





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       :				Tuple           =			{
    """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(		_lowerCamelCase):

  """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    ,							)->   str:
     super().__init__(**__lowerCamelCase      )

     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(__lowerCamelCase    ,							__lowerCamelCase      ):
        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(**__lowerCamelCase      )

     __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









'''simple docstring'''





def  lowerCamelCase_  (     lowercase__					,  lowercase__):
 lowerCamelCase__	=  len(lowercase__)
 lowerCamelCase__	=  len(lowercase__)
 lowerCamelCase__	=  (
     first_input_list_length
     if first_input_list_length > second_input_list_length
     else second_input_list_length
 )
 lowerCamelCase__	=  []
 for char_count in range(lowercase__):
  if char_count < first_input_list_length:
   output_result_list.append(first_input_list[char_count])
  if char_count < second_input_list_length:
   output_result_list.append(second_input_list[char_count])

 return output_result_list


if __name__ == "__main__":
 print(alternative_list_arrange(["""A""", """B""", """C"""], [1, 2, 3, 4, 5]), end=""" """)

