

from __future__ import annotations







def _a				( SCREAMING_SNAKE_CASE	:    str					,      SCREAMING_SNAKE_CASE	:    dict[str, str]	)					->					str:

 """simple docstring"""






 __lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase:     List[str]     			=   '', '', ''
 __lowerCAmelCase:     List[str]     			=   []

 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				( SCREAMING_SNAKE_CASE	:    str					,      SCREAMING_SNAKE_CASE	:    dict[str, str]	)					->					tuple[str, str, str]:

 """simple docstring"""






 __lowerCAmelCase			,							__lowerCAmelCase:     List[str]     			=   '', ''
 __lowerCAmelCase:     List[Any]     			=   []

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

 for digit in this_part:
  tmp += digit
  if len(SCREAMING_SNAKE_CASE	) == len(SCREAMING_SNAKE_CASE	):
   result.append(SCREAMING_SNAKE_CASE	)
   __lowerCAmelCase:     Any     			=   ''

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







def _a				( SCREAMING_SNAKE_CASE	:    str					,      SCREAMING_SNAKE_CASE	:    str	)					->					tuple[str, str, dict[str, str], dict[str, str]]:

 """simple docstring"""






 __lowerCAmelCase:     List[str]     			=   alphabet.replace(' '					,      ''	).upper()
 __lowerCAmelCase:     Any     			=   message.replace(' '					,      ''	).upper()

 # Check length and characters
 if len(SCREAMING_SNAKE_CASE	) != 27:
  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
 __lowerCAmelCase:     Optional[int]     			=   (
     '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',
 )
 __lowerCAmelCase:     List[str]     			=   {}
 __lowerCAmelCase:     Any     			=   {}
 for letter, number in zip(SCREAMING_SNAKE_CASE					,      SCREAMING_SNAKE_CASE	):
  __lowerCAmelCase:     Tuple     			=   number
  __lowerCAmelCase:     Optional[int]     			=   letter

 return message, alphabet, character_to_number, number_to_character







def _a				( SCREAMING_SNAKE_CASE	:    str					,      SCREAMING_SNAKE_CASE	:    str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."					,      SCREAMING_SNAKE_CASE	:    int = 5	)					->					str:

 """simple docstring"""






 __lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase:     List[Any]     			=   __prepare(
     SCREAMING_SNAKE_CASE					,      SCREAMING_SNAKE_CASE	)
 __lowerCAmelCase			,							__lowerCAmelCase:     Optional[int]     			=   '', ''

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

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

 return encrypted







def _a				( SCREAMING_SNAKE_CASE	:    str					,      SCREAMING_SNAKE_CASE	:    str = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."					,      SCREAMING_SNAKE_CASE	:    int = 5	)					->					str:

 """simple docstring"""






 __lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase:     Dict     			=   __prepare(
     SCREAMING_SNAKE_CASE					,      SCREAMING_SNAKE_CASE	)
 __lowerCAmelCase:     Union[str, Any]     			=   []
 __lowerCAmelCase:     Optional[Any]     			=   ''

 for i in range(0					,      len(SCREAMING_SNAKE_CASE	) + 1					,      SCREAMING_SNAKE_CASE	):
  __lowerCAmelCase			,							__lowerCAmelCase			,							__lowerCAmelCase:     Tuple     			=   __decrypt_part(message[i : i + period]					,      SCREAMING_SNAKE_CASE	)

  for j in range(0					,      len(SCREAMING_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__":
  _a	 =     '''DEFEND THE EAST WALL OF THE CASTLE.'''
  _a	 =     encrypt_message(msg, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
  _a	 =     decrypt_message(encrypted, '''EPSDUCVWYM.ZLKXNBTFGORIJHAQ''')
  print(f"Encrypted: {encrypted}\nDecrypted: {decrypted}")








# 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

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


_a	 =     {
    '''configuration_tvlt''': ['''TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TvltConfig'''],
    '''feature_extraction_tvlt''': ['''TvltFeatureExtractor'''],
    '''processing_tvlt''': ['''TvltProcessor'''],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _a	 =     [
      '''TVLT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TvltModel''',
      '''TvltForPreTraining''',
      '''TvltForAudioVisualClassification''',
      '''TvltPreTrainedModel''',
  ]

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _a	 =     ['''TvltImageProcessor''']


if TYPE_CHECKING:
  from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
  from .processing_tvlt import TvltProcessor
  from .feature_extraction_tvlt import TvltFeatureExtractor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tvlt import (
        TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TvltForAudioVisualClassification,
        TvltForPreTraining,
        TvltModel,
        TvltPreTrainedModel,
    )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_tvlt import TvltImageProcessor


else:
  import sys

  _a	 =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





