


from typing import TYPE_CHECKING

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


_A			=						{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						['OwlViTFeatureExtractor']
   _A			=						['OwlViTImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'OwlViTModel',
       'OwlViTPreTrainedModel',
       'OwlViTTextModel',
       'OwlViTVisionModel',
       'OwlViTForObjectDetection',
   ]

if TYPE_CHECKING:
   from .configuration_owlvit import (
       OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       OwlViTConfig,
       OwlViTOnnxConfig,
       OwlViTTextConfig,
       OwlViTVisionConfig,
   )
   from .processing_owlvit import OwlViTProcessor

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_owlvit import OwlViTFeatureExtractor
      from .image_processing_owlvit import OwlViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_owlvit import (
          OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          OwlViTForObjectDetection,
          OwlViTModel,
          OwlViTPreTrainedModel,
          OwlViTTextModel,
          OwlViTVisionModel,
      )

else:
   import sys

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










import warnings

from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor


_A			=						logging.get_logger(__name__)






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    def __init__(      self ,       *A_ ,       **A_   )  ->	None:
         warnings.warn(
             'The class ImageGPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
             ' Please use ImageGPTImageProcessor instead.' ,       A_ ,       )
         super().__init__(*A_ ,       **A_   )





