





'''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


A_		:  Dict		 =						logging.get_logger(__name__)

A_		:  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  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      '''detr'''
   lowerCamelCase__    							=      ['''past_key_values''']
   lowerCamelCase__    							=      {
       '''hidden_size''': '''d_model''',
       '''num_attention_heads''': '''encoder_attention_heads''',
   }

   def __init__(							self	,		__SCREAMING_SNAKE_CASE=True	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE=3	,		__SCREAMING_SNAKE_CASE=1_0_0	,		__SCREAMING_SNAKE_CASE=6	,		__SCREAMING_SNAKE_CASE=2_0_4_8	,		__SCREAMING_SNAKE_CASE=8	,		__SCREAMING_SNAKE_CASE=6	,		__SCREAMING_SNAKE_CASE=2_0_4_8	,		__SCREAMING_SNAKE_CASE=8	,		__SCREAMING_SNAKE_CASE=0.0	,		__SCREAMING_SNAKE_CASE=0.0	,		__SCREAMING_SNAKE_CASE=True	,		__SCREAMING_SNAKE_CASE="relu"	,		__SCREAMING_SNAKE_CASE=2_5_6	,		__SCREAMING_SNAKE_CASE=0.1	,		__SCREAMING_SNAKE_CASE=0.0	,		__SCREAMING_SNAKE_CASE=0.0	,		__SCREAMING_SNAKE_CASE=0.02	,		__SCREAMING_SNAKE_CASE=1.0	,		__SCREAMING_SNAKE_CASE=False	,		__SCREAMING_SNAKE_CASE="sine"	,		__SCREAMING_SNAKE_CASE="resnet50"	,		__SCREAMING_SNAKE_CASE=True	,		__SCREAMING_SNAKE_CASE=False	,		__SCREAMING_SNAKE_CASE=1	,		__SCREAMING_SNAKE_CASE=5	,		__SCREAMING_SNAKE_CASE=2	,		__SCREAMING_SNAKE_CASE=1	,		__SCREAMING_SNAKE_CASE=1	,		__SCREAMING_SNAKE_CASE=5	,		__SCREAMING_SNAKE_CASE=2	,		__SCREAMING_SNAKE_CASE=0.1	,		**__SCREAMING_SNAKE_CASE	,		):
    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."""       )
      snake_case__     :					Optional[int]    =  CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]       )
     elif isinstance(__SCREAMING_SNAKE_CASE	,		__SCREAMING_SNAKE_CASE       ):
      snake_case__     :					List[str]    =  backbone_config.get("""model_type"""       )
      snake_case__     :					List[Any]    =  CONFIG_MAPPING[backbone_model_type]
      snake_case__     :					Dict    =  config_class.from_dict(__SCREAMING_SNAKE_CASE       )
     # set timm attributes to None
     snake_case__  ,							snake_case__  ,							snake_case__     :					int    =  None, None, None

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

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

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

   @classmethod
   def 		__UpperCamelCase						(							cls	,		__SCREAMING_SNAKE_CASE	,		**__SCREAMING_SNAKE_CASE       ):
    return cls(backbone_config=__SCREAMING_SNAKE_CASE	,		**__SCREAMING_SNAKE_CASE       )


   def 		__UpperCamelCase						(							self       ):
    snake_case__     :					Dict    =  copy.deepcopy(self.__dict__       )
    if output["backbone_config"] is not None:
     snake_case__     :					Union[str, Any]    =  self.backbone_config.to_dict()
    snake_case__     :					Tuple    =  self.__class__.model_type
    return output



class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      version.parse('''1.11'''							)

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

   @property
   def 		__UpperCamelCase						(							self       ):
    return 1e-5


   @property
   def 		__UpperCamelCase						(							self       ):
    return 1_2







from __future__ import annotations
def 							__SCREAMING_SNAKE_CASE     (   a__    :   List[str]			,a__    :   Dict			,a__    :   Union[str, Any]			,a__    :   Any       )					->				Optional[int]:  # noqa: E741
	while r - l > 1:
		__A :			Any		    =			(l + r) // 2
		if v[m] >= key:
			__A :			Optional[int]		    =			m
		else:
			__A :			List[Any]		    =			m  # noqa: E741
	return r
def 							__SCREAMING_SNAKE_CASE     (   a__    :   list[int]       )					->				int:
	if len(a__       ) == 0:
		return 0

	__A :			str		    =			[0] * len(a__       )
	__A :			List[str]		    =			1

	__A :			List[Any]		    =			v[0]

	for i in range(1			,len(a__       )       ):
		if v[i] < tail[0]:
			__A :			int		    =			v[i]
		elif v[i] > tail[length - 1]:
			__A :			Union[str, Any]		    =			v[i]
			length += 1
		else:
			__A :			Any		    =			v[i]

	return length


if __name__ == "__main__":
			import doctest

			doctest.testmod()





