





'''simple docstring'''






import copy
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


A__    :       List[str]              =logging.get_logger(__name__)

A__    :       Tuple              ={
    '''microsoft/conditional-detr-resnet-50''': (
        '''https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'''
    ),
}




class 			UpperCAmelCase					(      snake_case_       ):
 _lowercase:      Optional[Any]											=       '''conditional_detr'''
 _lowercase:      Optional[int]											=       ['''past_key_values''']
 _lowercase:      int											=       {
     '''hidden_size''': '''d_model''',
     '''num_attention_heads''': '''encoder_attention_heads''',
 }




 def __init__(      self      :			Optional[int]      ,      __snake_case      :			Tuple=True      ,      __snake_case      :			Any=None      ,      __snake_case      :			str=3      ,      __snake_case      :			int=3_00      ,      __snake_case      :			Dict=6      ,      __snake_case      :			Optional[int]=20_48      ,      __snake_case      :			Dict=8      ,      __snake_case      :			List[str]=6      ,      __snake_case      :			Tuple=20_48      ,      __snake_case      :			Optional[int]=8      ,      __snake_case      :			Optional[int]=0.0      ,      __snake_case      :			Tuple=0.0      ,      __snake_case      :			Union[str, Any]=True      ,      __snake_case      :			Dict="relu"      ,      __snake_case      :			List[Any]=2_56      ,      __snake_case      :			List[str]=0.1      ,      __snake_case      :			Tuple=0.0      ,      __snake_case      :			Optional[int]=0.0      ,      __snake_case      :			Optional[int]=0.02      ,      __snake_case      :			Union[str, Any]=1.0      ,      __snake_case      :			List[Any]=False      ,      __snake_case      :			Any="sine"      ,      __snake_case      :			Optional[int]="resnet50"      ,      __snake_case      :			List[str]=True      ,      __snake_case      :			Optional[int]=False      ,      __snake_case      :			int=2      ,      __snake_case      :			Optional[int]=5      ,      __snake_case      :			Union[str, Any]=2      ,      __snake_case      :			str=1      ,      __snake_case      :			Optional[Any]=1      ,      __snake_case      :			List[str]=2      ,      __snake_case      :			Optional[int]=5      ,      __snake_case      :			Union[str, Any]=2      ,      __snake_case      :			List[str]=0.25      ,      **__snake_case      :			Union[str, Any]      ,      )    ->				str:
       if backbone_config is not None and use_timm_backbone:
             raise ValueError("""You can't specify both `backbone_config` and `use_timm_backbone`."""  )

       if not use_timm_backbone:
             if backbone_config is None:
                   logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""  )
                   _lowerCAmelCase												=							CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]  )
             elif isinstance(__snake_case      ,      __snake_case  ):
                   _lowerCAmelCase												=							backbone_config.get("""model_type"""  )
                   _lowerCAmelCase												=							CONFIG_MAPPING[backbone_model_type]
                   _lowerCAmelCase												=							config_class.from_dict(__snake_case  )

       _lowerCAmelCase												=							use_timm_backbone
       _lowerCAmelCase												=							backbone_config
       _lowerCAmelCase												=							num_channels
       _lowerCAmelCase												=							num_queries
       _lowerCAmelCase												=							d_model
       _lowerCAmelCase												=							encoder_ffn_dim
       _lowerCAmelCase												=							encoder_layers
       _lowerCAmelCase												=							encoder_attention_heads
       _lowerCAmelCase												=							decoder_ffn_dim
       _lowerCAmelCase												=							decoder_layers
       _lowerCAmelCase												=							decoder_attention_heads
       _lowerCAmelCase												=							dropout
       _lowerCAmelCase												=							attention_dropout
       _lowerCAmelCase												=							activation_dropout
       _lowerCAmelCase												=							activation_function
       _lowerCAmelCase												=							init_std
       _lowerCAmelCase												=							init_xavier_std
       _lowerCAmelCase												=							encoder_layerdrop
       _lowerCAmelCase												=							decoder_layerdrop
       _lowerCAmelCase												=							encoder_layers
       _lowerCAmelCase												=							auxiliary_loss
       _lowerCAmelCase												=							position_embedding_type
       _lowerCAmelCase												=							backbone
       _lowerCAmelCase												=							use_pretrained_backbone
       _lowerCAmelCase												=							dilation
       # Hungarian matcher
       _lowerCAmelCase												=							class_cost
       _lowerCAmelCase												=							bbox_cost
       _lowerCAmelCase												=							giou_cost
       # Loss coefficients
       _lowerCAmelCase												=							mask_loss_coefficient
       _lowerCAmelCase												=							dice_loss_coefficient
       _lowerCAmelCase												=							cls_loss_coefficient
       _lowerCAmelCase												=							bbox_loss_coefficient
       _lowerCAmelCase												=							giou_loss_coefficient
       _lowerCAmelCase												=							focal_alpha
       super().__init__(is_encoder_decoder=__snake_case      ,      **__snake_case  )




 @property
 def     lowercase__   (      self      :			Any  )    ->				int:
       return self.encoder_attention_heads




 @property
 def     lowercase__   (      self      :			Optional[Any]  )    ->				int:
       return self.d_model




 def     lowercase__   (      self      :			int  )    ->				int:
       _lowerCAmelCase												=							copy.deepcopy(self.__dict__  )
       if self.backbone_config is not None:
             _lowerCAmelCase												=							self.backbone_config.to_dict()
       _lowerCAmelCase												=							self.__class__.model_type
       return output




class 			UpperCAmelCase					(      snake_case_       ):
 _lowercase:      Tuple											=       version.parse('''1.11'''       )




 @property
 def     lowercase__   (      self      :			str  )    ->				Mapping[str, Mapping[int, str]]:
       return OrderedDict(
           [
               ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
               ("""pixel_mask""", {0: """batch"""}),
           ]  )




 @property
 def     lowercase__   (      self      :			Optional[int]  )    ->				float:
       return 1E-5




 @property
 def     lowercase__   (      self      :			Any  )    ->				int:
       return 12













'''simple docstring'''






def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      if len(lowerCAmelCase  ) != len(lowerCAmelCase  ):
            raise ValueError("""String lengths must match!"""  )

      _lowerCAmelCase												=							0

      for chara, chara in zip(lowerCAmelCase							,     lowerCAmelCase  ):
            if chara != chara:
                  count += 1

      return count


if __name__ == "__main__":
      import doctest

      doctest.testmod()






