"""simple docstring"""



import copy
from collections import OrderedDict
from typing import Dict, Mapping

from packaging import version

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


SCREAMING_SNAKE_CASE__:List[Any]			=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__:Optional[Any]			=	{
    """facebook/detr-resnet-50""": """https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json""",
    # See all DETR models at https://huggingface.co/models?filter=detr
}






class 				snake_case__     (   snake_case_   ):
 _snake_case   :			Tuple           =		"""detr"""
 _snake_case   :			Dict           =		["""past_key_values"""]
 _snake_case   :			List[Any]           =		{
     """hidden_size""": """d_model""",
     """num_attention_heads""": """encoder_attention_heads""",
 }


 def __init__(				self  ,						lowerCamelCase=True  ,						lowerCamelCase=None  ,						lowerCamelCase=3  ,						lowerCamelCase=100  ,						lowerCamelCase=6  ,						lowerCamelCase=2048  ,						lowerCamelCase=8  ,						lowerCamelCase=6  ,						lowerCamelCase=2048  ,						lowerCamelCase=8  ,						lowerCamelCase=0.0  ,						lowerCamelCase=0.0  ,						lowerCamelCase=True  ,						lowerCamelCase="relu"  ,						lowerCamelCase=256  ,						lowerCamelCase=0.1  ,						lowerCamelCase=0.0  ,						lowerCamelCase=0.0  ,						lowerCamelCase=0.02  ,						lowerCamelCase=1.0  ,						lowerCamelCase=False  ,						lowerCamelCase="sine"  ,						lowerCamelCase="resnet50"  ,						lowerCamelCase=True  ,						lowerCamelCase=False  ,						lowerCamelCase=1  ,						lowerCamelCase=5  ,						lowerCamelCase=2  ,						lowerCamelCase=1  ,						lowerCamelCase=1  ,						lowerCamelCase=5  ,						lowerCamelCase=2  ,						lowerCamelCase=0.1  ,						**lowerCamelCase  ,						):
        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."		)
                      __a     				=  CONFIG_MAPPING["resnet"](out_features=["stage4"]		)
               elif isinstance(lowerCamelCase  ,						lowerCamelCase		):
                      __a     				=  backbone_config.get("model_type"		)
                      __a     				=  CONFIG_MAPPING[backbone_model_type]
                      __a     				=  config_class.from_dict(lowerCamelCase		)
               # set timm attributes to None
               __a				, __a				, __a     				=  None, None, None

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


 @property
 def 		a__ (				self		):
        return self.encoder_attention_heads


 @property
 def 		a__ (				self		):
        return self.d_model


 @classmethod
 def 		a__ (				cls  ,						lowerCamelCase  ,						**lowerCamelCase		):
        return cls(backbone_config=lowerCamelCase  ,						**lowerCamelCase		)






 def 		a__ (				self		):
        __a     				=  copy.deepcopy(self.__dict__		)
        if output["backbone_config"] is not None:
               __a     				=  self.backbone_config.to_dict()
        __a     				=  self.__class__.model_type
        return output






class 				snake_case__     (   snake_case_   ):
 _snake_case   :			List[Any]           =		version.parse("""1.11"""   )


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


 @property
 def 		a__ (				self		):
        return 1E-5






 @property
 def 		a__ (				self		):
        return 12

"""simple docstring"""



def 					_lowerCamelCase(					a							):
       __a     				=  len(a							)
       for i in range(1 ,  a							):
              __a     				=  collection[i]
              __a     				=  0
              __a     				=  i - 1

              while low <= high:
                     __a     				=  (low + high) // 2
                     if val < collection[mid]:
                            __a     				=  mid - 1
                     else:
                            __a     				=  mid + 1
              for j in range(a ,  a ,  -1							):
                     __a     				=  collection[j - 1]
              __a     				=  val
       return collection


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE__:str			=	input("""Enter numbers separated by a comma:\n""").strip()
   SCREAMING_SNAKE_CASE__:Any			=	[int(item) for item in user_input.split(""",""")]
   print(binary_insertion_sort(unsorted))
