def    lowerCAmelCase_ (     __A							)     ->				str:







      '''simple docstring'''


      UpperCAmelCase__								=  ""
      for ch in key:
            if ch == " " or ch not in key_no_dups and ch.isalpha():
                  key_no_dups += ch
      return key_no_dups




def    lowerCAmelCase_ (     __A							)     ->				dict[str, str]:







      '''simple docstring'''


      UpperCAmelCase__								=  [chr(i + 65							) for i in range(26							)]
      # Remove duplicate characters from key
      UpperCAmelCase__								=  remove_duplicates(key.upper()							)
      UpperCAmelCase__								=  len(__A							)
      # First fill cipher with key characters
      UpperCAmelCase__								=  {alphabet[i]: char for i, char in enumerate(__A							)}
      # Then map remaining characters in alphabet to
      # the alphabet from the beginning
      for i in range(len(__A							),  26							):
            UpperCAmelCase__								=  alphabet[i - offset]
            # Ensure we are not mapping letters to letters previously mapped
            while char in key:
                  offset -= 1
                  UpperCAmelCase__								=  alphabet[i - offset]
            UpperCAmelCase__								=  char
      return cipher_alphabet




def    lowerCAmelCase_ (     __A,  __A							)     ->				str:







      '''simple docstring'''


      return "".join(cipher_map.get(__A,  __A							) for ch in message.upper()							)




def    lowerCAmelCase_ (     __A,  __A							)     ->				str:







      '''simple docstring'''


      UpperCAmelCase__								=  {v: k for k, v in cipher_map.items()}
      return "".join(rev_cipher_map.get(__A,  __A							) for ch in message.upper()							)




def    lowerCAmelCase_ (     )     ->				None:







      '''simple docstring'''


      UpperCAmelCase__								=  input("Enter message to encode or decode: "							).strip()
      UpperCAmelCase__								=  input("Enter keyword: "							).strip()
      UpperCAmelCase__								=  input("Encipher or decipher? E/D:"							).strip()[0].lower()
      try:
            UpperCAmelCase__								=  {"e": encipher, "d": decipher}[option]
      except KeyError:
            raise KeyError("invalid input option"							)
      UpperCAmelCase__								=  create_cipher_map(__A							)
      print(func(__A,  __A							)							)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()







"""simple docstring"""




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


lowercase_			     =  logging.get_logger(__name__)

lowercase_			     =  {
    "microsoft/beit-base-patch16-224-pt22k": (
        "https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			List[str]										=				'beit'

		def __init__(  self							, _a=8_192							, _a=768							, _a=12							, _a=12							, _a=3_072							, _a="gelu"							, _a=0.0							, _a=0.0							, _a=0.02							, _a=1E-12							, _a=224							, _a=16							, _a=3							, _a=False							, _a=False							, _a=False							, _a=False							, _a=0.1							, _a=0.1							, _a=True							, _a=[3, 5, 7, 11]							, _a=[1, 2, 3, 6]							, _a=True							, _a=0.4							, _a=256							, _a=1							, _a=False							, _a=255							, **_a							, ):
				super().__init__(**_a      )

				__a           =			vocab_size
				__a           =			hidden_size
				__a           =			num_hidden_layers
				__a           =			num_attention_heads
				__a           =			intermediate_size
				__a           =			hidden_act
				__a           =			hidden_dropout_prob
				__a           =			attention_probs_dropout_prob
				__a           =			initializer_range
				__a           =			layer_norm_eps

				__a           =			image_size
				__a           =			patch_size
				__a           =			num_channels
				__a           =			use_mask_token
				__a           =			use_absolute_position_embeddings
				__a           =			use_relative_position_bias
				__a           =			use_shared_relative_position_bias
				__a           =			layer_scale_init_value
				__a           =			drop_path_rate
				__a           =			use_mean_pooling
				# decode head attributes (semantic segmentation)
				__a           =			out_indices
				__a           =			pool_scales
				# auxiliary head attributes (semantic segmentation)
				__a           =			use_auxiliary_head
				__a           =			auxiliary_loss_weight
				__a           =			auxiliary_channels
				__a           =			auxiliary_num_convs
				__a           =			auxiliary_concat_input
				__a           =			semantic_loss_ignore_index







class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			List[Any]										=				version.parse('1.11'       )

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





		@property
		def 			__UpperCAmelCase       (  self      ):
				return 1E-4






