


'''simple docstring'''







from __future__ import annotations






def 	lowercase (_A      ,  _A    ):







       """simple docstring"""







       _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase			:							int      	=				'', '', ''
       _lowerCAmelCase			:							Tuple      	=				[]

       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 	lowercase (_A      ,  _A    ):







       """simple docstring"""







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

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

       for digit in this_part:
              tmp += digit
              if len(_A    ) == len(_A    ):
                     result.append(_A    )
                     _lowerCAmelCase			:							Optional[int]      	=				''

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






def 	lowercase (_A      ,  _A    ):







       """simple docstring"""







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

       # Check length and characters
       if len(_A    ) != 2_7:
              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			:							Dict      	=				(
           '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			:							Union[str, Any]      	=				{}
       _lowerCAmelCase			:							Optional[int]      	=				{}
       for letter, number in zip(_A      ,  _A    ):
              _lowerCAmelCase			:							str      	=				number
              _lowerCAmelCase			:							str      	=				letter

       return message, alphabet, character_to_number, number_to_character






def 	lowercase (_A      ,  _A = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."      ,  _A = 5    ):







       """simple docstring"""







       _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase			:							int      	=				__prepare(
           _A      ,  _A    )
       _lowerCAmelCase	,   _lowerCAmelCase			:							Tuple      	=				'', ''

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

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

       return encrypted






def 	lowercase (_A      ,  _A = "ABCDEFGHIJKLMNOPQRSTUVWXYZ."      ,  _A = 5    ):







       """simple docstring"""







       _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase			:							Tuple      	=				__prepare(
           _A      ,  _A    )
       _lowerCAmelCase			:							Optional[Any]      	=				[]
       _lowerCAmelCase			:							Dict      	=				''

       for i in range(0      ,  len(_A    ) + 1      ,  _A    ):
              _lowerCAmelCase	,   _lowerCAmelCase	,   _lowerCAmelCase			:							List[Any]      	=				__decrypt_part(message[i : i + period]      ,  _A    )

              for j in range(0      ,  len(_A    )    ):
                     decrypted_numeric.append(a[j] + b[j] + c[j]    )

       for each in decrypted_numeric:
              decrypted += number_to_character[each]

       return decrypted


if __name__ == "__main__":
       lowerCAmelCase			:   Tuple 		=  'DEFEND THE EAST WALL OF THE CASTLE.'
       lowerCAmelCase			:   Optional[int] 		=  encrypt_message(msg, """EPSDUCVWYM.ZLKXNBTFGORIJHAQ""")
       lowerCAmelCase			:   Optional[Any] 		=  decrypt_message(encrypted, """EPSDUCVWYM.ZLKXNBTFGORIJHAQ""")
       print(F'''Encrypted: {encrypted}\nDecrypted: {decrypted}''')







'''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_torch_available,
)


_snake_case      :      Tuple   							=		{
    'configuration_convnextv2': [
        'CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConvNextV2Config',
    ]
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case      :      Tuple   							=		[
				    'CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'ConvNextV2ForImageClassification',
				    'ConvNextV2Model',
				    'ConvNextV2PreTrainedModel',
				    'ConvNextV2Backbone',
				]


if TYPE_CHECKING:
				from .configuration_convnextva import (
				    CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    ConvNextVaConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_convnextva import (
								    CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ConvNextVaBackbone,
								    ConvNextVaForImageClassification,
								    ConvNextVaModel,
								    ConvNextVaPreTrainedModel,
								)

else:
				import sys

				_snake_case      :      Any   							=		_LazyModule(__name__, globals()['__file__'], _import_structure)

