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


lowerCAmelCase__     						=			logging.get_logger(__name__)

lowerCAmelCase__     						=			{
    'microsoft/conditional-detr-resnet-50': (
        'https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'
    ),
}
class     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_     			= 'conditional_detr'
 UpperCAmelCase_     			= ['past_key_values']
 UpperCAmelCase_     			= {
     'hidden_size': 'd_model',
     'num_attention_heads': 'encoder_attention_heads',
 }




 def __init__(      self :  Dict      ,   lowercase__ :  Any=True      ,   lowercase__ :  Optional[Any]=None      ,   lowercase__ :  List[str]=3      ,   lowercase__ :  str=300      ,   lowercase__ :  List[str]=6      ,   lowercase__ :  Dict=2_048      ,   lowercase__ :  List[Any]=8      ,   lowercase__ :  Optional[Any]=6      ,   lowercase__ :  Union[str, Any]=2_048      ,   lowercase__ :  Union[str, Any]=8      ,   lowercase__ :  int=0.0      ,   lowercase__ :  Dict=0.0      ,   lowercase__ :  Optional[int]=True      ,   lowercase__ :  Optional[int]="relu"      ,   lowercase__ :  int=256      ,   lowercase__ :  Optional[int]=0.1      ,   lowercase__ :  int=0.0      ,   lowercase__ :  Any=0.0      ,   lowercase__ :  Tuple=0.02      ,   lowercase__ :  Union[str, Any]=1.0      ,   lowercase__ :  Dict=False      ,   lowercase__ :  Dict="sine"      ,   lowercase__ :  Union[str, Any]="resnet50"      ,   lowercase__ :  List[Any]=True      ,   lowercase__ :  Any=False      ,   lowercase__ :  str=2      ,   lowercase__ :  Union[str, Any]=5      ,   lowercase__ :  str=2      ,   lowercase__ :  Tuple=1      ,   lowercase__ :  List[str]=1      ,   lowercase__ :  Tuple=2      ,   lowercase__ :  List[Any]=5      ,   lowercase__ :  Dict=2      ,   lowercase__ :  Optional[int]=0.25      ,   **lowercase__ :  Tuple      ,   ):







        '''simple docstring'''



        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(lowercase__      ,   lowercase__):
                      lowerCAmelCase__					     = backbone_config.get('model_type')
                      lowerCAmelCase__					     = CONFIG_MAPPING[backbone_model_type]
                      lowerCAmelCase__					     = config_class.from_dict(lowercase__)

        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=lowercase__      ,   **lowercase__)




 @property
 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        return self.encoder_attention_heads




 @property
 def 		__snake_case						(      self :  Optional[Any]):







        '''simple docstring'''



        return self.d_model




 def 		__snake_case						(      self :  Optional[int]):







        '''simple docstring'''



        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     a_			(						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_     			= version.parse('1.11'						)




 @property
 def 		__snake_case						(      self :  int):







        '''simple docstring'''



        return OrderedDict(
            [
                ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
                ('pixel_mask', {0: 'batch'}),
            ])




 @property
 def 		__snake_case						(      self :  Optional[Any]):







        '''simple docstring'''



        return 1e-5




 @property
 def 		__snake_case						(      self :  str):







        '''simple docstring'''



        return 12

from math import log

from scipy.constants import Boltzmann, physical_constants

lowerCAmelCase__     						=			300  # TEMPERATURE (unit = K)






def 				__lowerCamelCase		(						lowerCAmelCase__     ,  lowerCAmelCase__     ,  lowerCAmelCase__     ,  ):

       if donor_conc <= 0:
              raise ValueError('Donor concentration should be positive'     )
       elif acceptor_conc <= 0:
              raise ValueError('Acceptor concentration should be positive'     )
       elif intrinsic_conc <= 0:
              raise ValueError('Intrinsic concentration should be positive'     )
       elif donor_conc <= intrinsic_conc:
              raise ValueError(
                  'Donor concentration should be greater than intrinsic concentration'     )
       elif acceptor_conc <= intrinsic_conc:
              raise ValueError(
                  'Acceptor concentration should be greater than intrinsic concentration'     )
       else:
              return (
                  Boltzmann
                  * T
                  * log((donor_conc * acceptor_conc) / intrinsic_conc**2     )
                  / physical_constants["electron volt"][0]
              )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
