






def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	__lowercase             =  """"""
	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 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	__lowercase             =  [chr(i + 65					) for i in range(26					)]
	# Remove duplicate characters from key
	__lowercase             =  remove_duplicates(key.upper()					)
	__lowercase             =  len(lowerCamelCase					)
	# First fill cipher with key characters
	__lowercase             =  {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					):
		__lowercase             =  alphabet[i - offset]
		# Ensure we are not mapping letters to letters previously mapped
		while char in key:
			offset -= 1
			__lowercase             =  alphabet[i - offset]
		__lowercase             =  char
	return cipher_alphabet





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







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





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







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





def 				snake_case  (     ):




	'''simple docstring'''







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


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()









# 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


__UpperCamelCase      :      Any     						=						{"""configuration_mra""": ["""MRA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MraConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase      :      Dict     						=						[
						    """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

						__UpperCamelCase      :      List[str]     						=						_LazyModule(__name__, globals()["""__file__"""], _import_structure)

