



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


_lowercase     							=						logging.get_logger(__name__)

_lowercase     							=						{
    '''microsoft/conditional-detr-resnet-50''': (
        '''https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'''
    ),
}
class 				__A					( __UpperCAmelCase      ):
			UpperCamelCase					:Optional[Any]     =			'''conditional_detr'''
			UpperCamelCase					:str     =			['''past_key_values''']
			UpperCamelCase					:Union[str, Any]     =			{
			    '''hidden_size''': '''d_model''',
			    '''num_attention_heads''': '''encoder_attention_heads''',
			}





			def __init__(self							,    __magic_name__=True							,    __magic_name__=None							,    __magic_name__=3							,    __magic_name__=300							,    __magic_name__=6							,    __magic_name__=2048							,    __magic_name__=8							,    __magic_name__=6							,    __magic_name__=2048							,    __magic_name__=8							,    __magic_name__=0.0							,    __magic_name__=0.0							,    __magic_name__=True							,    __magic_name__="relu"							,    __magic_name__=256							,    __magic_name__=0.1							,    __magic_name__=0.0							,    __magic_name__=0.0							,    __magic_name__=0.02							,    __magic_name__=1.0							,    __magic_name__=False							,    __magic_name__="sine"							,    __magic_name__="resnet50"							,    __magic_name__=True							,    __magic_name__=False							,    __magic_name__=2							,    __magic_name__=5							,    __magic_name__=2							,    __magic_name__=1							,    __magic_name__=1							,    __magic_name__=2							,    __magic_name__=5							,    __magic_name__=2							,    __magic_name__=0.25							,    **__magic_name__							,    ):

						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__ :      int								=		CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]				)
									elif isinstance(__SCREAMING_SNAKE_CASE							,    __SCREAMING_SNAKE_CASE				):
												lowerCamelCase__ :      Tuple								=		backbone_config.get("""model_type"""				)
												lowerCamelCase__ :      Optional[Any]								=		CONFIG_MAPPING[backbone_model_type]
												lowerCamelCase__ :      Dict								=		config_class.from_dict(__SCREAMING_SNAKE_CASE				)

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





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





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





			def        _snake_case    (self				):
						lowerCamelCase__ :      Dict								=		copy.deepcopy(self.__dict__				)
						if self.backbone_config is not None:
									lowerCamelCase__ :      str								=		self.backbone_config.to_dict()
						lowerCamelCase__ :      List[str]								=		self.__class__.model_type
						return output







class 				__A					( __UpperCAmelCase      ):
			UpperCamelCase					:Any     =			version.parse('''1.11'''      )





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





			@property
			def        _snake_case    (self				):
						return 1E-5





			@property
			def        _snake_case    (self				):
						return 12






from string import ascii_uppercase

_lowercase     							=						{char: i for i, char in enumerate(ascii_uppercase)}
_lowercase     							=						dict(enumerate(ascii_uppercase))






def      _A				(UpperCamelCase		:      str      ,			UpperCamelCase		:      str )  ->str:



			'''simple docstring'''







			lowerCamelCase__ :      List[str]								=		len(UpperCamelCase )
			lowerCamelCase__ :      int								=		0
			while True:
						if x == i:
									lowerCamelCase__ :      Union[str, Any]								=		0
						if len(UpperCamelCase ) == len(UpperCamelCase ):
									break
						key += key[i]
						i += 1
			return key






def      _A				(UpperCamelCase		:      str      ,			UpperCamelCase		:      str )  ->str:



			'''simple docstring'''







			lowerCamelCase__ :      int								=		""""""
			lowerCamelCase__ :      str								=		0
			for letter in message:
						if letter == " ":
									cipher_text += " "
						else:
									lowerCamelCase__ :      Optional[int]								=		(dicta[letter] - dicta[key_new[i]]) % 26
									i += 1
									cipher_text += dicta[x]
			return cipher_text






def      _A				(UpperCamelCase		:      str      ,			UpperCamelCase		:      str )  ->str:



			'''simple docstring'''







			lowerCamelCase__ :      Dict								=		""""""
			lowerCamelCase__ :      Tuple								=		0
			for letter in cipher_text:
						if letter == " ":
									or_txt += " "
						else:
									lowerCamelCase__ :      List[Any]								=		(dicta[letter] + dicta[key_new[i]] + 26) % 26
									i += 1
									or_txt += dicta[x]
			return or_txt






def      _A				()  ->None:



			'''simple docstring'''







			lowerCamelCase__ :      Union[str, Any]								=		"""THE GERMAN ATTACK"""
			lowerCamelCase__ :      Union[str, Any]								=		"""SECRET"""
			lowerCamelCase__ :      List[str]								=		generate_key(UpperCamelCase      ,			UpperCamelCase )
			lowerCamelCase__ :      List[Any]								=		cipher_text(UpperCamelCase      ,			UpperCamelCase )
			print(f"Encrypted Text = {s}" )
			print(f"Original Text = {original_text(UpperCamelCase      ,			UpperCamelCase )}" )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()



