



'''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


_UpperCamelCase											=						logging.get_logger(__name__)

_UpperCamelCase											=						{
    '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 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




  a_												="""detr"""
  a_												=["""past_key_values"""]
  a_												={
      """hidden_size""": """d_model""",
      """num_attention_heads""": """encoder_attention_heads""",
  }




  def __init__( self      :	List[Any]			,	_a      :	List[Any]=True			,	_a      :	Union[str, Any]=None			,	_a      :	List[str]=3			,	_a      :	Dict=100			,	_a      :	Optional[int]=6			,	_a      :	Union[str, Any]=2048			,	_a      :	Union[str, Any]=8			,	_a      :	int=6			,	_a      :	List[str]=2048			,	_a      :	Dict=8			,	_a      :	Dict=0.0			,	_a      :	Union[str, Any]=0.0			,	_a      :	str=True			,	_a      :	Dict="relu"			,	_a      :	Dict=256			,	_a      :	Optional[int]=0.1			,	_a      :	int=0.0			,	_a      :	Optional[Any]=0.0			,	_a      :	Tuple=0.02			,	_a      :	Union[str, Any]=1.0			,	_a      :	Optional[Any]=False			,	_a      :	List[str]="sine"			,	_a      :	Any="resnet50"			,	_a      :	Any=True			,	_a      :	Optional[Any]=False			,	_a      :	Optional[int]=1			,	_a      :	int=5			,	_a      :	Any=2			,	_a      :	int=1			,	_a      :	Optional[int]=1			,	_a      :	Union[str, Any]=5			,	_a      :	List[str]=2			,	_a      :	Any=0.1			,	**_a      :	List[Any]			,	)					->					Optional[Any]:
    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       :       Optional[Any]           = CONFIG_MAPPING['resnet'](out_features=['stage4']   )
      elif isinstance(_a			,	_a   ):
        __lowerCamelCase       :       Optional[Any]           = backbone_config.get('model_type'   )
        __lowerCamelCase       :       Tuple           = CONFIG_MAPPING[backbone_model_type]
        __lowerCamelCase       :       int           = config_class.from_dict(_a   )
      # set timm attributes to None
      __lowerCamelCase       ,__lowerCamelCase       ,__lowerCamelCase       :       Optional[Any]           = None, None, None

    __lowerCamelCase       :       Optional[Any]           = use_timm_backbone
    __lowerCamelCase       :       List[Any]           = backbone_config
    __lowerCamelCase       :       Optional[Any]           = num_channels
    __lowerCamelCase       :       List[Any]           = num_queries
    __lowerCamelCase       :       List[str]           = d_model
    __lowerCamelCase       :       str           = encoder_ffn_dim
    __lowerCamelCase       :       Tuple           = encoder_layers
    __lowerCamelCase       :       List[Any]           = encoder_attention_heads
    __lowerCamelCase       :       Tuple           = decoder_ffn_dim
    __lowerCamelCase       :       int           = decoder_layers
    __lowerCamelCase       :       Union[str, Any]           = decoder_attention_heads
    __lowerCamelCase       :       Optional[Any]           = dropout
    __lowerCamelCase       :       str           = attention_dropout
    __lowerCamelCase       :       List[str]           = activation_dropout
    __lowerCamelCase       :       Optional[Any]           = activation_function
    __lowerCamelCase       :       str           = init_std
    __lowerCamelCase       :       int           = init_xavier_std
    __lowerCamelCase       :       Tuple           = encoder_layerdrop
    __lowerCamelCase       :       Dict           = decoder_layerdrop
    __lowerCamelCase       :       Any           = encoder_layers
    __lowerCamelCase       :       List[str]           = auxiliary_loss
    __lowerCamelCase       :       Union[str, Any]           = position_embedding_type
    __lowerCamelCase       :       str           = backbone
    __lowerCamelCase       :       str           = use_pretrained_backbone
    __lowerCamelCase       :       List[Any]           = dilation
    # Hungarian matcher
    __lowerCamelCase       :       int           = class_cost
    __lowerCamelCase       :       Optional[int]           = bbox_cost
    __lowerCamelCase       :       Union[str, Any]           = giou_cost
    # Loss coefficients
    __lowerCamelCase       :       Any           = mask_loss_coefficient
    __lowerCamelCase       :       Any           = dice_loss_coefficient
    __lowerCamelCase       :       List[Any]           = bbox_loss_coefficient
    __lowerCamelCase       :       Union[str, Any]           = giou_loss_coefficient
    __lowerCamelCase       :       Union[str, Any]           = eos_coefficient
    super().__init__(is_encoder_decoder=_a			,	**_a   )




  @property
  def 						_lowercase     ( self      :	Union[str, Any]   )					->					int:
    return self.encoder_attention_heads




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




  @classmethod
  def 						_lowercase     ( cls      :	Tuple			,	_a      :	PretrainedConfig			,	**_a      :	Optional[int]   )					->					Any:
    return cls(backbone_config=_a			,	**_a   )




  def 						_lowercase     ( self      :	Union[str, Any]   )					->					Dict[str, any]:
    __lowerCamelCase       :       List[Any]           = copy.deepcopy(self.__dict__   )
    if output["backbone_config"] is not None:
      __lowerCamelCase       :       List[Any]           = self.backbone_config.to_dict()
    __lowerCamelCase       :       Any           = self.__class__.model_type
    return output






class 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




  a_												=version.parse("""1.11"""     )




  @property
  def 						_lowercase     ( self      :	List[Any]   )					->					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      :	Tuple   )					->					float:
    return 1e-5




  @property
  def 						_lowercase     ( self      :	Optional[Any]   )					->					int:
    return 12











'''simple docstring'''





def        a_     (							_lowerCAmelCase       )      ->      str:
  if not all(char in '01' for char in bin_string       ):
    raise ValueError('Non-binary value was passed to the function'       )
  if not bin_string:
    raise ValueError('Empty string was passed to the function'       )
  __lowerCamelCase       :       int           = ''
  while len(_lowerCAmelCase       ) % 3 != 0:
    __lowerCamelCase       :       str           = '0' + bin_string
  __lowerCamelCase       :       Union[str, Any]           = [
      bin_string[index : index + 3]
      for index in range(len(_lowerCAmelCase       )       )
      if index % 3 == 0
  ]
  for bin_group in bin_string_in_3_list:
    __lowerCamelCase       :       Tuple           = 0
    for index, val in enumerate(_lowerCAmelCase       ):
      oct_val += int(2 ** (2 - index) * int(_lowerCAmelCase       )       )
    oct_string += str(_lowerCAmelCase       )
  return oct_string


if __name__ == "__main__":
   from doctest import testmod

   testmod()






