





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


_UpperCamelCase       :				Dict           =			logging.get_logger(__name__)

_UpperCamelCase       :				Optional[int]           =			{
    """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(		_a):

  """simple docstring"""







  lowerCamelCase__     	=       '''vit-hybrid'''

  def __init__(   self    ,							UpperCAmelCase=None    ,							UpperCAmelCase=7_68    ,							UpperCAmelCase=12    ,							UpperCAmelCase=12    ,							UpperCAmelCase=30_72    ,							UpperCAmelCase="gelu"    ,							UpperCAmelCase=0.0    ,							UpperCAmelCase=0.0    ,							UpperCAmelCase=0.02    ,							UpperCAmelCase=1e-12    ,							UpperCAmelCase=2_24    ,							UpperCAmelCase=1    ,							UpperCAmelCase=3    ,							UpperCAmelCase=[1, 10_24, 24, 24]    ,							UpperCAmelCase=True    ,							**UpperCAmelCase    ,							)->   Optional[Any]:
     super().__init__(**UpperCAmelCase      )

     if backbone_config is None:
        logger.info('''`backbone_config` is `None`. Initializing the config with a `BiT` backbone.'''      )
        __A    =  {
            '''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:
           __A    =  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    =  BitConfig
        __A    =  backbone_config_class(**UpperCAmelCase      )

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





  def 						SCREAMING_SNAKE_CASE__			(   self      )->   Dict[str, any]:
     __A    =  copy.deepcopy(self.__dict__      )
     __A    =  self.backbone_config.to_dict()
     __A    =  self.__class__.model_type
     return output








class 		_lowerCAmelCase:

  """simple docstring"""







  def __init__(   self      )->   None:
     # numbermap keys are the number and its values are lists of indexes sorted
     # in ascending order
     __A    =  {}
     # indexmap keys are an index and it's values are the number at that index
     __A    =  {}

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   list[int]:
     if isinstance(UpperCAmelCase    ,							(range, str)      ):
        __A    =  list(UpperCAmelCase      )
     elif not isinstance(UpperCAmelCase    ,							UpperCAmelCase      ):
        raise TypeError(
            '''binary_search_delete() only accepts either a list, range or str'''      )

     __A    =  0
     __A    =  len(UpperCAmelCase      ) - 1

     while low <= high:
        __A    =  (low + high) // 2
        if array[mid] == item:
           array.pop(UpperCAmelCase      )
           return array
        elif array[mid] < item:
           __A    =  mid + 1
        else:
           __A    =  mid - 1
     raise ValueError(
         '''Either the item is not in the array or the array was unsorted'''      )

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   list[int]:
     if isinstance(UpperCAmelCase    ,							(range, str)      ):
        __A    =  list(UpperCAmelCase      )
     elif not isinstance(UpperCAmelCase    ,							UpperCAmelCase      ):
        raise TypeError(
            '''binary_search_insert() only accepts either a list, range or str'''      )

     __A    =  0
     __A    =  len(UpperCAmelCase      ) - 1

     while low <= high:
        __A    =  (low + high) // 2
        if array[mid] == index:
           # If the item already exists in the array,
           # insert it after the existing item
           array.insert(mid + 1    ,							UpperCAmelCase      )
           return array
        elif array[mid] < index:
           __A    =  mid + 1
        else:
           __A    =  mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
     array.insert(UpperCAmelCase    ,							UpperCAmelCase      )
     return array

  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase    ,							UpperCAmelCase      )->   None:
     # Remove previous index
     if index in self.indexmap:
        __A    =  self.indexmap[index]
        if len(self.numbermap[n]      ) == 1:
           del self.numbermap[n]
        else:
           __A    =  self.binary_search_delete(self.numbermap[n]    ,							UpperCAmelCase      )

        # Set new index
     __A    =  number

     # Number not seen before or empty so insert number value
     if number not in self.numbermap:
        __A    =  [index]

     # Here we need to perform a binary search insertion in order to insert
     # The item in the correct place
     else:
        __A    =  self.binary_search_insert(
            self.numbermap[number]    ,							UpperCAmelCase      )





  def 						SCREAMING_SNAKE_CASE__			(   self    ,							UpperCAmelCase      )->   int:
     return self.numbermap.get(UpperCAmelCase    ,							[-1]      )[0]


if __name__ == "__main__":
    import doctest

    doctest.testmod()

