






"""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 						__lowerCAmelCase   (			UpperCAmelCase       ):







  '''simple docstring'''


  __lowerCamelCase       :    Dict     	=			"vit-hybrid"
  def __init__(      self:		int				,			UpperCamelCase_:		str=None				,			UpperCamelCase_:		Any=768				,			UpperCamelCase_:		Dict=12				,			UpperCamelCase_:		List[str]=12				,			UpperCamelCase_:		Optional[int]=3072				,			UpperCamelCase_:		Tuple="gelu"				,			UpperCamelCase_:		int=0.0				,			UpperCamelCase_:		int=0.0				,			UpperCamelCase_:		Union[str, Any]=0.02				,			UpperCamelCase_:		Optional[int]=1e-1_2				,			UpperCamelCase_:		List[str]=224				,			UpperCamelCase_:		Union[str, Any]=1				,			UpperCamelCase_:		str=3				,			UpperCamelCase_:		Tuple=[1, 1024, 24, 24]				,			UpperCamelCase_:		str=True				,			**UpperCamelCase_:		Any				,			):
     super().__init__(**UpperCamelCase_					)

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

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

     UpperCamelCase_     =backbone_featmap_shape
     UpperCamelCase_     =backbone_config
     UpperCamelCase_     =hidden_size
     UpperCamelCase_     =num_hidden_layers
     UpperCamelCase_     =num_attention_heads
     UpperCamelCase_     =intermediate_size
     UpperCamelCase_     =hidden_act
     UpperCamelCase_     =hidden_dropout_prob
     UpperCamelCase_     =attention_probs_dropout_prob
     UpperCamelCase_     =initializer_range
     UpperCamelCase_     =layer_norm_eps
     UpperCamelCase_     =image_size
     UpperCamelCase_     =patch_size
     UpperCamelCase_     =num_channels
     UpperCamelCase_     =qkv_bias





  def 					UpperCamelCase__   (      self:		List[Any]					):
     UpperCamelCase_     =copy.deepcopy(self.__dict__					)
     UpperCamelCase_     =self.backbone_config.to_dict()
     UpperCamelCase_     =self.__class__.model_type
     return output














"""simple docstring"""






from collections import defaultdict




def 						_UpperCamelCase			(  A = 5			):
   UpperCamelCase_     =defaultdict(A			)
   UpperCamelCase_     =0

   while True:
      UpperCamelCase_     =get_digits(A			)
      freqs[digits].append(A			)

      if len(freqs[digits]			) == max_base:
         UpperCamelCase_     =freqs[digits][0] ** 3
         return base

      num += 1




def 						_UpperCamelCase			(  A			):
   return "".join(sorted(str(num**3			)			)			)


if __name__ == "__main__":
    print(f'''{solution() = }''')
