
"""simple docstring"""


def        lowerCAmelCase_       (		snake_case_		:      str							,   snake_case_		:      str      )       ->str:
			if not isinstance(snake_case_							,   snake_case_      ):
						raise TypeError('plaintext must be a string'      )
			if not isinstance(snake_case_							,   snake_case_      ):
						raise TypeError('key must be a string'      )

			if not plaintext:
						raise ValueError('plaintext is empty'      )
			if not key:
						raise ValueError('key is empty'      )

			key += plaintext
			lowerCamelCase__     :					Optional[int]		=plaintext.lower()
			lowerCamelCase__     :					Union[str, Any]		=key.lower()
			lowerCamelCase__     :					Tuple		=0
			lowerCamelCase__     :					Optional[Any]		=0
			lowerCamelCase__     :					Tuple		=''
			while plaintext_iterator < len(snake_case_      ):
						if (
						    ord(plaintext[plaintext_iterator]      ) < 9_7
						    or ord(plaintext[plaintext_iterator]      ) > 1_2_2
						):
									ciphertext += plaintext[plaintext_iterator]
									plaintext_iterator += 1
						elif ord(key[key_iterator]      ) < 9_7 or ord(key[key_iterator]      ) > 1_2_2:
									key_iterator += 1
						else:
									ciphertext += chr(
									    (
									        (ord(plaintext[plaintext_iterator]      ) - 9_7 + ord(key[key_iterator]      ))
									        - 9_7
									    )
									    % 2_6
									    + 9_7      )
									key_iterator += 1
									plaintext_iterator += 1
			return ciphertext






def        lowerCAmelCase_       (		snake_case_		:      str							,   snake_case_		:      str      )       ->str:
			if not isinstance(snake_case_							,   snake_case_      ):
						raise TypeError('ciphertext must be a string'      )
			if not isinstance(snake_case_							,   snake_case_      ):
						raise TypeError('key must be a string'      )

			if not ciphertext:
						raise ValueError('ciphertext is empty'      )
			if not key:
						raise ValueError('key is empty'      )

			lowerCamelCase__     :					Tuple		=key.lower()
			lowerCamelCase__     :					Tuple		=0
			lowerCamelCase__     :					List[Any]		=0
			lowerCamelCase__     :					Optional[Any]		=''
			while ciphertext_iterator < len(snake_case_      ):
						if (
						    ord(ciphertext[ciphertext_iterator]      ) < 9_7
						    or ord(ciphertext[ciphertext_iterator]      ) > 1_2_2
						):
									plaintext += ciphertext[ciphertext_iterator]
						else:
									plaintext += chr(
									    (ord(ciphertext[ciphertext_iterator]      ) - ord(key[key_iterator]      )) % 2_6
									    + 9_7      )
									key += chr(
									    (ord(ciphertext[ciphertext_iterator]      ) - ord(key[key_iterator]      )) % 2_6
									    + 9_7      )
									key_iterator += 1
						ciphertext_iterator += 1
			return plaintext


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							lowerCAmelCase								=						int(input("""Type 1 to encrypt or 2 to decrypt:"""))
							if operation == 1:
														lowerCAmelCase								=						input("""Typeplaintext to be encrypted:\n""")
														lowerCAmelCase								=						input("""Type the key:\n""")
														print(encrypt(plaintext, key))
							elif operation == 2:
														lowerCAmelCase								=						input("""Type the ciphertext to be decrypted:\n""")
														lowerCAmelCase								=						input("""Type the key:\n""")
														print(decrypt(ciphertext, key))
							decrypt("""jsqqs avvwo""", """coffee""")

"""simple docstring"""


from typing import TYPE_CHECKING

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


lowerCAmelCase								=						{
    """configuration_deberta_v2""": ["""DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaV2Config""", """DebertaV2OnnxConfig"""],
    """tokenization_deberta_v2""": ["""DebertaV2Tokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						["""DebertaV2TokenizerFast"""]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFDebertaV2ForMaskedLM""",
							    """TFDebertaV2ForQuestionAnswering""",
							    """TFDebertaV2ForSequenceClassification""",
							    """TFDebertaV2ForTokenClassification""",
							    """TFDebertaV2Model""",
							    """TFDebertaV2PreTrainedModel""",
							]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DebertaV2ForMaskedLM""",
							    """DebertaV2ForMultipleChoice""",
							    """DebertaV2ForQuestionAnswering""",
							    """DebertaV2ForSequenceClassification""",
							    """DebertaV2ForTokenClassification""",
							    """DebertaV2Model""",
							    """DebertaV2PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_deberta_va import (
							    DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DebertaVaConfig,
							    DebertaVaOnnxConfig,
							)
							from .tokenization_deberta_va import DebertaVaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_deberta_va import (
														    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFDebertaVaForMaskedLM,
														    TFDebertaVaForQuestionAnswering,
														    TFDebertaVaForSequenceClassification,
														    TFDebertaVaForTokenClassification,
														    TFDebertaVaModel,
														    TFDebertaVaPreTrainedModel,
														)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_deberta_va import (
														    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DebertaVaForMaskedLM,
														    DebertaVaForMultipleChoice,
														    DebertaVaForQuestionAnswering,
														    DebertaVaForSequenceClassification,
														    DebertaVaForTokenClassification,
														    DebertaVaModel,
														    DebertaVaPreTrainedModel,
														)

else:
							import sys

							lowerCAmelCase								=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)