





from typing import TYPE_CHECKING

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


lowercase    : int    	=  {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase    : int    	=  ["""DPTFeatureExtractor"""]
       lowercase    : int    	=  ["""DPTImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase    : List[Any]    	=  [
           """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """DPTForDepthEstimation""",
           """DPTForSemanticSegmentation""",
           """DPTModel""",
           """DPTPreTrainedModel""",
       ]


if TYPE_CHECKING:
       from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_dpt import DPTFeatureExtractor
              from .image_processing_dpt import DPTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dpt import (
                  DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPTForDepthEstimation,
                  DPTForSemanticSegmentation,
                  DPTModel,
                  DPTPreTrainedModel,
              )


else:
       import sys

       lowercase    : int    	=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


lowercase    : str    	=  logging.get_logger(__name__)

class  __A(						__UpperCAmelCase ):

     def __init__(      self,       *A,       **A      ):





            """simple docstring"""

            warnings.warn(
                '''The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
                ''' use CLIPImageProcessor instead.''',       A,       )
            super().__init__(*A,       **A      )






