


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_snake_case					=					{
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _snake_case					=					['''FlavaFeatureExtractor''']
      _snake_case					=					['''FlavaImageProcessor''']
      _snake_case					=					['''FlavaProcessor''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _snake_case					=					[
          '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''FlavaForPreTraining''',
          '''FlavaImageCodebook''',
          '''FlavaImageModel''',
          '''FlavaModel''',
          '''FlavaMultimodalModel''',
          '''FlavaPreTrainedModel''',
          '''FlavaTextModel''',
      ]

if TYPE_CHECKING:
      from .configuration_flava import (
          FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
          FlavaConfig,
          FlavaImageCodebookConfig,
          FlavaImageConfig,
          FlavaMultimodalConfig,
          FlavaTextConfig,
      )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_flava import FlavaFeatureExtractor
            from .image_processing_flava import FlavaImageProcessor
            from .processing_flava import FlavaProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flava import (
                FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
                FlavaForPreTraining,
                FlavaImageCodebook,
                FlavaImageModel,
                FlavaModel,
                FlavaMultimodalModel,
                FlavaPreTrainedModel,
                FlavaTextModel,
            )

else:
      import sys

      _snake_case					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_snake_case					=					{'''configuration_hubert''': ['''HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''HubertConfig''']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''HubertForCTC''',
       '''HubertForSequenceClassification''',
       '''HubertModel''',
       '''HubertPreTrainedModel''',
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFHubertForCTC''',
       '''TFHubertModel''',
       '''TFHubertPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_hubert import (
          HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          HubertForCTC,
          HubertForSequenceClassification,
          HubertModel,
          HubertPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_hubert import (
          TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFHubertForCTC,
          TFHubertModel,
          TFHubertPreTrainedModel,
      )


else:
   import sys

   _snake_case					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



