





from typing import TYPE_CHECKING

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


__UpperCAmelCase       :   int				       =							{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   List[Any]				       =							["GLPNFeatureExtractor"]
      __UpperCAmelCase       :   int				       =							["GLPNImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   List[Any]				       =							[
          "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
          "GLPNForDepthEstimation",
          "GLPNLayer",
          "GLPNModel",
          "GLPNPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_glpn import GLPNFeatureExtractor
            from .image_processing_glpn import GLPNImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_glpn import (
                GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                GLPNForDepthEstimation,
                GLPNLayer,
                GLPNModel,
                GLPNPreTrainedModel,
            )


else:
      import sys

      __UpperCAmelCase       :   List[str]				       =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)













import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


__UpperCAmelCase       :   Tuple				       =							logging.get_logger(__name__)







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       def __init__(  self :    Union[str, Any]							,				*A :    Union[str, Any]							,				**A :    Optional[int]		):
         warnings.warn(
             """The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
             """ Please use PerceiverImageProcessor instead."""							,				A							,				)
         super().__init__(*A							,				**A		)






