



'''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


lowercase							       =			logging.get_logger(__name__)

lowercase							       =			{
    '''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 	UpperCAmelCase	(		__a):


	'''simple docstring'''




	__magic_name__					: Dict  =      "detr"
	__magic_name__					: Dict  =      ["past_key_values"]
	__magic_name__					: int  =      {
	    "hidden_size": "d_model",
	    "num_attention_heads": "encoder_attention_heads",
	}




	def __init__(   self							,  lowerCAmelCase_=True							,  lowerCAmelCase_=None							,  lowerCAmelCase_=3							,  lowerCAmelCase_=1_0_0							,  lowerCAmelCase_=6							,  lowerCAmelCase_=2_0_4_8							,  lowerCAmelCase_=8							,  lowerCAmelCase_=6							,  lowerCAmelCase_=2_0_4_8							,  lowerCAmelCase_=8							,  lowerCAmelCase_=0.0							,  lowerCAmelCase_=0.0							,  lowerCAmelCase_=True							,  lowerCAmelCase_="relu"							,  lowerCAmelCase_=2_5_6							,  lowerCAmelCase_=0.1							,  lowerCAmelCase_=0.0							,  lowerCAmelCase_=0.0							,  lowerCAmelCase_=0.0_2							,  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_							,  ) ->      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.")
																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       lowercase_  (   self) ->      int:



						"""simple docstring"""







						return self.encoder_attention_heads




	@property
	def       lowercase_  (   self) ->      int:



						"""simple docstring"""







						return self.d_model




	@classmethod
	def       lowercase_  (   cls							,  lowerCAmelCase_							,  **lowerCAmelCase_) ->      List[Any]:



						"""simple docstring"""







						return cls(backbone_config=lowerCAmelCase_							,  **lowerCAmelCase_)




	def       lowercase_  (   self) ->      Dict[str, any]:



						"""simple docstring"""







						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 	UpperCAmelCase	(		__a):


	'''simple docstring'''




	__magic_name__					: Optional[int]  =      version.parse("1.11")




	@property
	def       lowercase_  (   self) ->      Mapping[str, Mapping[int, str]]:



						"""simple docstring"""







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




	@property
	def       lowercase_  (   self) ->      float:



						"""simple docstring"""







						return 1e-5




	@property
	def       lowercase_  (   self) ->      int:



						"""simple docstring"""







						return 1_2







'''simple docstring'''


from collections.abc import Sequence






def  UpperCAmelCase_       (		lowercase__ = None       ):


     '''simple docstring'''







     if nums is None or not nums:
          raise ValueError("Input sequence should not be empty"       )

     a_       		=nums[0]
     for i in range(1       ,	len(lowercase__       )       ):
          a_       		=nums[i]
          a_       		=max(lowercase__       ,	ans + num       ,	lowercase__       )

     return ans


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  # Try on a sample input from the user
  lowercase							       =			int(input('''Enter number of elements : ''').strip())
  lowercase							       =			list(map(int, input('''\nEnter the numbers : ''').strip().split()))[:n]
  print(max_subsequence_sum(array))


