





from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__       :			Any			      =						{
    """configuration_chinese_clip""": [
        """CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ChineseCLIPConfig""",
        """ChineseCLIPOnnxConfig""",
        """ChineseCLIPTextConfig""",
        """ChineseCLIPVisionConfig""",
    ],
    """processing_chinese_clip""": ["""ChineseCLIPProcessor"""],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__       :			List[Any]			      =						["""ChineseCLIPFeatureExtractor"""]
  SCREAMING_SNAKE_CASE__       :			List[Any]			      =						["""ChineseCLIPImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__       :			List[str]			      =						[
      """CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ChineseCLIPModel""",
      """ChineseCLIPPreTrainedModel""",
      """ChineseCLIPTextModel""",
      """ChineseCLIPVisionModel""",
  ]

if TYPE_CHECKING:
  from .configuration_chinese_clip import (
      CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
      ChineseCLIPConfig,
      ChineseCLIPOnnxConfig,
      ChineseCLIPTextConfig,
      ChineseCLIPVisionConfig,
  )
  from .processing_chinese_clip import ChineseCLIPProcessor

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_chinese_clip import (
        CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
        ChineseCLIPModel,
        ChineseCLIPPreTrainedModel,
        ChineseCLIPTextModel,
        ChineseCLIPVisionModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE__       :			int			      =						logging.get_logger(__name__)







class   __lowerCAmelCase			(					_UpperCamelCase  ):
   _UpperCamelCase :						int     		=				"""upernet"""





   def __init__( self					,			snake_case=None					,			snake_case=512					,			snake_case=0.02					,			snake_case=[1, 2, 3, 6]					,			snake_case=True					,			snake_case=0.4					,			snake_case=384					,			snake_case=256					,			snake_case=1					,			snake_case=False					,			snake_case=255					,			**snake_case					,			)				->  Optional[Any]:
      """simple docstring"""





      super().__init__(**snake_case      )

      if backbone_config is None:
         logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."      )
         a__	:						List[str]      		=  CONFIG_MAPPING["resnet"](out_features=["stage1", "stage2", "stage3", "stage4"]      )
      elif isinstance(snake_case					,			snake_case      ):
         a__	:						Optional[int]      		=  backbone_config.get("model_type"      )
         a__	:						str      		=  CONFIG_MAPPING[backbone_model_type]
         a__	:						str      		=  config_class.from_dict(snake_case      )

      a__	:						int      		=  backbone_config
      a__	:						Optional[Any]      		=  hidden_size
      a__	:						Optional[Any]      		=  initializer_range
      a__	:						Tuple      		=  pool_scales
      a__	:						Optional[Any]      		=  use_auxiliary_head
      a__	:						Optional[Any]      		=  auxiliary_loss_weight
      a__	:						Dict      		=  auxiliary_in_channels
      a__	:						Optional[int]      		=  auxiliary_channels
      a__	:						Any      		=  auxiliary_num_convs
      a__	:						Any      		=  auxiliary_concat_input
      a__	:						int      		=  loss_ignore_index





   def 	_snake_case ( self      )				->  str:
      """simple docstring"""





      a__	:						Tuple      		=  copy.deepcopy(self.__dict__      )
      a__	:						Optional[Any]      		=  self.backbone_config.to_dict()
      a__	:						List[Any]      		=  self.__class__.model_type
      return output

