




def 		a_							( __lowerCAmelCase				):
  lowerCAmelCase__										=      ''''''
  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				):
  lowerCAmelCase__										=      [chr(i + 65				) for i in range(26				)]
  # Remove duplicate characters from key
  lowerCAmelCase__										=      remove_duplicates(key.upper()				)
  lowerCAmelCase__										=      len(__lowerCAmelCase				)
  # First fill cipher with key characters
  lowerCAmelCase__										=      {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				):
    lowerCAmelCase__										=      alphabet[i - offset]
    # Ensure we are not mapping letters to letters previously mapped
    while char in key:
      offset -= 1
      lowerCAmelCase__										=      alphabet[i - offset]
    lowerCAmelCase__										=      char
  return cipher_alphabet
def 		a_							( __lowerCAmelCase   , __lowerCAmelCase				):
  return "".join(cipher_map.get(__lowerCAmelCase   , __lowerCAmelCase				) for ch in message.upper()				)
def 		a_							( __lowerCAmelCase   , __lowerCAmelCase				):
  lowerCAmelCase__										=      {v: k for k, v in cipher_map.items()}
  return "".join(rev_cipher_map.get(__lowerCAmelCase   , __lowerCAmelCase				) for ch in message.upper()				)
def 		a_							( ):
  lowerCAmelCase__										=      input('''Enter message to encode or decode: '''				).strip()
  lowerCAmelCase__										=      input('''Enter keyword: '''				).strip()
  lowerCAmelCase__										=      input('''Encipher or decipher? E/D:'''				).strip()[0].lower()
  try:
    lowerCAmelCase__										=      {'''e''': encipher, '''d''': decipher}[option]
  except KeyError:
    raise KeyError('''invalid input option'''				)
  lowerCAmelCase__										=      create_cipher_map(__lowerCAmelCase				)
  print(func(__lowerCAmelCase   , __lowerCAmelCase				)				)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


__magic_name__  :  Any					=       {
    """configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMv2Config"""],
    """processing_layoutlmv2""": ["""LayoutLMv2Processor"""],
    """tokenization_layoutlmv2""": ["""LayoutLMv2Tokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  List[str]					=       ["""LayoutLMv2TokenizerFast"""]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  Any					=       ["""LayoutLMv2FeatureExtractor"""]
      __magic_name__  :  Any					=       ["""LayoutLMv2ImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  Any					=       [
          """LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """LayoutLMv2ForQuestionAnswering""",
          """LayoutLMv2ForSequenceClassification""",
          """LayoutLMv2ForTokenClassification""",
          """LayoutLMv2Layer""",
          """LayoutLMv2Model""",
          """LayoutLMv2PreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
      from .processing_layoutlmva import LayoutLMvaProcessor
      from .tokenization_layoutlmva import LayoutLMvaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_layoutlmva import (
                LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                LayoutLMvaForQuestionAnswering,
                LayoutLMvaForSequenceClassification,
                LayoutLMvaForTokenClassification,
                LayoutLMvaLayer,
                LayoutLMvaModel,
                LayoutLMvaPreTrainedModel,
            )
else:
      import sys

      __magic_name__  :  Union[str, Any]					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

