

"""simple docstring"""
import copy
from typing import Dict

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


A									=						logging.get_logger(__name__)

A									=						{
    "google/vit-hybrid-base-bit-384": "https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}

class        _UpperCamelCase	(						_a	):


  """simple docstring"""





  snake_case_        =    "vit-hybrid"



  def __init__( self					: Union[str, Any]       ,       snake_case					: Tuple=None       ,       snake_case					: str=768       ,       snake_case					: Union[str, Any]=12       ,       snake_case					: str=12       ,       snake_case					: Dict=3072       ,       snake_case					: Union[str, Any]="gelu"       ,       snake_case					: Optional[int]=0.0       ,       snake_case					: Any=0.0       ,       snake_case					: Optional[Any]=0.02       ,       snake_case					: Union[str, Any]=1e-12       ,       snake_case					: Any=224       ,       snake_case					: int=1       ,       snake_case					: int=3       ,       snake_case					: Any=[1, 1024, 24, 24]       ,       snake_case					: Optional[Any]=True       ,       **snake_case					: Optional[Any]       ,       )	->			List[Any]:


         '''simple docstring'''





         super().__init__(**snake_case      )

         if backbone_config is None:
                logger.info('''`backbone_config` is `None`. Initializing the config with a `BiT` backbone.'''      )
                __magic_name__			:		List[str]        =     {
                    '''global_padding''': '''same''',
                    '''layer_type''': '''bottleneck''',
                    '''depths''': [3, 4, 9],
                    '''out_features''': ['''stage3'''],
                    '''embedding_dynamic_padding''': True,
                }

         if isinstance(snake_case       ,       snake_case      ):
                if "model_type" in backbone_config:
                       __magic_name__			:		Any        =     CONFIG_MAPPING[backbone_config['''model_type''']]
                else:
                       logger.info(
                           '''`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class.'''      )
                       __magic_name__			:		Tuple        =     BitConfig
                __magic_name__			:		Tuple        =     backbone_config_class(**snake_case      )

         __magic_name__			:		Any        =     backbone_featmap_shape
         __magic_name__			:		Tuple        =     backbone_config
         __magic_name__			:		Dict        =     hidden_size
         __magic_name__			:		List[str]        =     num_hidden_layers
         __magic_name__			:		List[str]        =     num_attention_heads
         __magic_name__			:		int        =     intermediate_size
         __magic_name__			:		str        =     hidden_act
         __magic_name__			:		Tuple        =     hidden_dropout_prob
         __magic_name__			:		Tuple        =     attention_probs_dropout_prob
         __magic_name__			:		Dict        =     initializer_range
         __magic_name__			:		Tuple        =     layer_norm_eps
         __magic_name__			:		List[str]        =     image_size
         __magic_name__			:		Tuple        =     patch_size
         __magic_name__			:		Optional[int]        =     num_channels
         __magic_name__			:		Any        =     qkv_bias




  def 							_UpperCAmelCase      ( self					: int      )	->			Dict[str, any]:


         '''simple docstring'''





         __magic_name__			:		int        =     copy.deepcopy(self.__dict__      )
         __magic_name__			:		Union[str, Any]        =     self.backbone_config.to_dict()
         __magic_name__			:		str        =     self.__class__.model_type
         return output




'''simple docstring'''



def       _a      (		_lowercase   :      list    ):





     '''simple docstring'''






     if len(_lowercase    ) <= 1:
          return data
     else:
          return [
              *quick_sort([e for e in data[1:] if e <= data[0]]    ),
              data[0],
              *quick_sort([e for e in data[1:] if e > data[0]]    ),
          ]


if __name__ == "__main__":
      import doctest

      doctest.testmod()