


"""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


UpperCAmelCase__  							=logging.get_logger(__name__)

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





class    lowerCamelCase__						(		_a    ):
      a :     Any											=		"""conditional_detr"""
      a :     Any											=		["""past_key_values"""]
      a :     List[Any]											=		{
          """hidden_size""": """d_model""",
          """num_attention_heads""": """encoder_attention_heads""",
      }
      def __init__(		self	:	Union[str, Any]      ,       A_	:	List[Any]=True      ,       A_	:	Optional[int]=None      ,       A_	:	Union[str, Any]=3      ,       A_	:	Any=3_0_0      ,       A_	:	str=6      ,       A_	:	str=2_0_4_8      ,       A_	:	Optional[int]=8      ,       A_	:	str=6      ,       A_	:	Any=2_0_4_8      ,       A_	:	Optional[int]=8      ,       A_	:	List[Any]=0.0      ,       A_	:	int=0.0      ,       A_	:	Optional[int]=True      ,       A_	:	List[Any]="relu"      ,       A_	:	Dict=2_5_6      ,       A_	:	List[Any]=0.1      ,       A_	:	Optional[int]=0.0      ,       A_	:	Optional[int]=0.0      ,       A_	:	Tuple=0.02      ,       A_	:	Optional[Any]=1.0      ,       A_	:	List[Any]=False      ,       A_	:	List[Any]="sine"      ,       A_	:	Optional[int]="resnet50"      ,       A_	:	str=True      ,       A_	:	Union[str, Any]=False      ,       A_	:	Optional[int]=2      ,       A_	:	List[Any]=5      ,       A_	:	Optional[Any]=2      ,       A_	:	Union[str, Any]=1      ,       A_	:	List[str]=1      ,       A_	:	Dict=2      ,       A_	:	Optional[int]=5      ,       A_	:	List[str]=2      ,       A_	:	Optional[int]=0.25      ,       **A_	:	Any      ,       ):






       '''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."""							)
         __lowercase									=	CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]							)
        elif isinstance(A_      ,       A_							):
         __lowercase									=	backbone_config.get("""model_type"""							)
         __lowercase									=	CONFIG_MAPPING[backbone_model_type]
         __lowercase									=	config_class.from_dict(A_							)

       __lowercase									=	use_timm_backbone
       __lowercase									=	backbone_config
       __lowercase									=	num_channels
       __lowercase									=	num_queries
       __lowercase									=	d_model
       __lowercase									=	encoder_ffn_dim
       __lowercase									=	encoder_layers
       __lowercase									=	encoder_attention_heads
       __lowercase									=	decoder_ffn_dim
       __lowercase									=	decoder_layers
       __lowercase									=	decoder_attention_heads
       __lowercase									=	dropout
       __lowercase									=	attention_dropout
       __lowercase									=	activation_dropout
       __lowercase									=	activation_function
       __lowercase									=	init_std
       __lowercase									=	init_xavier_std
       __lowercase									=	encoder_layerdrop
       __lowercase									=	decoder_layerdrop
       __lowercase									=	encoder_layers
       __lowercase									=	auxiliary_loss
       __lowercase									=	position_embedding_type
       __lowercase									=	backbone
       __lowercase									=	use_pretrained_backbone
       __lowercase									=	dilation
       # Hungarian matcher
       __lowercase									=	class_cost
       __lowercase									=	bbox_cost
       __lowercase									=	giou_cost
       # Loss coefficients
       __lowercase									=	mask_loss_coefficient
       __lowercase									=	dice_loss_coefficient
       __lowercase									=	cls_loss_coefficient
       __lowercase									=	bbox_loss_coefficient
       __lowercase									=	giou_loss_coefficient
       __lowercase									=	focal_alpha
       super().__init__(is_encoder_decoder=A_      ,       **A_							)
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[int]							):






       '''simple docstring'''


       return self.encoder_attention_heads
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Tuple							):






       '''simple docstring'''


       return self.d_model






      def SCREAMING_SNAKE_CASE_	(		self	:	Any							):






       '''simple docstring'''


       __lowercase									=	copy.deepcopy(self.__dict__							)
       if self.backbone_config is not None:
        __lowercase									=	self.backbone_config.to_dict()
       __lowercase									=	self.__class__.model_type
       return output






class    lowerCamelCase__						(		_a    ):
      a :     str											=		version.parse("""1.11"""    )
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       return OrderedDict(
           [
               ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
               ("""pixel_mask""", {0: """batch"""}),
           ]							)
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]							):






       '''simple docstring'''


       return 1e-5






      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Any							):






       '''simple docstring'''


       return 1_2




"""simple docstring"""

# Algorithm for the pigeonhole sorting




def lowerCAmelCase_      (				UpperCamelCase__	: Dict ):






 """simple docstring"""







 __lowercase									=	min(UpperCamelCase__ )  # min() finds the minimum value
 __lowercase									=	max(UpperCamelCase__ )  # max() finds the maximum value

 __lowercase									=	max_val - min_val + 1  # size is difference of max and min values plus one

 # list of pigeonholes of size equal to the variable size
 __lowercase									=	[0] * size

 # Populate the pigeonholes.
 for x in a:
  assert isinstance(UpperCamelCase__				,   UpperCamelCase__ ), "integers only please"
  holes[x - min_val] += 1

 # Putting the elements back into the array in an order.
 __lowercase									=	0
 for count in range(UpperCamelCase__ ):
  while holes[count] > 0:
   holes[count] -= 1
   __lowercase									=	count + min_val
   i += 1


def lowerCAmelCase_      (				):






 """simple docstring"""







 __lowercase									=	[8, 3, 2, 7, 4, 6, 8]
 pigeonhole_sort(UpperCamelCase__ )
 print("""Sorted order is:"""				,   """ """.join(UpperCamelCase__ ) )


if __name__ == "__main__":
       main()
