .models.xmod import XmodConfig from .models.yolos import YolosConfig from .models.yoso import YosoConfig from .models.zamba import ZambaConfig from .models.zoedepth import ZoeDepthConfig # Pipelines from .pipelines import ( AudioClassificationPipeline, AutomaticSpeechRecognitionPipeline, CsvPipelineDataFormat, DepthEstimationPipeline, DocumentQuestionAnsweringPipeline, FeatureExtractionPipeline, FillMaskPipeline, ImageClassificationPipeline, ImageFeatureExtractionPipeline, ImageSegmentationPipeline, ImageTextToTextPipeline, ImageToImagePipeline, ImageToTextPipeline, JsonPipelineDataFormat, MaskGenerationPipeline, 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, ) # 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_av_available, is_bitsandbytes_available, is_datasets_available, is_faiss_available, is_flax_available, is_keras_nlp_available, is_phonemizer_available, is_psutil_available, is_py3nvml_available, is_pyctcdecode_available, is_sacremoses_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_mlu_available, is_torch_musa_available, is_torch_neuroncore_available, is_torch_npu_available, is_torch_tpu_available, is_torch_xla_available, is_torch_xpu_available, is_torchvision_available, is_vision_available, logging, ) # bitsandbytes config from .utils.quantization_config import ( AqlmConfig, AwqConfig, BitNetConfig, BitsAndBytesConfig, CompressedTensorsConfig, EetqConfig, FbgemmFp8Config, GPTQConfig, HqqConfig, QuantoConfig, TorchAoConfig, ) 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.deprecated.ernie_m import ErnieMTokenizer from .models.deprecated.xlm_prophetnet import XLMProphetNetTokenizer from .models.fnet import FNetTokenizer from .models.gemma import GemmaTokenizer 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 MBartTokenizer from .models.mbart50 import MBart50Tokenizer 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.seamless_m4t import SeamlessM4TTokenizer from .models.siglip import SiglipTokenizer from .models.speech_to_text import Speech2TextTokenizer from .models.speecht5 import SpeechT5Tokenizer from .models.t5 import T5Tokenizer from .models.udop import UdopTokenizer from .models.xglm import XGLMTokenizer 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.cohere import CohereTokenizerFast from .models.convbert import ConvBertTokenizerFast from .models.cpm import CpmTokenizerFast from .models.deberta import DebertaTokenizerFast from .models.deberta_v2 import DebertaV2TokenizerFast from .models.deprecated.realm import RealmTokenizerFast 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.gemma import GemmaTokenizerFast 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.qwen2 import Qwen2TokenizerFast from .models.reformer import ReformerTokenizerFast from .models.rembert import RemBertTokenizerFast from .models.roberta import RobertaTokenizerFast from .models.roformer import RoFormerTokenizerFast from .models.seamless_m4t import SeamlessM4TTokenizerFast from .models.splinter import SplinterTokenizerFast from .models.squeezebert import SqueezeBertTokenizerFast from .models.t5 import T5TokenizerFast from .models.udop import UdopTokenizerFast 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_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_base import ImageProcessingMixin from .image_processing_utils import BaseImageProcessor 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.chameleon import ChameleonImageProcessor 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.deprecated.deta import DetaImageProcessor from .models.deprecated.efficientformer import EfficientFormerImageProcessor from .models.deprecated.tvlt import TvltImageProcessor from .models.deprecated.vit_hybrid import ViTHybridImageProcessor from .models.detr import DetrFeatureExtractor, DetrImageProcessor from .models.donut import DonutFeatureExtractor, DonutImageProcessor from .models.dpt import DPTFeatureExtractor, DPTImageProcessor from .models.efficientnet import EfficientNetImageProcessor from .models.flava import ( FlavaFeatureExtractor, FlavaImageProcessor, FlavaProcessor, ) from .models.fuyu import FuyuImageProcessor, FuyuProcessor from .models.glpn import GLPNFeatureExtractor, GLPNImageProcessor from .models.grounding_dino import GroundingDinoImageProcessor from .models.idefics import IdeficsImageProcessor from .models.idefics2 import Idefics2ImageProcessor from .models.idefics3 import Idefics3ImageProcessor from .models.imagegpt import ImageGPTFeatureExtractor, ImageGPTImageProcessor from .models.instructblipvideo import InstructBlipVideoImageProcessor from .models.layoutlmv2 import ( LayoutLMv2FeatureExtractor, LayoutLMv2ImageProcessor, ) from .models.layoutlmv3 import ( LayoutLMv3FeatureExtractor, LayoutLMv3ImageProcessor, ) from .models.levit import LevitFeatureExtractor, LevitImageProcessor from .models.llava_next import LlavaNextImageProcessor from .models.llava_next_video import LlavaNextVideoImageProcessor from .models.llava_onevision import LlavaOnevisionImageProcessor, LlavaOnevisionVideoProcessor from .models.mask2former import Mask2FormerImageProcessor from .models.maskformer import ( MaskFormerFeatureExtractor, MaskFormerImageProcessor, ) from .models.mllama import MllamaImageProcessor 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.owlv2 import Owlv2ImageProcessor from .models.owlvit import OwlViTFeatureExtractor, OwlViTImageProcessor from .models.perceiver import PerceiverFeatureExtractor, PerceiverImageProcessor from .models.pix2struct import Pix2StructImageProcessor from .models.pixtral import PixtralImageProcessor from .models.poolformer import ( PoolFormerFeatureExtractor, PoolFormerImageProcessor, ) from .models.pvt import PvtImageProcessor from .models.qwen2_vl import Qwen2VLImageProcessor from .models.rt_detr import RTDetrImageProcessor from .models.sam import SamImageProcessor from .models.segformer import SegformerFeatureExtractor, SegformerImageProcessor from .models.seggpt import SegGptImageProcessor from .models.siglip import SiglipImageProcessor from .models.superpoint import SuperPointImageProcessor from .models.swin2sr import Swin2SRImageProcessor from .models.tvp import TvpImageProcessor from .models.video_llava import VideoLlavaImageProcessor from .models.videomae import VideoMAEFeatureExtractor, VideoMAEImageProcessor from .models.vilt import ViltFeatureExtractor, ViltImageProcessor, ViltProcessor from .models.vit import ViTFeatureExtractor, ViTImageProcessor from .models.vitmatte import VitMatteImageProcessor from .models.vivit import VivitImageProcessor from .models.yolos import YolosFeatureExtractor, YolosImageProcessor from .models.zoedepth import ZoeDepthImageProcessor try: if not is_torchvision_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: from .utils.dummy_torchvision_objects import * else: from .image_processing_utils_fast import BaseImageProcessorFast from .models.deformable_detr import DeformableDetrImageProcessorFast from .models.detr import DetrImageProcessorFast from .models.pixtral import PixtralImageProcessorFast from .models.rt_detr import RTDetrImageProcessorFast from .models.vit import ViTImageProcessorFast # 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 .cache_utils import ( Cache, CacheConfig, DynamicCache, EncoderDecoderCache, HQQQuantizedCache, HybridCache, MambaCache, OffloadedCache, OffloadedStaticCache, QuantizedCache, QuantizedCacheConfig, QuantoQuantizedCache, SinkCache, SlidingWindowCache, StaticCache, ) from .data.datasets import ( GlueDataset, GlueDataTrainingArguments, LineByLineTextDataset, LineByLineWithRefDataset, LineByLineWithSOPTextDataset, SquadDataset, SquadDataTrainingArguments, TextDataset, TextDatasetForNextSentencePrediction, ) from .generation import ( AlternatingCodebooksLogitsProcessor, BayesianDetectorConfig, BayesianDetectorModel, BeamScorer, BeamSearchScorer, ClassifierFreeGuidanceLogitsProcessor, ConstrainedBeamSearchScorer, Constraint, ConstraintListState, DisjunctiveConstraint, EncoderNoRepeatNGramLogitsProcessor, EncoderRepetitionPenaltyLogitsProcessor, EosTokenCriteria, EpsilonLogitsWarper, EtaLogitsWarper, ExponentialDecayLengthPenalty, ForcedBOSTokenLogitsProcessor, ForcedEOSTokenLogitsProcessor, GenerationMixin, HammingDiversityLogitsProcessor, InfNanRemoveLogitsProcessor, LogitNormalization, LogitsProcessor, LogitsProcessorList, LogitsWarper, MaxLengthCriteria, MaxTimeCriteria, MinLengthLogitsProcessor, MinNewTokensLengthLogitsProcessor, MinPLogitsWarper, NoBadWordsLogitsProcessor, NoRepeatNGramLogitsProcessor, PhrasalConstraint, PrefixConstrainedLogitsProcessor, RepetitionPenaltyLogitsProcessor, SequenceBiasLogitsProcessor, StoppingCriteria, StoppingCriteriaList, StopStringCriteria, SuppressTokensAtBeginLogitsProcessor, SuppressTokensLogitsProcessor, SynthIDTextWatermarkDetector, SynthIDTextWatermarkingConfig, SynthIDTextWatermarkLogitsProcessor, TemperatureLogitsWarper, TopKLogitsWarper, TopPLogitsWarper, TypicalLogitsWarper, UnbatchedClassifierFreeGuidanceLogitsProcessor, WatermarkDetector, WatermarkLogitsProcessor, WhisperTimeStampLogitsProcessor, ) from .integrations.executorch import ( TorchExportableModuleWithStaticCache, convert_and_export_with_cache, ) from .modeling_rope_utils import ROPE_INIT_FUNCTIONS from .modeling_utils import PreTrainedModel from .models.albert import ( AlbertForMaskedLM, AlbertForMultipleChoice, AlbertForPreTraining, AlbertForQuestionAnswering, AlbertForSequenceClassification, AlbertForTokenClassification, AlbertModel, AlbertPreTrainedModel, load_tf_weights_in_albert, ) from .models.align import ( AlignModel, AlignPreTrainedModel, AlignTextModel, AlignVisionModel, ) from .models.altclip import ( AltCLIPModel, AltCLIPPreTrainedModel, AltCLIPTextModel, AltCLIPVisionModel, ) from .models.audio_spectrogram_transformer import ( 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_MAPPING, MODEL_FOR_IMAGE_SEGMENTATION_MAPPING, MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING, MODEL_FOR_IMAGE_TO_IMAGE_MAPPING, MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING, MODEL_FOR_KEYPOINT_DETECTION_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_TIME_SERIES_CLASSIFICATION_MAPPING, MODEL_FOR_TIME_SERIES_REGRESSION_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, AutoModelForImageTextToText, AutoModelForImageToImage, AutoModelForInstanceSegmentation, AutoModelForKeypointDetection, 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 ( AutoformerForPrediction, AutoformerModel, AutoformerPreTrainedModel, ) from .models.bark import ( BarkCausalModel, BarkCoarseModel, BarkFineModel, BarkModel, BarkPreTrainedModel, BarkSemanticModel, ) from .models.bart import ( BartForCausalLM, BartForConditionalGeneration, BartForQuestionAnswering, BartForSequenceClassification, BartModel, BartPreTrainedModel, BartPretrainedModel, PretrainedBartModel, ) from .models.beit import ( BeitBackbone, BeitForImageClassification, BeitForMaskedImageModeling, BeitForSemanticSegmentation, BeitModel, BeitPreTrainedModel, ) from .models.bert import ( BertForMaskedLM, BertForMultipleChoice, BertForNextSentencePrediction, BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification, BertForTokenClassification, 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 ( BigBirdForCausalLM, BigBirdForMaskedLM, BigBirdForMultipleChoice, BigBirdForPreTraining, BigBirdForQuestionAnswering, BigBirdForSequenceClassification, BigBirdForTokenClassification, BigBirdModel, BigBirdPreTrainedModel, load_tf_weights_in_big_bird, ) from .models.bigbird_pegasus import ( BigBirdPegasusForCausalLM, BigBirdPegasusForConditionalGeneration, BigBirdPegasusForQuestionAnswering, BigBirdPegasusForSequenceClassification, BigBirdPegasusModel, BigBirdPegasusPreTrainedModel, ) from .models.biogpt import ( BioGptForCausalLM, BioGptForSequenceClassification, BioGptForTokenClassification, BioGptModel, BioGptPreTrainedModel, ) from .models.bit import ( BitBackbone, BitForImageClassification, BitModel, BitPreTrainedModel, ) from .models.blenderbot import ( BlenderbotForCausalLM, BlenderbotForConditionalGeneration, BlenderbotModel, BlenderbotPreTrainedModel, ) from .models.blenderbot_small import ( BlenderbotSmallForCausalLM, BlenderbotSmallForConditionalGeneration, BlenderbotSmallModel, BlenderbotSmallPreTrainedModel, ) from .models.blip import ( BlipForConditionalGeneration, BlipForImageTextRetrieval, BlipForQuestionAnswering, BlipModel, BlipPreTrainedModel, BlipTextModel, BlipVisionModel, ) from .models.blip_2 import ( Blip2ForConditionalGeneration, Blip2ForImageTextRetrieval, Blip2Model, Blip2PreTrainedModel, Blip2QFormerModel, Blip2TextModelWithProjection, Blip2VisionModel, Blip2VisionModelWithProjection, ) from .models.bloom import ( BloomForCausalLM, BloomForQuestionAnswering, BloomForSequenceClassification, BloomForTokenClassification, BloomModel, BloomPreTrainedModel, ) from .models.bridgetower import ( BridgeTowerForContrastiveLearning, BridgeTowerForImageAndTextRetrieval, BridgeTowerForMaskedLM, BridgeTowerModel, BridgeTowerPreTrainedModel, ) from .models.bros import ( BrosForTokenClassification, BrosModel, BrosPreTrainedModel, BrosProcessor, BrosSpadeEEForTokenClassification, BrosSpadeELForTokenClassification, ) from .models.camembert import ( CamembertForCausalLM, CamembertForMaskedLM, CamembertForMultipleChoice, CamembertForQuestionAnswering, CamembertForSequenceClassification, CamembertForTokenClassification, CamembertModel, CamembertPreTrainedModel, ) from .models.canine import ( CanineForMultipleChoice, CanineForQuestionAnswering, CanineForSequenceClassification, CanineForTokenClassification, CanineModel, CaninePreTrainedModel, load_tf_weights_in_canine, ) from .models.chameleon import ( ChameleonForConditionalGeneration, ChameleonModel, ChameleonPreTrainedModel, ChameleonProcessor, ChameleonVQVAE, ) from .models.chinese_clip import ( ChineseCLIPModel, ChineseCLIPPreTrainedModel, ChineseCLIPTextModel, ChineseCLIPVisionModel, ) from .models.clap import ( ClapAudioModel, ClapAudioModelWithProjection, ClapFeatureExtractor, ClapModel, ClapPreTrainedModel, ClapTextModel, ClapTextModelWithProjection, ) from .models.clip import ( CLIPForImageClassification, CLIPModel, CLIPPreTrainedModel, CLIPTextModel, CLIPTextModelWithProjection, CLIPVisionModel, CLIPVisionModelWithProjection, ) from .models.clipseg import ( CLIPSegForImageSegmentation, CLIPSegModel, CLIPSegPreTrainedModel, CLIPSegTextModel, CLIPSegVisionModel, ) from .models.clvp import ( ClvpDecoder, ClvpEncoder, ClvpForCausalLM, ClvpModel, ClvpModelForConditionalGeneration, ClvpPreTrainedModel, ) from .models.codegen import ( CodeGenForCausalLM, CodeGenModel, CodeGenPreTrainedModel, ) from .models.cohere import ( CohereForCausalLM, CohereModel, CoherePreTrainedModel, ) from .models.conditional_detr import ( ConditionalDetrForObjectDetection, ConditionalDetrForSegmentation, ConditionalDetrModel, ConditionalDetrPreTrainedModel, ) from .models.convbert import ( ConvBertForMaskedLM, ConvBertForMultipleChoice, ConvBertForQuestionAnswering, ConvBertForSequenceClassification, ConvBertForTokenClassification, ConvBertModel, ConvBertPreTrainedModel, load_tf_weights_in_convbert, ) from .models.convnext import ( ConvNextBackbone, ConvNextForImageClassification, ConvNextModel, ConvNextPreTrainedModel, ) from .models.convnextv2 import ( ConvNextV2Backbone, ConvNextV2ForImageClassification, ConvNextV2Model, ConvNextV2PreTrainedModel, ) from .models.cpmant import ( CpmAntForCausalLM, CpmAntModel, CpmAntPreTrainedModel, ) from .models.ctrl import ( CTRLForSequenceClassification, CTRLLMHeadModel, CTRLModel, CTRLPreTrainedModel, ) from .models.cvt import ( CvtForImageClassification, CvtModel, CvtPreTrainedModel, ) from .models.dac import ( DacModel, DacPreTrainedModel, ) from .models.data2vec import ( Data2VecAudioForAudioFrameClassification, Data2VecAudioForCTC, Data2VecAudioForSequenceClassification, Data2VecAudioForXVector, Data2VecAudioModel, Data2VecAudioPreTrainedModel, Data2VecTextForCausalLM, Data2VecTextForMaskedLM, Data2VecTextForMultipleChoice, Data2VecTextForQuestionAnswering, Data2VecTextForSequenceClassification, Data2VecTextForTokenClassification, Data2VecTextModel, Data2VecTextPreTrainedModel, Data2VecVisionForImageClassification, Data2VecVisionForSemanticSegmentation, Data2VecVisionModel, Data2VecVisionPreTrainedModel, ) # PyTorch model imports from .models.dbrx import ( DbrxForCausalLM, DbrxModel, DbrxPreTrainedModel, ) from .models.deberta import ( DebertaForMaskedLM, DebertaForQuestionAnswering, DebertaForSequenceClassification, DebertaForTokenClassification, DebertaModel, DebertaPreTrainedModel, ) from .models.deberta_v2 import ( DebertaV2ForMaskedLM, DebertaV2ForMultipleChoice, DebertaV2ForQuestionAnswering, DebertaV2ForSequenceClassification, DebertaV2ForTokenClassification, DebertaV2Model, DebertaV2PreTrainedModel, ) from .models.decision_transformer import ( DecisionTransformerGPT2Model, DecisionTransformerGPT2PreTrainedModel, DecisionTransformerModel, DecisionTransformerPreTrainedModel, ) from .models.deformable_detr import ( DeformableDetrForObjectDetection, DeformableDetrModel, DeformableDetrPreTrainedModel, ) from .models.deit import ( DeiTForImageClassification, DeiTForImageClassificationWithTeacher, DeiTForMaskedImageModeling, DeiTModel, DeiTPreTrainedModel, ) from .models.deprecated.deta import ( DetaForObjectDetection, DetaModel, DetaPreTrainedModel, ) from .models.deprecated.efficientformer import ( EfficientFormerForImageClassification, EfficientFormerForImageClassificationWithTeacher, EfficientFormerModel, EfficientFormerPreTrainedModel, ) from .models.deprecated.ernie_m import ( ErnieMForInformationExtraction, ErnieMForMultipleChoice, ErnieMForQuestionAnswering, ErnieMForSequenceClassification, ErnieMForTokenClassification, ErnieMModel, ErnieMPreTrainedModel, ) from .models.deprecated.gptsan_japanese import ( GPTSanJapaneseForConditionalGeneration, GPTSanJapaneseModel, GPTSanJapanesePreTrainedModel, ) from .models.deprecated.graphormer import ( GraphormerForGraphClassification, GraphormerModel, GraphormerPreTrainedModel, ) from .models.deprecated.jukebox import ( JukeboxModel, JukeboxPreTrainedModel, JukeboxPrior, JukeboxVQVAE, ) from .models.deprecated.mctct import ( MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel, ) from .models.deprecated.mega import ( MegaForCausalLM, MegaForMaskedLM, MegaForMultipleChoice, MegaForQuestionAnswering, MegaForSequenceClassification, MegaForTokenClassification, MegaModel, MegaPreTrainedModel, ) from .models.deprecated.mmbt import ( MMBTForClassification, MMBTModel, ModalEmbeddings, ) from .models.deprecated.nat import ( NatBackbone, NatForImageClassification, NatModel, NatPreTrainedModel, ) from .models.deprecated.nezha import ( NezhaForMaskedLM, NezhaForMultipleChoice, NezhaForNextSentencePrediction, NezhaForPreTraining, NezhaForQuestionAnswering, NezhaForSequenceClassification, NezhaForTokenClassification, NezhaModel, NezhaPreTrainedModel, ) from .models.deprecated.open_llama import ( OpenLlamaForCausalLM, OpenLlamaForSequenceClassification, OpenLlamaModel, OpenLlamaPreTrainedModel, ) from .models.deprecated.qdqbert import ( QDQBertForMaskedLM, QDQBertForMultipleChoice, QDQBertForNextSentencePrediction, QDQBertForQuestionAnswering, QDQBertForSequenceClassification, QDQBertForTokenClassification, QDQBertLMHeadModel, QDQBertModel, QDQBertPreTrainedModel, load_tf_weights_in_qdqbert, ) from .models.deprecated.realm import ( RealmEmbedder, RealmForOpenQA, RealmKnowledgeAugEncoder, RealmPreTrainedModel, RealmReader, RealmRetriever, RealmScorer, load_tf_weights_in_realm, ) from .models.deprecated.retribert import ( RetriBertModel, RetriBertPreTrainedModel, ) from .models.deprecated.speech_to_text_2 import ( Speech2Text2ForCausalLM, Speech2Text2PreTrainedModel, ) from .models.deprecated.trajectory_transformer import ( TrajectoryTransformerModel, TrajectoryTransformerPreTrainedModel, ) from .models.deprecated.transfo_xl import ( AdaptiveEmbedding, TransfoXLForSequenceClassification, TransfoXLLMHeadModel, TransfoXLModel, TransfoXLPreTrainedModel, load_tf_weights_in_transfo_xl, ) from .models.deprecated.tvlt import ( TvltForAudioVisualClassification, TvltForPreTraining, TvltModel, TvltPreTrainedModel, ) from .models.deprecated.van import ( VanForImageClassification, VanModel, VanPreTrainedModel, ) from .models.deprecated.vit_hybrid import ( ViTHybridForImageClassification, ViTHybridModel, ViTHybridPreTrainedModel, ) from .models.deprecated.xlm_prophetnet import ( XLMProphetNetDecoder, XLMProphetNetEncoder, XLMProphetNetForCausalLM, XLMProphetNetForConditionalGeneration, XLMProphetNetModel, XLMProphetNetPreTrainedModel, ) from .models.depth_anything import ( DepthAnythingForDepthEstimation, DepthAnythingPreTrainedModel, ) from .models.detr import ( DetrForObjectDetection, DetrForSegmentation, DetrModel, DetrPreTrainedModel, ) from .models.dinat import ( DinatBackbone, DinatForImageClassification, DinatModel, DinatPreTrainedModel, ) from .models.dinov2 import ( Dinov2Backbone, Dinov2ForImageClassification, Dinov2Model, Dinov2PreTrainedModel, ) from .models.distilbert import ( DistilBertForMaskedLM, DistilBertForMultipleChoice, DistilBertForQuestionAnswering, DistilBertForSequenceClassification, DistilBertForTokenClassification, DistilBertModel, DistilBertPreTrainedModel, ) from .models.donut import ( DonutSwinModel, DonutSwinPreTrainedModel, ) from .models.dpr import ( DPRContextEncoder, DPRPretrainedContextEncoder, DPRPreTrainedModel, DPRPretrainedQuestionEncoder, DPRPretrainedReader, DPRQuestionEncoder, DPRReader, ) from .models.dpt import ( DPTForDepthEstimation, DPTForSemanticSegmentation, DPTModel, DPTPreTrainedModel, ) from .models.efficientnet import ( EfficientNetForImageClassification, EfficientNetModel, EfficientNetPreTrainedModel, ) from .models.electra import ( ElectraForCausalLM, ElectraForMaskedLM, ElectraForMultipleChoice, ElectraForPreTraining, ElectraForQuestionAnswering, ElectraForSequenceClassification, ElectraForTokenClassification, ElectraModel, ElectraPreTrainedModel, load_tf_weights_in_electra, ) from .models.encodec import ( EncodecModel, EncodecPreTrainedModel, ) from .models.encoder_decoder import EncoderDecoderModel from .models.ernie import ( ErnieForCausalLM, ErnieForMaskedLM, ErnieForMultipleChoice, ErnieForNextSentencePrediction, ErnieForPreTraining, ErnieForQuestionAnswering, ErnieForSequenceClassification, ErnieForTokenClassification, ErnieModel, ErniePreTrainedModel, ) from .models.esm import ( EsmFoldPreTrainedModel, EsmForMaskedLM, EsmForProteinFolding, EsmForSequenceClassification, EsmForTokenClassification, EsmModel, EsmPreTrainedModel, ) from .models.falcon import ( FalconForCausalLM, FalconForQuestionAnswering, FalconForSequenceClassification, FalconForTokenClassification, FalconModel, FalconPreTrainedModel, ) from .models.falcon_mamba import ( FalconMambaForCausalLM, FalconMambaModel, FalconMambaPreTrainedModel, ) from .models.fastspeech2_conformer import ( FastSpeech2ConformerHifiGan, FastSpeech2ConformerModel, FastSpeech2ConformerPreTrainedModel, FastSpeech2ConformerWithHifiGan, ) from .models.flaubert import ( FlaubertForMultipleChoice, FlaubertForQuestionAnswering, FlaubertForQuestionAnsweringSimple, FlaubertForSequenceClassification, FlaubertForTokenClassification, FlaubertModel, FlaubertPreTrainedModel, FlaubertWithLMHeadModel, ) from .models.flava import ( FlavaForPreTraining, FlavaImageCodebook, FlavaImageModel, FlavaModel, FlavaMultimodalModel, FlavaPreTrainedModel, FlavaTextModel, ) from .models.fnet import ( FNetForMaskedLM, FNetForMultipleChoice, FNetForNextSentencePrediction, FNetForPreTraining, FNetForQuestionAnswering, FNetForSequenceClassification, FNetForTokenClassification, FNetModel, FNetPreTrainedModel, ) from .models.focalnet import ( FocalNetBackbone, FocalNetForImageClassification, FocalNetForMaskedImageModeling, FocalNetModel, FocalNetPreTrainedModel, ) from .models.fsmt import ( FSMTForConditionalGeneration, FSMTModel, PretrainedFSMTModel, ) from .models.funnel import ( FunnelBaseModel, FunnelForMaskedLM, FunnelForMultipleChoice, FunnelForPreTraining, FunnelForQuestionAnswering, FunnelForSequenceClassification, FunnelForTokenClassification, FunnelModel, FunnelPreTrainedModel, load_tf_weights_in_funnel, ) from .models.fuyu import ( FuyuForCausalLM, FuyuPreTrainedModel, ) from .models.gemma import ( GemmaForCausalLM, GemmaForSequenceClassification, GemmaForTokenClassification, GemmaModel, GemmaPreTrainedModel, ) from .models.gemma2 import ( Gemma2ForCausalLM, Gemma2ForSequenceClassification, Gemma2ForTokenClassification, Gemma2Model, Gemma2PreTrainedModel, ) from .models.git import ( GitForCausalLM, GitModel, GitPreTrainedModel, GitVisionModel, ) from .models.glm import ( GlmForCausalLM, GlmForSequenceClassification, GlmForTokenClassification, GlmModel, GlmPreTrainedModel, ) from .models.glpn import ( GLPNForDepthEstimation, GLPNModel, GLPNPreTrainedModel, ) from .models.gpt2 import ( GPT2DoubleHeadsModel, GPT2ForQuestionAnswering, GPT2ForSequenceClassification, GPT2ForTokenClassification, GPT2LMHeadModel, GPT2Model, GPT2PreTrainedModel, load_tf_weights_in_gpt2, ) from .models.gpt_bigcode import ( GPTBigCodeForCausalLM, GPTBigCodeForSequenceClassification, GPTBigCodeForTokenClassification, GPTBigCodeModel, GPTBigCodePreTrainedModel, ) from .models.gpt_neo import ( GPTNeoForCausalLM, GPTNeoForQuestionAnswering, GPTNeoForSequenceClassification, GPTNeoForTokenClassification, GPTNeoModel, GPTNeoPreTrainedModel, load_tf_weights_in_gpt_neo, ) from .models.gpt_neox import ( GPTNeoXForCausalLM, GPTNeoXForQuestionAnswering, GPTNeoXForSequenceClassification, GPTNeoXForTokenClassification, GPTNeoXModel, GPTNeoXPreTrainedModel, ) from .models.gpt_neox_japanese import ( GPTNeoXJapaneseForCausalLM, GPTNeoXJapaneseModel, GPTNeoXJapanesePreTrainedModel, ) from .models.gptj import ( GPTJForCausalLM, GPTJForQuestionAnswering, GPTJForSequenceClassification, GPTJModel, GPTJPreTrainedModel, ) from .models.granite import ( GraniteForCausalLM, GraniteModel, GranitePreTrainedModel, ) from .models.granitemoe import ( GraniteMoeForCausalLM, GraniteMoeModel, GraniteMoePreTrainedModel, ) from .models.grounding_dino import ( GroundingDinoForObjectDetection, GroundingDinoModel, GroundingDinoPreTrainedModel, ) from .models.groupvit import ( GroupViTModel, GroupViTPreTrainedModel, GroupViTTextModel, GroupViTVisionModel, ) from .models.hiera import ( HieraBackbone, HieraForImageClassification, HieraForPreTraining, HieraModel, HieraPreTrainedModel, ) from .models.hubert import ( HubertForCTC, HubertForSequenceClassification, HubertModel, HubertPreTrainedModel, ) from .models.ibert import ( IBertForMaskedLM, IBertForMultipleChoice, IBertForQuestionAnswering, IBertForSequenceClassification, IBertForTokenClassification, IBertModel, IBertPreTrainedModel, ) from .models.idefics import ( IdeficsForVisionText2Text, IdeficsModel, IdeficsPreTrainedModel, IdeficsProcessor, ) from .models.idefics2 import ( Idefics2ForConditionalGeneration, Idefics2Model, Idefics2PreTrainedModel, Idefics2Processor, ) from .models.idefics3 import ( Idefics3ForConditionalGeneration, Idefics3Model, Idefics3PreTrainedModel, Idefics3Processor, ) from .models.ijepa import ( IJepaForImageClassification, IJepaModel, IJepaPreTrainedModel, ) from .models.imagegpt import ( ImageGPTForCausalImageModeling, ImageGPTForImageClassification, ImageGPTModel, ImageGPTPreTrainedModel, load_tf_weights_in_imagegpt, ) from .models.informer import ( InformerForPrediction, InformerModel, InformerPreTrainedModel, ) from .models.instructblip import ( InstructBlipForConditionalGeneration, InstructBlipPreTrainedModel, InstructBlipQFormerModel, InstructBlipVisionModel, ) from .models.instructblipvideo import ( InstructBlipVideoForConditionalGeneration, InstructBlipVideoPreTrainedModel, InstructBlipVideoQFormerModel, InstructBlipVideoVisionModel, ) from .models.jamba import ( JambaForCausalLM, JambaForSequenceClassification, JambaModel, JambaPreTrainedModel, ) from .models.jetmoe import ( JetMoeForCausalLM, JetMoeForSequenceClassification, JetMoeModel, JetMoePreTrainedModel, ) from .models.kosmos2 import ( Kosmos2ForConditionalGeneration, Kosmos2Model, Kosmos2PreTrainedModel, ) from .models.layoutlm import ( LayoutLMForMaskedLM, LayoutLMForQuestionAnswering, LayoutLMForSequenceClassification, LayoutLMForTokenClassification, LayoutLMModel, LayoutLMPreTrainedModel, ) from .models.layoutlmv2 import ( LayoutLMv2ForQuestionAnswering, LayoutLMv2ForSequenceClassification, LayoutLMv2ForTokenClassification, LayoutLMv2Model, LayoutLMv2PreTrainedModel, ) from .models.layoutlmv3 import ( LayoutLMv3ForQuestionAnswering, LayoutLMv3ForSequenceClassification, LayoutLMv3ForTokenClassification, LayoutLMv3Model, LayoutLMv3PreTrainedModel, ) from .models.led import ( LEDForConditionalGeneration, LEDForQuestionAnswering, LEDForSequenceClassification, LEDModel, LEDPreTrainedModel, ) from .models.levit import ( LevitForImageClassification, LevitForImageClassificationWithTeacher, LevitModel, LevitPreTrainedModel, ) from .models.lilt import ( LiltForQuestionAnswering, LiltForSequenceClassification, LiltForTokenClassification, LiltModel, LiltPreTrainedModel, ) from .models.llama import ( LlamaForCausalLM, LlamaForQuestionAnswering, LlamaForSequenceClassification, LlamaForTokenClassification, LlamaModel, LlamaPreTrainedModel, ) from .models.llava import ( LlavaForConditionalGeneration, LlavaPreTrainedModel, ) from .models.llava_next import ( LlavaNextForConditionalGeneration, LlavaNextPreTrainedModel, ) from .models.llava_next_video import ( LlavaNextVideoForConditionalGeneration, LlavaNextVideoPreTrainedModel, ) from .models.llava_onevision import ( LlavaOnevisionForConditionalGeneration, LlavaOnevisionPreTrainedModel, ) from .models.longformer import ( LongformerForMaskedLM, LongformerForMultipleChoice, LongformerForQuestionAnswering, LongformerForSequenceClassification, LongformerForTokenClassification, LongformerModel, LongformerPreTrainedModel, ) from .models.longt5 import ( LongT5EncoderModel, LongT5ForConditionalGeneration, LongT5Model, LongT5PreTrainedModel, ) from .models.luke import ( LukeForEntityClassification, LukeForEntityPairClassification, LukeForEntitySpanClassification, LukeForMaskedLM, LukeForMultipleChoice, LukeForQuestionAnswering, LukeForSequenceClassification, LukeForTokenClassification, LukeModel, LukePreTrainedModel, ) from .models.lxmert import ( LxmertEncoder, LxmertForPreTraining, LxmertForQuestionAnswering, LxmertModel, LxmertPreTrainedModel, LxmertVisualFeatureEncoder, ) from .models.m2m_100 import ( M2M100ForConditionalGeneration, M2M100Model, M2M100PreTrainedModel, ) from .models.mamba import ( MambaForCausalLM, MambaModel, MambaPreTrainedModel, ) from .models.mamba2 import ( Mamba2ForCausalLM, Mamba2Model, Mamba2PreTrainedModel, ) from .models.marian import MarianForCausalLM, MarianModel, MarianMTModel, MarianPreTrainedModel from .models.markuplm import ( MarkupLMForQuestionAnswering, MarkupLMForSequenceClassification, MarkupLMForTokenClassification, MarkupLMModel, MarkupLMPreTrainedModel, ) from .models.mask2former import ( Mask2FormerForUniversalSegmentation, Mask2FormerModel, Mask2FormerPreTrainedModel, ) from .models.maskformer import ( MaskFormerForInstanceSegmentation, MaskFormerModel, MaskFormerPreTrainedModel, MaskFormerSwinBackbone, ) from .models.mbart import ( MBartForCausalLM, MBartForConditionalGeneration, MBartForQuestionAnswering, MBartForSequenceClassification, MBartModel, MBartPreTrainedModel, ) from .models.megatron_bert import ( MegatronBertForCausalLM, MegatronBertForMaskedLM, MegatronBertForMultipleChoice, MegatronBertForNextSentencePrediction, MegatronBertForPreTraining, MegatronBertForQuestionAnswering, MegatronBertForSequenceClassification, MegatronBertForTokenClassification, MegatronBertModel, MegatronBertPreTrainedModel, ) from .models.mgp_str import ( MgpstrForSceneTextRecognition, MgpstrModel, MgpstrPreTrainedModel, ) from .models.mimi import ( MimiModel, MimiPreTrainedModel, ) from .models.mistral import ( MistralForCausalLM, MistralForQuestionAnswering, MistralForSequenceClassification, MistralForTokenClassification, MistralModel, MistralPreTrainedModel, ) from .models.mixtral import ( MixtralForCausalLM, MixtralForQuestionAnswering, MixtralForSequenceClassification, MixtralForTokenClassification, MixtralModel, MixtralPreTrainedModel, ) from .models.mllama import ( MllamaForCausalLM, MllamaForConditionalGeneration, MllamaPreTrainedModel, MllamaProcessor, MllamaTextModel, MllamaVisionModel, ) from .models.mobilebert import ( MobileBertForMaskedLM, MobileBertForMultipleChoice, MobileBertForNextSentencePrediction, MobileBertForPreTraining, MobileBertForQuestionAnswering, MobileBertForSequenceClassification, MobileBertForTokenClassification, MobileBertModel, MobileBertPreTrainedModel, load_tf_weights_in_mobilebert, ) from .models.mobilenet_v1 import ( MobileNetV1ForImageClassification, MobileNetV1Model, MobileNetV1PreTrainedModel, load_tf_weights_in_mobilenet_v1, ) from .models.mobilenet_v2 import ( MobileNetV2ForImageClassification, MobileNetV2ForSemanticSegmentation, MobileNetV2Model, MobileNetV2PreTrainedModel, load_tf_weights_in_mobilenet_v2, ) from .models.mobilevit import ( MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTModel, MobileViTPreTrainedModel, ) from .models.mobilevitv2 import ( MobileViTV2ForImageClassification, MobileViTV2ForSemanticSegmentation, MobileViTV2Model, MobileViTV2PreTrainedModel, ) from .models.moshi import ( MoshiForCausalLM, MoshiForConditionalGeneration, MoshiModel, MoshiPreTrainedModel, ) from .models.mpnet import ( MPNetForMaskedLM, MPNetForMultipleChoice, MPNetForQuestionAnswering, MPNetForSequenceClassification, MPNetForTokenClassification, MPNetModel, MPNetPreTrainedModel, ) from .models.mpt import ( MptForCausalLM, MptForQuestionAnswering, MptForSequenceClassification, MptForTokenClassification, MptModel, MptPreTrainedModel, ) from .models.mra import ( MraForMaskedLM, MraForMultipleChoice, MraForQuestionAnswering, MraForSequenceClassification, MraForTokenClassification, MraModel, MraPreTrainedModel, ) from .models.mt5 import ( MT5EncoderModel, MT5ForConditionalGeneration, MT5ForQuestionAnswering, MT5ForSequenceClassification, MT5ForTokenClassification, MT5Model, MT5PreTrainedModel, ) from .models.musicgen import ( MusicgenForCausalLM, MusicgenForConditionalGeneration, MusicgenModel, MusicgenPreTrainedModel, MusicgenProcessor, ) from .models.musicgen_melody import ( MusicgenMelodyForCausalLM, MusicgenMelodyForConditionalGeneration, MusicgenMelodyModel, MusicgenMelodyPreTrainedModel, ) from .models.mvp import ( MvpForCausalLM, MvpForConditionalGeneration, MvpForQuestionAnswering, MvpForSequenceClassification, MvpModel, MvpPreTrainedModel, ) from .models.nemotron import ( NemotronForCausalLM, NemotronForQuestionAnswering, NemotronForSequenceClassification, NemotronForTokenClassification, NemotronModel, NemotronPreTrainedModel, ) from .models.nllb_moe import ( NllbMoeForConditionalGeneration, NllbMoeModel, NllbMoePreTrainedModel, NllbMoeSparseMLP, NllbMoeTop2Router, ) from .models.nystromformer import ( NystromformerForMaskedLM, NystromformerForMultipleChoice, NystromformerForQuestionAnswering, NystromformerForSequenceClassification, NystromformerForTokenClassification, NystromformerModel, NystromformerPreTrainedModel, ) from .models.olmo import ( OlmoForCausalLM, OlmoModel, OlmoPreTrainedModel, ) from .models.olmo2 import ( Olmo2ForCausalLM, Olmo2Model, Olmo2PreTrainedModel, ) from .models.olmoe import ( OlmoeForCausalLM, OlmoeModel, OlmoePreTrainedModel, ) from .models.omdet_turbo import ( OmDetTurboForObjectDetection, OmDetTurboPreTrainedModel, ) from .models.oneformer import ( OneFormerForUniversalSegmentation, OneFormerModel, OneFormerPreTrainedModel, ) from .models.openai import ( OpenAIGPTDoubleHeadsModel, OpenAIGPTForSequenceClassification, OpenAIGPTLMHeadModel, OpenAIGPTModel, OpenAIGPTPreTrainedModel, load_tf_weights_in_openai_gpt, ) from .models.opt import ( OPTForCausalLM, OPTForQuestionAnswering, OPTForSequenceClassification, OPTModel, OPTPreTrainedModel, ) from .models.owlv2 import ( Owlv2ForObjectDetection, Owlv2Model, Owlv2PreTrainedModel, Owlv2TextModel, Owlv2VisionModel, ) from .models.owlvit import ( OwlViTForObjectDetection, OwlViTModel, OwlViTPreTrainedModel, OwlViTTextModel, OwlViTVisionModel, ) from .models.paligemma import ( PaliGemmaForConditionalGeneration, PaliGemmaPreTrainedModel, PaliGemmaProcessor, ) from .models.patchtsmixer import ( PatchTSMixerForPrediction, PatchTSMixerForPretraining, PatchTSMixerForRegression, PatchTSMixerForTimeSeriesClassification, PatchTSMixerModel, PatchTSMixerPreTrainedModel, ) from .models.patchtst import ( PatchTSTForClassification, PatchTSTForPrediction, PatchTSTForPretraining, PatchTSTForRegression, PatchTSTModel, PatchTSTPreTrainedModel, ) from .models.pegasus import ( PegasusForCausalLM, PegasusForConditionalGeneration, PegasusModel, PegasusPreTrainedModel, ) from .models.pegasus_x import ( PegasusXForConditionalGeneration, PegasusXModel, PegasusXPreTrainedModel, ) from .models.perceiver import ( PerceiverForImageClassificationConvProcessing, PerceiverForImageClassificationFourier, PerceiverForImageClassificationLearned, PerceiverForMaskedLM, PerceiverForMultimodalAutoencoding, PerceiverForOpticalFlow, PerceiverForSequenceClassification, PerceiverModel, PerceiverPreTrainedModel, ) from .models.persimmon import ( PersimmonForCausalLM, PersimmonForSequenceClassification, PersimmonForTokenClassification, PersimmonModel, PersimmonPreTrainedModel, ) from .models.phi import ( PhiForCausalLM, PhiForSequenceClassification, PhiForTokenClassification, PhiModel, PhiPreTrainedModel, ) from .models.phi3 import ( Phi3ForCausalLM, Phi3ForSequenceClassification, Phi3ForTokenClassification, Phi3Model, Phi3PreTrainedModel, ) from .models.phimoe import ( PhimoeForCausalLM, PhimoeForSequenceClassification, PhimoeModel, PhimoePreTrainedModel, ) from .models.pix2struct import ( Pix2StructForConditionalGeneration, Pix2StructPreTrainedModel, Pix2StructTextModel, Pix2StructVisionModel, ) from .models.pixtral import ( PixtralPreTrainedModel, PixtralVisionModel, ) from .models.plbart import ( PLBartForCausalLM, PLBartForConditionalGeneration, PLBartForSequenceClassification, PLBartModel, PLBartPreTrainedModel, ) from .models.poolformer import ( PoolFormerForImageClassification, PoolFormerModel, PoolFormerPreTrainedModel, ) from .models.pop2piano import ( Pop2PianoForConditionalGeneration, Pop2PianoPreTrainedModel, ) from .models.prophetnet import ( ProphetNetDecoder, ProphetNetEncoder, ProphetNetForCausalLM, ProphetNetForConditionalGeneration, ProphetNetModel, ProphetNetPreTrainedModel, ) from .models.pvt import ( PvtForImageClassification, PvtModel, PvtPreTrainedModel, ) from .models.pvt_v2 import ( PvtV2Backbone, PvtV2ForImageClassification, PvtV2Model, PvtV2PreTrainedModel, ) from .models.qwen2 import ( Qwen2ForCausalLM, Qwen2ForQuestionAnswering, Qwen2ForSequenceClassification, Qwen2ForTokenClassification, Qwen2Model, Qwen2PreTrainedModel, ) from .models.qwen2_audio import ( Qwen2AudioEncoder, Qwen2AudioForConditionalGeneration, Qwen2AudioPreTrainedModel, ) from .models.qwen2_moe import ( Qwen2MoeForCausalLM, Qwen2MoeForQuestionAnswering, Qwen2MoeForSequenceClassification, Qwen2MoeForTokenClassification, Qwen2MoeModel, Qwen2MoePreTrainedModel, ) from .models.qwen2_vl import ( Qwen2VLForConditionalGeneration, Qwen2VLModel, Qwen2VLPreTrainedModel, ) from .models.rag import ( RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration, ) from .models.recurrent_gemma import ( RecurrentGemmaForCausalLM, RecurrentGemmaModel, RecurrentGemmaPreTrainedModel, ) from .models.reformer import ( ReformerForMaskedLM, ReformerForQuestionAnswering, ReformerForSequenceClassification, ReformerModel, ReformerModelWithLMHead, ReformerPreTrainedModel, ) from .models.regnet import ( RegNetForImageClassification, RegNetModel, RegNetPreTrainedModel, ) from .models.rembert import ( RemBertForCausalLM, RemBertForMaskedLM, RemBertForMultipleChoice, RemBertForQuestionAnswering, RemBertForSequenceClassification, RemBertForTokenClassification, RemBertModel, RemBertPreTrainedModel, load_tf_weights_in_rembert, ) from .models.resnet import ( ResNetBackbone, ResNetForImageClassification, ResNetModel, ResNetPreTrainedModel, ) from .models.roberta import ( RobertaForCausalLM, RobertaForMaskedLM, RobertaForMultipleChoice, RobertaForQuestionAnswering, RobertaForSequenceClassification, RobertaForTokenClassification, RobertaModel, RobertaPreTrainedModel, ) from .models.roberta_prelayernorm import ( RobertaPreLayerNormForCausalLM, RobertaPreLayerNormForMaskedLM, RobertaPreLayerNormForMultipleChoice, RobertaPreLayerNormForQuestionAnswering, RobertaPreLayerNormForSequenceClassification, RobertaPreLayerNormForTokenClassification, RobertaPreLayerNormModel, RobertaPreLayerNormPreTrainedModel, ) from .models.roc_bert import ( RoCBertForCausalLM, RoCBertForMaskedLM, RoCBertForMultipleChoice, RoCBertForPreTraining, RoCBertForQuestionAnswering, RoCBertForSequenceClassification, RoCBertForTokenClassification, RoCBertModel, RoCBertPreTrainedModel, load_tf_weights_in_roc_bert, ) from .models.roformer import ( RoFormerForCausalLM, RoFormerForMaskedLM, RoFormerForMultipleChoice, RoFormerForQuestionAnswering, RoFormerForSequenceClassification, RoFormerForTokenClassification, RoFormerModel, RoFormerPreTrainedModel, load_tf_weights_in_roformer, ) from .models.rt_detr import ( RTDetrForObjectDetection, RTDetrModel, RTDetrPreTrainedModel, RTDetrResNetBackbone, RTDetrResNetPreTrainedModel, ) from .models.rwkv import ( RwkvForCausalLM, RwkvModel, RwkvPreTrainedModel, ) from .models.sam import ( SamModel, SamPreTrainedModel, ) from .models.seamless_m4t import ( SeamlessM4TCodeHifiGan, SeamlessM4TForSpeechToSpeech, SeamlessM4TForSpeechToText, SeamlessM4TForTextToSpeech, SeamlessM4TForTextToText, SeamlessM4THifiGan, SeamlessM4TModel, SeamlessM4TPreTrainedModel, SeamlessM4TTextToUnitForConditionalGeneration, SeamlessM4TTextToUnitModel, ) from .models.seamless_m4t_v2 import ( SeamlessM4Tv2ForSpeechToSpeech, SeamlessM4Tv2ForSpeechToText, SeamlessM4Tv2ForTextToSpeech, SeamlessM4Tv2ForTextToText, SeamlessM4Tv2Model, SeamlessM4Tv2PreTrainedModel, ) from .models.segformer import ( SegformerDecodeHead, SegformerForImageClassification, SegformerForSemanticSegmentation, SegformerModel, SegformerPreTrainedModel, ) from .models.seggpt import ( SegGptForImageSegmentation, SegGptModel, SegGptPreTrainedModel, ) from .models.sew import ( SEWForCTC, SEWForSequenceClassification, SEWModel, SEWPreTrainedModel, ) from .models.sew_d import ( SEWDForCTC, SEWDForSequenceClassification, SEWDModel, SEWDPreTrainedModel, ) from .models.siglip import ( SiglipForImageClassification, SiglipModel, SiglipPreTrainedModel, SiglipTextModel, SiglipVisionModel, ) from .models.speech_encoder_decoder import SpeechEncoderDecoderModel from .models.speech_to_text import ( Speech2TextForConditionalGeneration, Speech2TextModel, Speech2TextPreTrainedModel, ) from .models.speecht5 import ( SpeechT5ForSpeechToSpeech, SpeechT5ForSpeechToText, SpeechT5ForTextToSpeech, SpeechT5HifiGan, SpeechT5Model, SpeechT5PreTrainedModel, ) from .models.splinter import ( SplinterForPreTraining, SplinterForQuestionAnswering, SplinterModel, SplinterPreTrainedModel, ) from .models.squeezebert import ( SqueezeBertForMaskedLM, SqueezeBertForMultipleChoice, SqueezeBertForQuestionAnswering, SqueezeBertForSequenceClassification, SqueezeBertForTokenClassification, SqueezeBertModel, SqueezeBertPreTrainedModel, ) from .models.stablelm import ( StableLmForCausalLM, StableLmForSequenceClassification, StableLmForTokenClassification, StableLmModel, StableLmPreTrainedModel, ) from .models.starcoder2 import ( Starcoder2ForCausalLM, Starcoder2ForSequenceClassification, Starcoder2ForTokenClassification, Starcoder2Model, Starcoder2PreTrainedModel, ) from .models.superpoint import ( SuperPointForKeypointDetection, SuperPointPreTrainedModel, ) from .models.swiftformer import ( SwiftFormerForImageClassification, SwiftFormerModel, SwiftFormerPreTrainedModel, ) from .models.swin import ( SwinBackbone, SwinForImageClassification, SwinForMaskedImageModeling, SwinModel, SwinPreTrainedModel, ) from .models.swin2sr import ( Swin2SRForImageSuperResolution, Swin2SRModel, Swin2SRPreTrainedModel, ) from .models.swinv2 import ( Swinv2Backbone, Swinv2ForImageClassification, Swinv2ForMaskedImageModeling, Swinv2Model, Swinv2PreTrainedModel, ) from .models.switch_transformers import ( SwitchTransformersEncoderModel, SwitchTransformersForConditionalGeneration, SwitchTransformersModel, SwitchTransformersPreTrainedModel, SwitchTransformersSparseMLP, SwitchTransformersTop1Router, ) from .models.t5 import ( T5EncoderModel, T5ForConditionalGeneration, T5ForQuestionAnswering, T5ForSequenceClassification, T5ForTokenClassification, T5Model, T5PreTrainedModel, load_tf_weights_in_t5, ) from .models.table_transformer import ( TableTransformerForObjectDetection, TableTransformerModel, TableTransformerPreTrainedModel, ) from .models.tapas import ( TapasForMaskedLM, TapasForQuestionAnswering, TapasForSequenceClassification, TapasModel, TapasPreTrainedModel, load_tf_weights_in_tapas, ) from .models.time_series_transformer import ( TimeSeriesTransformerForPrediction, TimeSeriesTransformerModel, TimeSeriesTransformerPreTrainedModel, ) from .models.timesformer import ( TimesformerForVideoClassification, TimesformerModel, TimesformerPreTrainedModel, ) from .models.timm_backbone import TimmBackbone from .models.trocr import ( TrOCRForCausalLM, TrOCRPreTrainedModel, ) from .models.tvp import ( TvpForVideoGrounding, TvpModel, TvpPreTrainedModel, ) from .models.udop import ( UdopEncoderModel, UdopForConditionalGeneration, UdopModel, UdopPreTrainedModel, ) from .models.umt5 import ( UMT5EncoderModel, UMT5ForConditionalGeneration, UMT5ForQuestionAnswering, UMT5ForSequenceClassification, UMT5ForTokenClassification, UMT5Model, UMT5PreTrainedModel, ) from .models.unispeech import ( UniSpeechForCTC, UniSpeechForPreTraining, UniSpeechForSequenceClassification, UniSpeechModel, UniSpeechPreTrainedModel, ) from .models.unispeech_sat import ( UniSpeechSatForAudioFrameClassification, UniSpeechSatForCTC, UniSpeechSatForPreTraining, UniSpeechSatForSequenceClassification, UniSpeechSatForXVector, UniSpeechSatModel, UniSpeechSatPreTrainedModel, ) from .models.univnet import UnivNetModel from .models.upernet import ( UperNetForSemanticSegmentation, UperNetPreTrainedModel, ) from .models.video_llava import ( VideoLlavaForConditionalGeneration, VideoLlavaPreTrainedModel, VideoLlavaProcessor, ) from .models.videomae import ( VideoMAEForPreTraining, VideoMAEForVideoClassification, VideoMAEModel, VideoMAEPreTrainedModel, ) from .models.vilt import ( ViltForImageAndTextRetrieval, ViltForImagesAndTextClassification, ViltForMaskedLM, ViltForQuestionAnswering, ViltForTokenClassification, ViltModel, ViltPreTrainedModel, ) from .models.vipllava import ( VipLlavaForConditionalGeneration, VipLlavaPreTrainedModel, ) from .models.vision_encoder_decoder import VisionEncoderDecoderModel from .models.vision_text_dual_encoder import VisionTextDualEncoderModel from .models.visual_bert import ( VisualBertForMultipleChoice, VisualBertForPreTraining, VisualBertForQuestionAnswering, VisualBertForRegionToPhraseAlignment, VisualBertForVisualReasoning, VisualBertModel, VisualBertPreTrainedModel, ) from .models.vit import ( ViTForImageClassification, ViTForMaskedImageModeling, ViTModel, ViTPreTrainedModel, ) from .models.vit_mae import ( ViTMAEForPreTraining, ViTMAEModel, ViTMAEPreTrainedModel, ) from .models.vit_msn import ( ViTMSNForImageClassification, ViTMSNModel, ViTMSNPreTrainedModel, ) from .models.vitdet import ( VitDetBackbone, VitDetModel, VitDetPreTrainedModel, ) from .models.vitmatte import ( VitMatteForImageMatting, VitMattePreTrainedModel, ) from .models.vits import ( VitsModel, VitsPreTrainedModel, ) from .models.vivit import ( VivitForVideoClassification, VivitModel, VivitPreTrainedModel, ) from .models.wav2vec2 import ( Wav2Vec2ForAudioFrameClassification, Wav2Vec2ForCTC, Wav2Vec2ForMaskedLM, Wav2Vec2ForPreTraining, Wav2Vec2ForSequenceClassification, Wav2Vec2ForXVector, Wav2Vec2Model, Wav2Vec2PreTrainedModel, ) from .models.wav2vec2_bert import ( Wav2Vec2BertForAudioFrameClassification, Wav2Vec2BertForCTC, Wav2Vec2BertForSequenceClassification, Wav2Vec2BertForXVector, Wav2Vec2BertModel, Wav2Vec2BertPreTrainedModel, ) from .models.wav2vec2_conformer import ( Wav2Vec2ConformerForAudioFrameClassification, Wav2Vec2ConformerForCTC, Wav2Vec2ConformerForPreTraining, Wav2Vec2ConformerForSequenceClassification, Wav2Vec2ConformerForXVector, Wav2Vec2ConformerModel, Wav2Vec2ConformerPreTrainedModel, ) from .models.wavlm import ( WavLMForAudioFrameClassification, WavLMForCTC, WavLMForSequenceClassification, WavLMForXVector, WavLMModel, WavLMPreTrainedModel, ) from .models.whisper import ( WhisperForAudioClassification, WhisperForCausalLM, WhisperForConditionalGeneration, WhisperModel, WhisperPreTrainedModel, ) from .models.x_clip import ( XCLIPModel, XCLIPPreTrainedModel, XCLIPTextModel, XCLIPVisionModel, ) from .models.xglm import ( XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel, ) from .models.xlm import ( XLMForMultipleChoice, XLMForQuestionAnswering, XLMForQuestionAnsweringSimple, XLMForSequenceClassification, XLMForTokenClassification, XLMModel, XLMPreTrainedModel, XLMWithLMHeadModel, ) from .models.xlm_roberta import ( XLMRobertaForCausalLM, XLMRobertaForMaskedLM, XLMRobertaForMultipleChoice, XLMRobertaForQuestionAnswering, XLMRobertaForSequenceClassification, XLMRobertaForTokenClassification, XLMRobertaModel, XLMRobertaPreTrainedModel, ) from .models.xlm_roberta_xl import ( XLMRobertaXLForCausalLM, XLMRobertaXLForMaskedLM, XLMRobertaXLForMultipleChoice, XLMRobertaXLForQuestionAnswering, XLMRobertaXLForSequenceClassification, XLMRobertaXLForTokenClassification, XLMRobertaXLModel, XLMRobertaXLPreTrainedModel, ) from .models.xlnet import ( XLNetForMultipleChoice, XLNetForQuestionAnswering, XLNetForQuestionAnsweringSimple, XLNetForSequenceClassification, XLNetForTokenClassification, XLNetLMHeadModel, XLNetModel, XLNetPreTrainedModel, load_tf_weights_in_xlnet, ) from .models.xmod import ( XmodForCausalLM, XmodForMaskedLM, XmodForMultipleChoice, XmodForQuestionAnswering, XmodForSequenceClassification, XmodForTokenClassification, XmodModel, XmodPreTrainedModel, ) from .models.yolos import ( YolosForObjectDetection, YolosModel, YolosPreTrainedModel, ) from .models.yoso import ( YosoForMaskedLM, YosoForMultipleChoice, YosoForQuestionAnswering, YosoForSequenceClassification, YosoForTokenClassification, YosoModel, YosoPreTrainedModel, ) from .models.zamba import ( ZambaForCausalLM, ZambaForSequenceClassification, ZambaModel, ZambaPreTrainedModel, ) from .models.zoedepth import ( ZoeDepthForDepthEstimation, ZoeDepthPreTrainedModel, ) # 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, get_wsd_schedule, ) 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, ) from .keras_callbacks import KerasMetricCallback, PushToHubCallback from .modeling_tf_utils import ( TFPreTrainedModel, TFSequenceSummary, TFSharedEmbeddings, shape_list, ) # TensorFlow model imports from .models.albert import ( 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 ( 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 ( TFBlipForConditionalGeneration, TFBlipForImageTextRetrieval, TFBlipForQuestionAnswering, TFBlipModel, TFBlipPreTrainedModel, TFBlipTextModel, TFBlipVisionModel, ) from .models.camembert import ( TFCamembertForCausalLM, TFCamembertForMaskedLM, TFCamembertForMultipleChoice, TFCamembertForQuestionAnswering, TFCamembertForSequenceClassification, TFCamembertForTokenClassification, TFCamembertModel, TFCamembertPreTrainedModel, ) from .models.clip import ( TFCLIPModel, TFCLIPPreTrainedModel, TFCLIPTextModel, TFCLIPVisionModel, ) from .models.convbert import ( TFConvBertForMaskedLM, TFConvBertForMultipleChoice, TFConvBertForQuestionAnswering, TFConvBertForSequenceClassification, TFConvBertForTokenClassification, TFConvBertModel, TFConvBertPreTrainedModel, ) from .models.convnext import ( TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel, ) from .models.convnextv2 import ( TFConvNextV2ForImageClassification, TFConvNextV2Model, TFConvNextV2PreTrainedModel, ) from .models.ctrl import ( TFCTRLForSequenceClassification, TFCTRLLMHeadModel, TFCTRLModel, TFCTRLPreTrainedModel, ) from .models.cvt import ( TFCvtForImageClassification, TFCvtModel, TFCvtPreTrainedModel, ) from .models.data2vec import ( TFData2VecVisionForImageClassification, TFData2VecVisionForSemanticSegmentation, TFData2VecVisionModel, TFData2VecVisionPreTrainedModel, ) from .models.deberta import ( TFDebertaForMaskedLM, TFDebertaForQuestionAnswering, TFDebertaForSequenceClassification, TFDebertaForTokenClassification, TFDebertaModel, TFDebertaPreTrainedModel, ) from .models.deberta_v2 import ( TFDebertaV2ForMaskedLM, TFDebertaV2ForMultipleChoice, TFDebertaV2ForQuestionAnswering, TFDebertaV2ForSequenceClassification, TFDebertaV2ForTokenClassification, TFDebertaV2Model, TFDebertaV2PreTrainedModel, ) from .models.deit import ( TFDeiTForImageClassification, TFDeiTForImageClassificationWithTeacher, TFDeiTForMaskedImageModeling, TFDeiTModel, TFDeiTPreTrainedModel, ) from .models.deprecated.efficientformer import ( TFEfficientFormerForImageClassification, TFEfficientFormerForImageClassificationWithTeacher, TFEfficientFormerModel, TFEfficientFormerPreTrainedModel, ) from .models.deprecated.transfo_xl import ( TFAdaptiveEmbedding, TFTransfoXLForSequenceClassification, TFTransfoXLLMHeadModel, TFTransfoXLMainLayer, TFTransfoXLModel, TFTransfoXLPreTrainedModel, ) from .models.distilbert import ( TFDistilBertForMaskedLM, TFDistilBertForMultipleChoice, TFDistilBertForQuestionAnswering, TFDistilBertForSequenceClassification, TFDistilBertForTokenClassification, TFDistilBertMainLayer, TFDistilBertModel, TFDistilBertPreTrainedModel, ) from .models.dpr import ( TFDPRContextEncoder, TFDPRPretrainedContextEncoder, TFDPRPretrainedQuestionEncoder, TFDPRPretrainedReader, TFDPRQuestionEncoder, TFDPRReader, ) from .models.electra import ( TFElectraForMaskedLM, TFElectraForMultipleChoice, TFElectraForPreTraining, TFElectraForQuestionAnswering, TFElectraForSequenceClassification, TFElectraForTokenClassification, TFElectraModel, TFElectraPreTrainedModel, ) from .models.encoder_decoder import TFEncoderDecoderModel from .models.esm import ( TFEsmForMaskedLM, TFEsmForSequenceClassification, TFEsmForTokenClassification, TFEsmModel, TFEsmPreTrainedModel, ) from .models.flaubert import ( TFFlaubertForMultipleChoice, TFFlaubertForQuestionAnsweringSimple, TFFlaubertForSequenceClassification, TFFlaubertForTokenClassification, TFFlaubertModel, TFFlaubertPreTrainedModel, TFFlaubertWithLMHeadModel, ) from .models.funnel import ( TFFunnelBaseModel, TFFunnelForMaskedLM, TFFunnelForMultipleChoice, TFFunnelForPreTraining, TFFunnelForQuestionAnswering, TFFunnelForSequenceClassification, TFFunnelForTokenClassification, TFFunnelModel, TFFunnelPreTrainedModel, ) from .models.gpt2 import ( TFGPT2DoubleHeadsModel, TFGPT2ForSequenceClassification, TFGPT2LMHeadModel, TFGPT2MainLayer, TFGPT2Model, TFGPT2PreTrainedModel, ) from .models.gptj import ( TFGPTJForCausalLM, TFGPTJForQuestionAnswering, TFGPTJForSequenceClassification, TFGPTJModel, TFGPTJPreTrainedModel, ) from .models.groupvit import ( TFGroupViTModel, TFGroupViTPreTrainedModel, TFGroupViTTextModel, TFGroupViTVisionModel, ) from .models.hubert import ( TFHubertForCTC, TFHubertModel, TFHubertPreTrainedModel, ) from .models.idefics import ( TFIdeficsForVisionText2Text, TFIdeficsModel, TFIdeficsPreTrainedModel, ) from .models.layoutlm import ( TFLayoutLMForMaskedLM, TFLayoutLMForQuestionAnswering, TFLayoutLMForSequenceClassification, TFLayoutLMForTokenClassification, TFLayoutLMMainLayer, TFLayoutLMModel, TFLayoutLMPreTrainedModel, ) from .models.layoutlmv3 import ( TFLayoutLMv3ForQuestionAnswering, TFLayoutLMv3ForSequenceClassification, TFLayoutLMv3ForTokenClassification, TFLayoutLMv3Model, TFLayoutLMv3PreTrainedModel, ) from .models.led import ( TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel, ) from .models.longformer import ( TFLongformerForMaskedLM, TFLongformerForMultipleChoice, TFLongformerForQuestionAnswering, TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerModel, TFLongformerPreTrainedModel, ) from .models.lxmert import ( TFLxmertForPreTraining, TFLxmertMainLayer, TFLxmertModel, TFLxmertPreTrainedModel, TFLxmertVisualFeatureEncoder, ) from .models.marian import ( TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel, ) from .models.mbart import ( TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel, ) from .models.mistral import ( TFMistralForCausalLM, TFMistralForSequenceClassification, TFMistralModel, TFMistralPreTrainedModel, ) from .models.mobilebert import ( TFMobileBertForMaskedLM, TFMobileBertForMultipleChoice, TFMobileBertForNextSentencePrediction, TFMobileBertForPreTraining, TFMobileBertForQuestionAnswering, TFMobileBertForSequenceClassification, TFMobileBertForTokenClassification, TFMobileBertMainLayer, TFMobileBertModel, TFMobileBertPreTrainedModel, ) from .models.mobilevit import ( TFMobileViTForImageClassification, TFMobileViTForSemanticSegmentation, TFMobileViTModel, TFMobileViTPreTrainedModel, ) from .models.mpnet import ( TFMPNetForMaskedLM, TFMPNetForMultipleChoice, TFMPNetForQuestionAnswering, TFMPNetForSequenceClassification, TFMPNetForTokenClassification, TFMPNetMainLayer, TFMPNetModel, TFMPNetPreTrainedModel, ) from .models.mt5 import ( TFMT5EncoderModel, TFMT5ForConditionalGeneration, TFMT5Model, ) from .models.openai import ( 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 ( TFRegNetForImageClassification, TFRegNetModel, TFRegNetPreTrainedModel, ) from .models.rembert import ( TFRemBertForCausalLM, TFRemBertForMaskedLM, TFRemBertForMultipleChoice, TFRemBertForQuestionAnswering, TFRemBertForSequenceClassification, TFRemBertForTokenClassification, TFRemBertModel, TFRemBertPreTrainedModel, ) from .models.resnet import ( TFResNetForImageClassification, TFResNetModel, TFResNetPreTrainedModel, ) from .models.roberta import ( TFRobertaForCausalLM, TFRobertaForMaskedLM, TFRobertaForMultipleChoice, TFRobertaForQuestionAnswering, TFRobertaForSequenceClassification, TFRobertaForTokenClassification, TFRobertaMainLayer, TFRobertaModel, TFRobertaPreTrainedModel, ) from .models.roberta_prelayernorm import ( TFRobertaPreLayerNormForCausalLM, TFRobertaPreLayerNormForMaskedLM, TFRobertaPreLayerNormForMultipleChoice, TFRobertaPreLayerNormForQuestionAnswering, TFRobertaPreLayerNormForSequenceClassification, TFRobertaPreLayerNormForTokenClassification, TFRobertaPreLayerNormMainLayer, TFRobertaPreLayerNormModel, TFRobertaPreLayerNormPreTrainedModel, ) from .models.roformer import ( TFRoFormerForCausalLM, TFRoFormerForMaskedLM, TFRoFormerForMultipleChoice, TFRoFormerForQuestionAnswering, TFRoFormerForSequenceClassification, TFRoFormerForTokenClassification, TFRoFormerModel, TFRoFormerPreTrainedModel, ) from .models.sam import ( TFSamModel, TFSamPreTrainedModel, ) from .models.segformer import ( TFSegformerDecodeHead, TFSegformerForImageClassification, TFSegformerForSemanticSegmentation, TFSegformerModel, TFSegformerPreTrainedModel, ) from .models.speech_to_text import ( TFSpeech2TextForConditionalGeneration, TFSpeech2TextModel, TFSpeech2TextPreTrainedModel, ) from .models.swiftformer import ( TFSwiftFormerForImageClassification, TFSwiftFormerModel, TFSwiftFormerPreTrainedModel, ) from .models.swin import ( TFSwinForImageClassification, TFSwinForMaskedImageModeling, TFSwinModel, TFSwinPreTrainedModel, ) from .models.t5 import ( TFT5EncoderModel, TFT5ForConditionalGeneration, TFT5Model, TFT5PreTrainedModel, ) from .models.tapas import ( TFTapasForMaskedLM, TFTapasForQuestionAnswering, TFTapasForSequenceClassification, TFTapasModel, TFTapasPreTrainedModel, ) 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 ( TFWav2Vec2ForCTC, TFWav2Vec2ForSequenceClassification, TFWav2Vec2Model, TFWav2Vec2PreTrainedModel, ) from .models.whisper import ( TFWhisperForConditionalGeneration, TFWhisperModel, TFWhisperPreTrainedModel, ) from .models.xglm import ( TFXGLMForCausalLM, TFXGLMModel, TFXGLMPreTrainedModel, ) from .models.xlm import ( TFXLMForMultipleChoice, TFXLMForQuestionAnsweringSimple, TFXLMForSequenceClassification, TFXLMForTokenClassification, TFXLMMainLayer, TFXLMModel, TFXLMPreTrainedModel, TFXLMWithLMHeadModel, ) from .models.xlm_roberta import ( TFXLMRobertaForCausalLM, TFXLMRobertaForMaskedLM, TFXLMRobertaForMultipleChoice, TFXLMRobertaForQuestionAnswering, TFXLMRobertaForSequenceClassification, TFXLMRobertaForTokenClassification, TFXLMRobertaModel, TFXLMRobertaPreTrainedModel, ) from .models.xlnet import ( TFXLNetForMultipleChoice, TFXLNetForQuestionAnsweringSimple, TFXLNetForSequenceClassification, TFXLNetForTokenClassification, TFXLNetLMHeadModel, TFXLNetMainLayer, TFXLNetModel, TFXLNetPreTrainedModel, ) # Optimization from .optimization_tf import ( AdamWeightDecay, GradientAccumulator, WarmUp, create_optimizer, ) 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_torchaudio_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: from .utils.dummy_torchaudio_objects import * else: from .models.musicgen_melody import MusicgenMelodyFeatureExtractor, MusicgenMelodyProcessor 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.dinov2 import ( FlaxDinov2ForImageClassification, FlaxDinov2Model, FlaxDinov2PreTrainedModel, ) 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.gemma import ( FlaxGemmaForCausalLM, FlaxGemmaModel, FlaxGemmaPreTrainedModel, ) from .models.gpt2 import ( FlaxGPT2LMHeadModel, FlaxGPT2Model, FlaxGPT2PreTrainedModel, ) from .models.gpt_neo import ( FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel, ) from .models.gptj import ( FlaxGPTJForCausalLM, FlaxGPTJModel, FlaxGPTJPreTrainedModel, ) from .models.llama import ( FlaxLlamaForCausalLM, FlaxLlamaModel, FlaxLlamaPreTrainedModel, ) 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.mistral import ( FlaxMistralForCausalLM, FlaxMistralModel, FlaxMistralPreTrainedModel, ) 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 ( 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_advice( "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." )