



'''simple docstring'''




# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a   :			int					  =    {"""configuration_mra""": ["""MRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MraConfig"""]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a   :			Tuple					  =    [
							    """MRA_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MraForMaskedLM""",
							    """MraForMultipleChoice""",
							    """MraForQuestionAnswering""",
							    """MraForSequenceClassification""",
							    """MraForTokenClassification""",
							    """MraLayer""",
							    """MraModel""",
							    """MraPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mra import (
														    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MraForMaskedLM,
														    MraForMultipleChoice,
														    MraForQuestionAnswering,
														    MraForSequenceClassification,
														    MraForTokenClassification,
														    MraLayer,
														    MraModel,
														    MraPreTrainedModel,
														)
else:
							import sys

							a   :			int					  =    _LazyModule(__name__, globals()["""__file__"""], _import_structure)








def 		A_				(     _lowerCAmelCase     )						-> str:
 UpperCamelCase	:					List[Any]       	=   ""
 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 		A_				(     _lowerCAmelCase     )						-> dict[str, str]:
 UpperCamelCase	:					Optional[Any]       	=   [chr(i + 65     ) for i in range(26     )]
 # Remove duplicate characters from key
 UpperCamelCase	:					Tuple       	=   remove_duplicates(key.upper()     )
 UpperCamelCase	:					int       	=   len(_lowerCAmelCase     )
 # First fill cipher with key characters
 UpperCamelCase	:					int       	=   {alphabet[i]: char for i, char in enumerate(_lowerCAmelCase     )}
 # Then map remaining characters in alphabet to
 # the alphabet from the beginning
 for i in range(len(_lowerCAmelCase     )							,   26     ):
  UpperCamelCase	:					Optional[Any]       	=   alphabet[i - offset]
  # Ensure we are not mapping letters to letters previously mapped
  while char in key:
   offset -= 1
   UpperCamelCase	:					List[str]       	=   alphabet[i - offset]
  UpperCamelCase	:					List[Any]       	=   char
 return cipher_alphabet



def 		A_				(     _lowerCAmelCase							,   _lowerCAmelCase     )						-> str:
 return "".join(cipher_map.get(_lowerCAmelCase							,   _lowerCAmelCase     ) for ch in message.upper()     )



def 		A_				(     _lowerCAmelCase							,   _lowerCAmelCase     )						-> str:
 UpperCamelCase	:					Union[str, Any]       	=   {v: k for k, v in cipher_map.items()}
 return "".join(rev_cipher_map.get(_lowerCAmelCase							,   _lowerCAmelCase     ) for ch in message.upper()     )



def 		A_				(     )						-> None:
 UpperCamelCase	:					int       	=   input("Enter message to encode or decode: "     ).strip()
 UpperCamelCase	:					str       	=   input("Enter keyword: "     ).strip()
 UpperCamelCase	:					Union[str, Any]       	=   input("Encipher or decipher? E/D:"     ).strip()[0].lower()
 try:
  UpperCamelCase	:					List[str]       	=   {"e": encipher, "d": decipher}[option]
 except KeyError:
  raise KeyError("invalid input option"     )
 UpperCamelCase	:					str       	=   create_cipher_map(_lowerCAmelCase     )
 print(func(_lowerCAmelCase							,   _lowerCAmelCase     )     )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    main()
