


'''simple docstring'''







from __future__ import annotations


def      SCREAMING_SNAKE_CASE_ (  _UpperCAmelCase     :     list   ,_UpperCAmelCase     :     list  )  ->      list:
       _a   :			Union[str, Any]					 =[None] * (len(_UpperCAmelCase  ) + len(_UpperCAmelCase  ))

       _a   :			Tuple					 =0  # pointer to current index for left Half
       _a   :			Any					 =0  # pointer to current index for the right Half
       _a   :			int					 =0  # pointer to current index for the sorted array Half

       while pointera < len(_UpperCAmelCase  ) and pointera < len(_UpperCAmelCase  ):
              if left_half[pointera] < right_half[pointera]:
                     _a   :			int					 =left_half[pointera]
                     pointera += 1
                     index += 1
              else:
                     _a   :			Optional[Any]					 =right_half[pointera]
                     pointera += 1
                     index += 1
       while pointera < len(_UpperCAmelCase  ):
              _a   :			Optional[int]					 =left_half[pointera]
              pointera += 1
              index += 1

       while pointera < len(_UpperCAmelCase  ):
              _a   :			Dict					 =right_half[pointera]
              pointera += 1
              index += 1

       return sorted_array


def      SCREAMING_SNAKE_CASE_ (  _UpperCAmelCase     :     list  )  ->      list:
       if len(_UpperCAmelCase  ) <= 1:
              return array
       # the actual formula to calculate the middle element = left + (right - left) // 2
       # this avoids integer overflow in case of large N
       _a   :			Any					 =0 + (len(_UpperCAmelCase  ) - 0) // 2

       # Split the array into halves till the array length becomes equal to One
       # merge the arrays of single length returned by mergeSort function and
       # pass them into the merge arrays function which merges the array
       _a   :			Optional[int]					 =array[:middle]
       _a   :			Tuple					 =array[middle:]

       return merge(merge_sort(_UpperCAmelCase  )   ,merge_sort(_UpperCAmelCase  )  )


if __name__ == "__main__":
   import doctest

   doctest.testmod()






'''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__:   List[Any]    =	logging.get_logger(__name__)

A__:   List[Any]    =	{
    '''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 A__	(						UpperCAmelCase__				):
      __UpperCamelCase	:  Dict     	=							"vit-hybrid"






      def __init__(			self      :List[Any]					,						SCREAMING_SNAKE_CASE      :Dict=None					,						SCREAMING_SNAKE_CASE      :Any=7_6_8					,						SCREAMING_SNAKE_CASE      :Optional[Any]=1_2					,						SCREAMING_SNAKE_CASE      :int=1_2					,						SCREAMING_SNAKE_CASE      :Any=3_0_7_2					,						SCREAMING_SNAKE_CASE      :List[str]="gelu"					,						SCREAMING_SNAKE_CASE      :str=0.0					,						SCREAMING_SNAKE_CASE      :Dict=0.0					,						SCREAMING_SNAKE_CASE      :Dict=0.02					,						SCREAMING_SNAKE_CASE      :Tuple=1e-12					,						SCREAMING_SNAKE_CASE      :List[Any]=2_2_4					,						SCREAMING_SNAKE_CASE      :Union[str, Any]=1					,						SCREAMING_SNAKE_CASE      :List[Any]=3					,						SCREAMING_SNAKE_CASE      :Optional[Any]=[1, 1_0_2_4, 2_4, 2_4]					,						SCREAMING_SNAKE_CASE      :Optional[Any]=True					,						**SCREAMING_SNAKE_CASE      :Dict					,						)	-> List[Any]:




             '''simple docstring'''
             super().__init__(**SCREAMING_SNAKE_CASE     )

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

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

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






      def __UpperCAmelCase	(			self      :Optional[Any]     )	-> Dict[str, any]:




             '''simple docstring'''
             _a   :			Dict					 =copy.deepcopy(self.__dict__     )
             _a   :			Tuple					 =self.backbone_config.to_dict()
             _a   :			str					 =self.__class__.model_type
             return output


