
import copy
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


_A     =  logging.get_logger(__name__)

_A     =  {
    '''microsoft/conditional-detr-resnet-50''': (
        '''https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'''
    ),
}





class 			_lowerCAmelCase      (			snake_case__ ):
				_lowercase    	='''conditional_detr'''
				_lowercase    	=['''past_key_values''']
				_lowercase    	={
				    '''hidden_size''': '''d_model''',
				    '''num_attention_heads''': '''encoder_attention_heads''',
				}




				def __init__(      self       ,       _UpperCamelCase=True       ,       _UpperCamelCase=None       ,       _UpperCamelCase=3       ,       _UpperCamelCase=300       ,       _UpperCamelCase=6       ,       _UpperCamelCase=2_048       ,       _UpperCamelCase=8       ,       _UpperCamelCase=6       ,       _UpperCamelCase=2_048       ,       _UpperCamelCase=8       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=True       ,       _UpperCamelCase="relu"       ,       _UpperCamelCase=256       ,       _UpperCamelCase=0.1       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=0.02       ,       _UpperCamelCase=1.0       ,       _UpperCamelCase=False       ,       _UpperCamelCase="sine"       ,       _UpperCamelCase="resnet50"       ,       _UpperCamelCase=True       ,       _UpperCamelCase=False       ,       _UpperCamelCase=2       ,       _UpperCamelCase=5       ,       _UpperCamelCase=2       ,       _UpperCamelCase=1       ,       _UpperCamelCase=1       ,       _UpperCamelCase=2       ,       _UpperCamelCase=5       ,       _UpperCamelCase=2       ,       _UpperCamelCase=0.25       ,       **_UpperCamelCase       ,       )       ->   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_      			=			CONFIG_MAPPING['resnet'](out_features=["stage4"]  )
										elif isinstance(_A       ,       _A  ):
													lowerCAmelCase_      			=			backbone_config.get("model_type"  )
													lowerCAmelCase_      			=			CONFIG_MAPPING[backbone_model_type]
													lowerCAmelCase_      			=			config_class.from_dict(_A  )

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




				@property
				def   __a		(      self  )       ->   int:
							return self.encoder_attention_heads




				@property
				def   __a		(      self  )       ->   int:
							return self.d_model




				def   __a		(      self  )       ->   int:
							lowerCAmelCase_      			=			copy.deepcopy(self.__dict__  )
							if self.backbone_config is not None:
										lowerCAmelCase_      			=			self.backbone_config.to_dict()
							lowerCAmelCase_      			=			self.__class__.model_type
							return output





class 			_lowerCAmelCase      (			snake_case__ ):
				_lowercase    	=version.parse('''1.11''' )




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




				@property
				def   __a		(      self  )       ->   Optional[Any]:
							return 1e-5




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





def      lowerCamelCase__       (       __lowerCAmelCase						:						int       ):




			"""simple docstring"""


			if upper_limit < 0:
						raise ValueError("Limit for the Catalan sequence must be ≥ 0"       )

			lowerCAmelCase_      			=			[0] * (upper_limit + 1)

			# Base case: C(0) = C(1) = 1
			lowerCAmelCase_      			=			1
			if upper_limit > 0:
						lowerCAmelCase_      			=			1

			# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
			for i in range(2					,							upper_limit + 1       ):
						for j in range(__lowerCAmelCase       ):
									catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

			return catalan_list


if __name__ == "__main__":
			print("\n********* Catalan Numbers Using Dynamic Programming ************\n")
			print("\n*** Enter -1 at any time to quit ***")
			print("\nEnter the upper limit (≥ 0) for the Catalan number sequence: ", end="")
			try:
						while True:
									_A     =  int(input().strip())
									if N < 0:
												print("\n********* Goodbye!! ************")
												break
									else:
												print(f"""The Catalan numbers from 0 through {N} are:""")
												print(catalan_numbers(N))
												print("Try another upper limit for the sequence: ", end="")
			except (NameError, ValueError):
						print("\n********* Invalid input, goodbye! ************\n")

			import doctest

			doctest.testmod()



