
"""simple docstring"""

from __future__ import annotations






def 				A		(							snake_case :str							,   snake_case :dict[str, str]						) ->      str:
 __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase							    =			'', '', ''
 __UpperCamelCase							    =			[]

 for character in message_part:
  tmp.append(character_to_number[character]						)

 for each in tmp:
  one += each[0]
  two += each[1]
  three += each[2]

 return one + two + three






def 				A		(							snake_case :str							,   snake_case :dict[str, str]						) ->      tuple[str, str, str]:
 __UpperCamelCase    ,      __UpperCamelCase							    =			'', ''
 __UpperCamelCase							    =			[]

 for character in message_part:
  this_part += character_to_number[character]

 for digit in this_part:
  tmp += digit
  if len(snake_case						) == len(snake_case						):
   result.append(snake_case						)
   __UpperCamelCase							    =			''

 return result[0], result[1], result[2]






def 				A		(							snake_case :str							,   snake_case :str						) ->      tuple[str, str, dict[str, str], dict[str, str]]:
 # Validate message and alphabet, set to upper and remove spaces
 __UpperCamelCase							    =			alphabet.replace(' '							,   ''						).upper()
 __UpperCamelCase							    =			message.replace(' '							,   ''						).upper()

 # Check length and characters
 if len(snake_case						) != 2_7:
  raise KeyError('Length of alphabet has to be 27.'						)
 for each in message:
  if each not in alphabet:
   raise ValueError('Each message character has to be included in alphabet!'						)

    # Generate dictionares
 __UpperCamelCase							    =			(
     '111',
     '112',
     '113',
     '121',
     '122',
     '123',
     '131',
     '132',
     '133',
     '211',
     '212',
     '213',
     '221',
     '222',
     '223',
     '231',
     '232',
     '233',
     '311',
     '312',
     '313',
     '321',
     '322',
     '323',
     '331',
     '332',
     '333',
 )
 __UpperCamelCase							    =			{}
 __UpperCamelCase							    =			{}
 for letter, number in zip(snake_case							,   snake_case						):
  __UpperCamelCase							    =			number
  __UpperCamelCase							    =			letter

 return message, alphabet, character_to_number, number_to_character






def 				A		(							snake_case :str							,   snake_case :str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."							,   snake_case :int = 5						) ->      str:
 __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase							    =			__prepare(
     snake_case							,   snake_case						)
 __UpperCamelCase    ,      __UpperCamelCase							    =			'', ''

 for i in range(0							,   len(snake_case						) + 1							,   snake_case						):
  encrypted_numeric += __encrypt_part(
      message[i : i + period]							,   snake_case						)

 for i in range(0							,   len(snake_case						)							,   3						):
  encrypted += number_to_character[encrypted_numeric[i : i + 3]]

 return encrypted






def 				A		(							snake_case :str							,   snake_case :str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."							,   snake_case :int = 5						) ->      str:
 __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase							    =			__prepare(
     snake_case							,   snake_case						)
 __UpperCamelCase							    =			[]
 __UpperCamelCase							    =			''

 for i in range(0							,   len(snake_case						) + 1							,   snake_case						):
  __UpperCamelCase    ,      __UpperCamelCase    ,      __UpperCamelCase							    =			__decrypt_part(message[i : i + period]							,   snake_case						)

  for j in range(0							,   len(snake_case						)						):
   decrypted_numeric.append(a[j] + b[j] + c[j]						)

 for each in decrypted_numeric:
  decrypted += number_to_character[each]

 return decrypted


if __name__ == "__main__":
      UpperCamelCase      :							Optional[int]          =					"DEFEND THE EAST WALL OF THE CASTLE."
      UpperCamelCase      :							Optional[Any]          =					encrypt_message(msg, "EPSDUCVWYM.ZLKXNBTFGORIJHAQ")
      UpperCamelCase      :							str          =					decrypt_message(encrypted, "EPSDUCVWYM.ZLKXNBTFGORIJHAQ")
      print(f'''Encrypted: {encrypted}\nDecrypted: {decrypted}''')





"""simple docstring"""

import copy
from typing import Dict, Optional

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


UpperCamelCase      :							List[str]          =					logging.get_logger(__name__)

UpperCamelCase      :							Dict          =					{
    "shi-labs/oneformer_ade20k_swin_tiny": (
        "https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json"
    ),
    # See all OneFormer models at https://huggingface.co/models?filter=oneformer
}

class __lowerCAmelCase						( __SCREAMING_SNAKE_CASE     ):
     lowercase		  =		"oneformer"
     lowercase		  =		{"hidden_size": "hidden_dim"}





     def __init__(      self      ,	__UpperCAmelCase = None      ,	__UpperCAmelCase = 255      ,	__UpperCAmelCase = 150      ,	__UpperCAmelCase = 0.1      ,	__UpperCAmelCase = 2.0      ,	__UpperCAmelCase = 5.0      ,	__UpperCAmelCase = 5.0      ,	__UpperCAmelCase = 0.5      ,	__UpperCAmelCase = 0.0_7      ,	__UpperCAmelCase = 1_2544      ,	__UpperCAmelCase = 3.0      ,	__UpperCAmelCase = 0.7_5      ,	__UpperCAmelCase = 0.0_2      ,	__UpperCAmelCase = 1.0      ,	__UpperCAmelCase = 1E-05      ,	__UpperCAmelCase = False      ,	__UpperCAmelCase = True      ,	__UpperCAmelCase = True      ,	__UpperCAmelCase = [4, 8, 16, 32]      ,	__UpperCAmelCase = 77      ,	__UpperCAmelCase = 256      ,	__UpperCAmelCase = 77      ,	__UpperCAmelCase = 6      ,	__UpperCAmelCase = 4_9408      ,	__UpperCAmelCase = 2      ,	__UpperCAmelCase = 16      ,	__UpperCAmelCase = 256      ,	__UpperCAmelCase = 256      ,	__UpperCAmelCase = 256      ,	__UpperCAmelCase = 1024      ,	__UpperCAmelCase = "GN"      ,	__UpperCAmelCase = 6      ,	__UpperCAmelCase = 10      ,	__UpperCAmelCase = True      ,	__UpperCAmelCase = 8      ,	__UpperCAmelCase = 0.1      ,	__UpperCAmelCase = 2048      ,	__UpperCAmelCase = False      ,	__UpperCAmelCase = False      ,	__UpperCAmelCase = 2      ,	__UpperCAmelCase = 4      ,	**__UpperCAmelCase      ,	):

      '''simple docstring'''




      if backbone_config is None:
       logger.info('`backbone_config` is unset. Initializing the config with the default `Swin` backbone.' )
       __UpperCamelCase							    =			CONFIG_MAPPING['swin'](
           image_size=224      ,	in_channels=3      ,	patch_size=4      ,	embed_dim=96      ,	depths=[2, 2, 6, 2]      ,	num_heads=[3, 6, 12, 24]      ,	window_size=7      ,	drop_path_rate=0.3      ,	use_absolute_embeddings=__UpperCAmelCase      ,	out_features=['stage1', 'stage2', 'stage3', 'stage4']      ,	)
      elif isinstance(__UpperCAmelCase      ,	__UpperCAmelCase ):
       __UpperCamelCase							    =			backbone_config.get('model_type' )
       __UpperCamelCase							    =			CONFIG_MAPPING[backbone_model_type]
       __UpperCamelCase							    =			config_class.from_dict(__UpperCAmelCase )

      __UpperCamelCase							    =			backbone_config

      __UpperCamelCase							    =			ignore_value
      __UpperCamelCase							    =			num_queries
      __UpperCamelCase							    =			no_object_weight
      __UpperCamelCase							    =			class_weight
      __UpperCamelCase							    =			mask_weight
      __UpperCamelCase							    =			dice_weight
      __UpperCamelCase							    =			contrastive_weight
      __UpperCamelCase							    =			contrastive_temperature
      __UpperCamelCase							    =			train_num_points
      __UpperCamelCase							    =			oversample_ratio
      __UpperCamelCase							    =			importance_sample_ratio
      __UpperCamelCase							    =			init_std
      __UpperCamelCase							    =			init_xavier_std
      __UpperCamelCase							    =			layer_norm_eps
      __UpperCamelCase							    =			is_training
      __UpperCamelCase							    =			use_auxiliary_loss
      __UpperCamelCase							    =			output_auxiliary_logits
      __UpperCamelCase							    =			strides
      __UpperCamelCase							    =			task_seq_len
      __UpperCamelCase							    =			text_encoder_width
      __UpperCamelCase							    =			text_encoder_context_length
      __UpperCamelCase							    =			text_encoder_num_layers
      __UpperCamelCase							    =			text_encoder_vocab_size
      __UpperCamelCase							    =			text_encoder_proj_layers
      __UpperCamelCase							    =			text_encoder_n_ctx
      __UpperCamelCase							    =			conv_dim
      __UpperCamelCase							    =			mask_dim
      __UpperCamelCase							    =			hidden_dim
      __UpperCamelCase							    =			encoder_feedforward_dim
      __UpperCamelCase							    =			norm
      __UpperCamelCase							    =			encoder_layers
      __UpperCamelCase							    =			decoder_layers
      __UpperCamelCase							    =			use_task_norm
      __UpperCamelCase							    =			num_attention_heads
      __UpperCamelCase							    =			dropout
      __UpperCamelCase							    =			dim_feedforward
      __UpperCamelCase							    =			pre_norm
      __UpperCamelCase							    =			enforce_input_proj
      __UpperCamelCase							    =			query_dec_layers
      __UpperCamelCase							    =			common_stride
      __UpperCamelCase							    =			decoder_layers

      super().__init__(**__UpperCAmelCase )







     def 		UpperCAmelCase   (      self ):

      '''simple docstring'''




      __UpperCamelCase							    =			copy.deepcopy(self.__dict__ )
      __UpperCamelCase							    =			self.backbone_config.to_dict()
      __UpperCamelCase							    =			self.__class__.model_type
      return output



