





"""simple docstring"""





from typing import Literal

lowerCAmelCase__        =      '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''


def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		UpperCamelCase =						LETTERS if mode == "decrypt" else key
		UpperCamelCase =						key if mode == "decrypt" else LETTERS
		UpperCamelCase =						""
		# loop through each symbol in the message
		for symbol in message:
				if symbol.upper() in chars_a:
						# encrypt/decrypt the symbol
						UpperCamelCase =						chars_a.find(symbol.upper()     )
						if symbol.isupper():
								translated += chars_b[sym_index].upper()
						else:
								translated += chars_b[sym_index].lower()
				else:
						# symbol is not in LETTERS, just add it
						translated += symbol
		return translated


def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		return translate_message(_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						"encrypt"     )


def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		return translate_message(_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						"decrypt"     )


def    a__       (       ):




		"""simple docstring"""


		UpperCamelCase =						"Hello World"
		UpperCamelCase =						"QWERTYUIOPASDFGHJKLZXCVBNM"
		UpperCamelCase =						"decrypt"  # set to 'encrypt' or 'decrypt'

		if mode == "encrypt":
				UpperCamelCase =						encrypt_message(_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     )
		elif mode == "decrypt":
				UpperCamelCase =						decrypt_message(_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     )
		print(F"Using the key {key}, the {mode}ed message is: {translated}"     )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()













"""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__)






