




import string







def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			str:



       """simple docstring"""

       A__ 					=       ''''''
       for i in sequence:
              A__ 					=       ord(lowercase_		)
              if 65 <= extract <= 90:
                     output += chr(155 - extract		)
              elif 97 <= extract <= 122:
                     output += chr(219 - extract		)
              else:
                     output += i
       return output







def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			str:



       """simple docstring"""

       A__ 					=       string.ascii_letters
       A__ 					=       string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
       return "".join(
           letters_reversed[letters.index(lowercase_		)] if c in letters else c for c in sequence		)







def SCREAMING_SNAKE_CASE							(			)  ->			None:



       """simple docstring"""

       from timeit import timeit

       print('''Running performance benchmarks...'''		)
       A__ 					=       '''from string import printable ; from __main__ import atbash, atbash_slow'''
       print(f"""> atbash_slow(): {timeit("atbash_slow(printable)"					,							setup=lowercase_		)} seconds"""		)
       print(f""">      atbash(): {timeit("atbash(printable)"					,							setup=lowercase_		)} seconds"""		)


if __name__ == "__main__":
  for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
    print(F'''{example} encrypted in atbash: {atbash(example)}''')
  benchmark()




'''simple docstring'''




import copy

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


lowercase     :							Optional[Any]       						=     logging.get_logger(__name__)

lowercase     :							int       						=     {
    'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}





class 					A							(				__snake_case		):
     __magic_name__          =						'''deta'''
     __magic_name__          =						{
         '''hidden_size''': '''d_model''',
         '''num_attention_heads''': '''encoder_attention_heads''',
     }





     def __init__(				self		,     SCREAMING_SNAKE_CASE=None		,     SCREAMING_SNAKE_CASE=900		,     SCREAMING_SNAKE_CASE=2048		,     SCREAMING_SNAKE_CASE=6		,     SCREAMING_SNAKE_CASE=2048		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=6		,     SCREAMING_SNAKE_CASE=1024		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE="relu"		,     SCREAMING_SNAKE_CASE=256		,     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=True		,     SCREAMING_SNAKE_CASE=False		,     SCREAMING_SNAKE_CASE="sine"		,     SCREAMING_SNAKE_CASE=5		,     SCREAMING_SNAKE_CASE=4		,     SCREAMING_SNAKE_CASE=4		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=300		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=True		,     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=0.25		,     **SCREAMING_SNAKE_CASE		,     )					->							Any:






         """simple docstring"""






         if backbone_config is None:
             logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''      )
             A			:  Optional[Any]   =		CONFIG_MAPPING['''resnet'''](out_features=['''stage2''', '''stage3''', '''stage4''']      )
         else:
             if isinstance(SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE      ):
                 A			:  List[Any]   =		backbone_config.pop('''model_type'''      )
                 A			:  List[Any]   =		CONFIG_MAPPING[backbone_model_type]
                 A			:  Optional[int]   =		config_class.from_dict(SCREAMING_SNAKE_CASE      )

         A			:  str   =		backbone_config
         A			:  Optional[int]   =		num_queries
         A			:  Dict   =		max_position_embeddings
         A			:  Optional[Any]   =		d_model
         A			:  Optional[Any]   =		encoder_ffn_dim
         A			:  List[str]   =		encoder_layers
         A			:  Tuple   =		encoder_attention_heads
         A			:  Optional[Any]   =		decoder_ffn_dim
         A			:  Optional[int]   =		decoder_layers
         A			:  List[str]   =		decoder_attention_heads
         A			:  Union[str, Any]   =		dropout
         A			:  str   =		attention_dropout
         A			:  Any   =		activation_dropout
         A			:  Optional[int]   =		activation_function
         A			:  Tuple   =		init_std
         A			:  Any   =		init_xavier_std
         A			:  Optional[Any]   =		encoder_layerdrop
         A			:  int   =		auxiliary_loss
         A			:  Dict   =		position_embedding_type
         # deformable attributes
         A			:  str   =		num_feature_levels
         A			:  Optional[int]   =		encoder_n_points
         A			:  Any   =		decoder_n_points
         A			:  Tuple   =		two_stage
         A			:  Dict   =		two_stage_num_proposals
         A			:  List[str]   =		with_box_refine
         A			:  List[str]   =		assign_first_stage
         if two_stage is True and with_box_refine is False:
             raise ValueError('''If two_stage is True, with_box_refine must be True.'''      )
         # Hungarian matcher
         A			:  Dict   =		class_cost
         A			:  Optional[int]   =		bbox_cost
         A			:  Optional[Any]   =		giou_cost
         # Loss coefficients
         A			:  int   =		mask_loss_coefficient
         A			:  int   =		dice_loss_coefficient
         A			:  Tuple   =		bbox_loss_coefficient
         A			:  int   =		giou_loss_coefficient
         A			:  Dict   =		eos_coefficient
         A			:  Optional[Any]   =		focal_alpha
         super().__init__(is_encoder_decoder=SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )





     @property
     def 							__lowerCAmelCase				(				self      )					->							int:






         """simple docstring"""






         return self.encoder_attention_heads





     @property
     def 							__lowerCAmelCase				(				self      )					->							int:






         """simple docstring"""






         return self.d_model





     def 							__lowerCAmelCase				(				self      )					->							Any:






         """simple docstring"""






         A			:  Any   =		copy.deepcopy(self.__dict__      )
         A			:  Dict   =		self.backbone_config.to_dict()
         A			:  List[Any]   =		self.__class__.model_type
         return output




