'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_UpperCAmelCase						:    List[Any]     					=					{
    '''auto_factory''': ['''get_values'''],
    '''configuration_auto''': ['''ALL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CONFIG_MAPPING''', '''MODEL_NAMES_MAPPING''', '''AutoConfig'''],
    '''feature_extraction_auto''': ['''FEATURE_EXTRACTOR_MAPPING''', '''AutoFeatureExtractor'''],
    '''image_processing_auto''': ['''IMAGE_PROCESSOR_MAPPING''', '''AutoImageProcessor'''],
    '''processing_auto''': ['''PROCESSOR_MAPPING''', '''AutoProcessor'''],
    '''tokenization_auto''': ['''TOKENIZER_MAPPING''', '''AutoTokenizer'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    Union[str, Any]     					=					[
       '''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_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
       '''MODEL_FOR_DEPTH_ESTIMATION_MAPPING''',
       '''MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
       '''MODEL_FOR_IMAGE_SEGMENTATION_MAPPING''',
       '''MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING''',
       '''MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
       '''MODEL_FOR_MASKED_LM_MAPPING''',
       '''MODEL_FOR_MASK_GENERATION_MAPPING''',
       '''MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
       '''MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
       '''MODEL_FOR_OBJECT_DETECTION_MAPPING''',
       '''MODEL_FOR_PRETRAINING_MAPPING''',
       '''MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
       '''MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
       '''MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
       '''MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
       '''MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
       '''MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
       '''MODEL_FOR_TEXT_ENCODING_MAPPING''',
       '''MODEL_FOR_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_MAPPING''',
       '''MODEL_WITH_LM_HEAD_MAPPING''',
       '''MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
       '''MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING''',
       '''AutoModel''',
       '''AutoBackbone''',
       '''AutoModelForAudioClassification''',
       '''AutoModelForAudioFrameClassification''',
       '''AutoModelForAudioXVector''',
       '''AutoModelForCausalLM''',
       '''AutoModelForCTC''',
       '''AutoModelForDepthEstimation''',
       '''AutoModelForImageClassification''',
       '''AutoModelForImageSegmentation''',
       '''AutoModelForInstanceSegmentation''',
       '''AutoModelForMaskGeneration''',
       '''AutoModelForTextEncoding''',
       '''AutoModelForMaskedImageModeling''',
       '''AutoModelForMaskedLM''',
       '''AutoModelForMultipleChoice''',
       '''AutoModelForNextSentencePrediction''',
       '''AutoModelForObjectDetection''',
       '''AutoModelForPreTraining''',
       '''AutoModelForQuestionAnswering''',
       '''AutoModelForSemanticSegmentation''',
       '''AutoModelForSeq2SeqLM''',
       '''AutoModelForSequenceClassification''',
       '''AutoModelForSpeechSeq2Seq''',
       '''AutoModelForTableQuestionAnswering''',
       '''AutoModelForTokenClassification''',
       '''AutoModelForUniversalSegmentation''',
       '''AutoModelForVideoClassification''',
       '''AutoModelForVision2Seq''',
       '''AutoModelForVisualQuestionAnswering''',
       '''AutoModelForDocumentQuestionAnswering''',
       '''AutoModelWithLMHead''',
       '''AutoModelForZeroShotImageClassification''',
       '''AutoModelForZeroShotObjectDetection''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    Any     					=					[
       '''TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
       '''TF_MODEL_FOR_CAUSAL_LM_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_DOCUMENT_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''',
       '''TFAutoModelForImageClassification''',
       '''TFAutoModelForMaskedImageModeling''',
       '''TFAutoModelForMaskedLM''',
       '''TFAutoModelForMaskGeneration''',
       '''TFAutoModelForMultipleChoice''',
       '''TFAutoModelForNextSentencePrediction''',
       '''TFAutoModelForPreTraining''',
       '''TFAutoModelForDocumentQuestionAnswering''',
       '''TFAutoModelForQuestionAnswering''',
       '''TFAutoModelForSemanticSegmentation''',
       '''TFAutoModelForSeq2SeqLM''',
       '''TFAutoModelForSequenceClassification''',
       '''TFAutoModelForSpeechSeq2Seq''',
       '''TFAutoModelForTableQuestionAnswering''',
       '''TFAutoModelForTextEncoding''',
       '''TFAutoModelForTokenClassification''',
       '''TFAutoModelForVision2Seq''',
       '''TFAutoModelForZeroShotImageClassification''',
       '''TFAutoModelWithLMHead''',
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    str     					=					[
       '''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''',
   ]


if TYPE_CHECKING:
   from .auto_factory import get_values
   from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
   from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
   from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
   from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
   from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_auto import (
          MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
          MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
          MODEL_FOR_AUDIO_XVECTOR_MAPPING,
          MODEL_FOR_BACKBONE_MAPPING,
          MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
          MODEL_FOR_CAUSAL_LM_MAPPING,
          MODEL_FOR_CTC_MAPPING,
          MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
          MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
          MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
          MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
          MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
          MODEL_FOR_MASK_GENERATION_MAPPING,
          MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
          MODEL_FOR_MASKED_LM_MAPPING,
          MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
          MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
          MODEL_FOR_OBJECT_DETECTION_MAPPING,
          MODEL_FOR_PRETRAINING_MAPPING,
          MODEL_FOR_QUESTION_ANSWERING_MAPPING,
          MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
          MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
          MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
          MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
          MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
          MODEL_FOR_TEXT_ENCODING_MAPPING,
          MODEL_FOR_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,
          AutoModelForInstanceSegmentation,
          AutoModelForMaskedImageModeling,
          AutoModelForMaskedLM,
          AutoModelForMaskGeneration,
          AutoModelForMultipleChoice,
          AutoModelForNextSentencePrediction,
          AutoModelForObjectDetection,
          AutoModelForPreTraining,
          AutoModelForQuestionAnswering,
          AutoModelForSemanticSegmentation,
          AutoModelForSeqaSeqLM,
          AutoModelForSequenceClassification,
          AutoModelForSpeechSeqaSeq,
          AutoModelForTableQuestionAnswering,
          AutoModelForTextEncoding,
          AutoModelForTokenClassification,
          AutoModelForUniversalSegmentation,
          AutoModelForVideoClassification,
          AutoModelForVisionaSeq,
          AutoModelForVisualQuestionAnswering,
          AutoModelForZeroShotImageClassification,
          AutoModelForZeroShotObjectDetection,
          AutoModelWithLMHead,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_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,
          TFAutoModelForSeqaSeqLM,
          TFAutoModelForSequenceClassification,
          TFAutoModelForSpeechSeqaSeq,
          TFAutoModelForTableQuestionAnswering,
          TFAutoModelForTextEncoding,
          TFAutoModelForTokenClassification,
          TFAutoModelForVisionaSeq,
          TFAutoModelForZeroShotImageClassification,
          TFAutoModelWithLMHead,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_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,
          FlaxAutoModelForSeqaSeqLM,
          FlaxAutoModelForSequenceClassification,
          FlaxAutoModelForSpeechSeqaSeq,
          FlaxAutoModelForTokenClassification,
          FlaxAutoModelForVisionaSeq,
      )

else:
   import sys

   _UpperCAmelCase						:    Optional[int]     					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_UpperCAmelCase						:    Optional[Any]     					=					{
    '''configuration_unispeech_sat''': ['''UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechSatConfig'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    Dict     					=					[
       '''UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''UniSpeechSatForAudioFrameClassification''',
       '''UniSpeechSatForCTC''',
       '''UniSpeechSatForPreTraining''',
       '''UniSpeechSatForSequenceClassification''',
       '''UniSpeechSatForXVector''',
       '''UniSpeechSatModel''',
       '''UniSpeechSatPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_unispeech_sat import (
          UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
          UniSpeechSatForAudioFrameClassification,
          UniSpeechSatForCTC,
          UniSpeechSatForPreTraining,
          UniSpeechSatForSequenceClassification,
          UniSpeechSatForXVector,
          UniSpeechSatModel,
          UniSpeechSatPreTrainedModel,
      )

else:
   import sys

   _UpperCAmelCase						:    int     					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



