


import copy

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


A   =			logging.get_logger(__name__)

A   =			{
    "SenseTime/deformable-detr": "https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json",
    # See all Deformable DETR models at https://huggingface.co/models?filter=deformable-detr
}


class      lowercase__	(       __SCREAMING_SNAKE_CASE		):
  A__=	'''deformable_detr'''
  A__=	{
      '''hidden_size''': '''d_model''',
      '''num_attention_heads''': '''encoder_attention_heads''',
  }






  def __init__(       self   :       List[Any]		,    _lowercase   :       Tuple=True		,    _lowercase   :       Dict=None		,    _lowercase   :       Dict=3		,    _lowercase   :       str=3_00		,    _lowercase   :       Union[str, Any]=10_24		,    _lowercase   :       Tuple=6		,    _lowercase   :       Optional[int]=10_24		,    _lowercase   :       Any=8		,    _lowercase   :       Optional[Any]=6		,    _lowercase   :       int=10_24		,    _lowercase   :       List[Any]=8		,    _lowercase   :       Any=0.0		,    _lowercase   :       List[str]=True		,    _lowercase   :       Optional[Any]="relu"		,    _lowercase   :       List[Any]=2_56		,    _lowercase   :       Dict=0.1		,    _lowercase   :       Union[str, Any]=0.0		,    _lowercase   :       List[str]=0.0		,    _lowercase   :       str=0.0_2		,    _lowercase   :       List[Any]=1.0		,    _lowercase   :       List[str]=True		,    _lowercase   :       Union[str, Any]=False		,    _lowercase   :       Tuple="sine"		,    _lowercase   :       Dict="resnet50"		,    _lowercase   :       List[Any]=True		,    _lowercase   :       Dict=False		,    _lowercase   :       Optional[int]=4		,    _lowercase   :       int=4		,    _lowercase   :       Dict=4		,    _lowercase   :       Dict=False		,    _lowercase   :       Dict=3_00		,    _lowercase   :       Optional[int]=False		,    _lowercase   :       Any=1		,    _lowercase   :       Dict=5		,    _lowercase   :       int=2		,    _lowercase   :       Optional[Any]=1		,    _lowercase   :       Optional[Any]=1		,    _lowercase   :       str=5		,    _lowercase   :       Optional[Any]=2		,    _lowercase   :       str=0.1		,    _lowercase   :       List[str]=0.2_5		,    _lowercase   :       List[Any]=False		,    **_lowercase   :       Optional[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."			)
                       UpperCAmelCase__					    =  CONFIG_MAPPING['resnet'](out_features=["stage4"]			)
                elif isinstance(_lowercase		,    _lowercase			):
                       UpperCAmelCase__					    =  backbone_config.get("model_type"			)
                       UpperCAmelCase__					    =  CONFIG_MAPPING[backbone_model_type]
                       UpperCAmelCase__					    =  config_class.from_dict(_lowercase			)
         UpperCAmelCase__					    =  use_timm_backbone
         UpperCAmelCase__					    =  backbone_config
         UpperCAmelCase__					    =  num_channels
         UpperCAmelCase__					    =  num_queries
         UpperCAmelCase__					    =  max_position_embeddings
         UpperCAmelCase__					    =  d_model
         UpperCAmelCase__					    =  encoder_ffn_dim
         UpperCAmelCase__					    =  encoder_layers
         UpperCAmelCase__					    =  encoder_attention_heads
         UpperCAmelCase__					    =  decoder_ffn_dim
         UpperCAmelCase__					    =  decoder_layers
         UpperCAmelCase__					    =  decoder_attention_heads
         UpperCAmelCase__					    =  dropout
         UpperCAmelCase__					    =  attention_dropout
         UpperCAmelCase__					    =  activation_dropout
         UpperCAmelCase__					    =  activation_function
         UpperCAmelCase__					    =  init_std
         UpperCAmelCase__					    =  init_xavier_std
         UpperCAmelCase__					    =  encoder_layerdrop
         UpperCAmelCase__					    =  auxiliary_loss
         UpperCAmelCase__					    =  position_embedding_type
         UpperCAmelCase__					    =  backbone
         UpperCAmelCase__					    =  use_pretrained_backbone
         UpperCAmelCase__					    =  dilation
         # deformable attributes
         UpperCAmelCase__					    =  num_feature_levels
         UpperCAmelCase__					    =  encoder_n_points
         UpperCAmelCase__					    =  decoder_n_points
         UpperCAmelCase__					    =  two_stage
         UpperCAmelCase__					    =  two_stage_num_proposals
         UpperCAmelCase__					    =  with_box_refine
         if two_stage is True and with_box_refine is False:
                raise ValueError("If two_stage is True, with_box_refine must be True."			)
         # Hungarian matcher
         UpperCAmelCase__					    =  class_cost
         UpperCAmelCase__					    =  bbox_cost
         UpperCAmelCase__					    =  giou_cost
         # Loss coefficients
         UpperCAmelCase__					    =  mask_loss_coefficient
         UpperCAmelCase__					    =  dice_loss_coefficient
         UpperCAmelCase__					    =  bbox_loss_coefficient
         UpperCAmelCase__					    =  giou_loss_coefficient
         UpperCAmelCase__					    =  eos_coefficient
         UpperCAmelCase__					    =  focal_alpha
         UpperCAmelCase__					    =  disable_custom_kernels
         super().__init__(is_encoder_decoder=_lowercase		,    **_lowercase			)






  @property
  def       _UpperCAmelCase	(       self   :       Any			):




         """simple docstring"""







         return self.encoder_attention_heads






  @property
  def       _UpperCAmelCase	(       self   :       Union[str, Any]			):




         """simple docstring"""







         return self.d_model






  def       _UpperCAmelCase	(       self   :       List[Any]			):




         """simple docstring"""







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











'''simple docstring'''



class 							_a				:





       '''simple docstring'''






       def __init__(      self,							A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Tuple    					=						val
             SCREAMING_SNAKE_CASE   :      Any    					=						None
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						None







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             if self.val:
                   if val < self.val:
                         if self.left is None:
                               SCREAMING_SNAKE_CASE   :      Optional[int]    					=						Node(A  )
                         else:
                               self.left.insert(A  )
                   elif val > self.val:
                         if self.right is None:
                               SCREAMING_SNAKE_CASE   :      int    					=						Node(A  )
                         else:
                               self.right.insert(A  )
             else:
                   SCREAMING_SNAKE_CASE   :      int    					=						val




def   lowercase__(			__UpperCamelCase:					Optional[int]      ,__UpperCamelCase:					List[str]    ):

      """simple docstring"""






      if root:
            inorder(root.left      ,__UpperCamelCase    )
            res.append(root.val    )
            inorder(root.right      ,__UpperCamelCase    )




def   lowercase__(			__UpperCamelCase:					List[Any]    ):

      """simple docstring"""






      if len(__UpperCamelCase    ) == 0:
            return arr
      SCREAMING_SNAKE_CASE   :      Optional[int]    					=						Node(arr[0]    )
      for i in range(1      ,len(__UpperCamelCase    )    ):
            root.insert(arr[i]    )
      # Traverse BST in order.
      SCREAMING_SNAKE_CASE   :      Dict    					=						[]
      inorder(__UpperCamelCase      ,__UpperCamelCase    )
      return res


if __name__ == "__main__":
      print(tree_sort([1_0, 1, 3, 2, 9, 1_4, 1_3]))


