


"""simple docstring"""






lowerCamelCase__				:  Any													=  [chr(i) for i in range(32, 1_26)]
lowerCamelCase__				:  Tuple													=  list(range(len(alphabets)))
lowerCamelCase__				:  Any													=  list(range(len(alphabets)))
lowerCamelCase__				:  Optional[Any]													=  list(range(len(alphabets)))
lowerCamelCase__				:  Union[str, Any]													=  list(reversed(range(len(alphabets))))
lowerCamelCase__				:  Dict													=  []
lowerCamelCase__				:  str													=  0
def       UpperCamelCase					(			)				->			str:
	global gear_one_pos
	global gear_two_pos
	global gear_three_pos
	_UpperCAmelCase    :							Optional[int]									=					gear_one[0]
	gear_one.append(_lowerCAmelCase )
	del gear_one[0]
	gear_one_pos += 1
	if gear_one_pos % int(len(_lowerCAmelCase ) ) == 0:
		_UpperCAmelCase    :							Union[str, Any]									=					gear_two[0]
		gear_two.append(_lowerCAmelCase )
		del gear_two[0]
		gear_two_pos += 1
		if gear_two_pos % int(len(_lowerCAmelCase ) ) == 0:
			_UpperCAmelCase    :							Dict									=					gear_three[0]
			gear_three.append(_lowerCAmelCase )
			del gear_three[0]
			gear_three_pos += 1
def       UpperCamelCase					(			_lowerCAmelCase     :						List[str] )				->			Optional[Any]:
	_UpperCAmelCase    :							Tuple									=					alphabets.index(_lowerCAmelCase )
	_UpperCAmelCase    :							Optional[Any]									=					gear_one[target]
	_UpperCAmelCase    :							Any									=					gear_two[target]
	_UpperCAmelCase    :							str									=					gear_three[target]
	_UpperCAmelCase    :							int									=					reflector[target]
	_UpperCAmelCase    :							str									=					gear_three.index(_lowerCAmelCase )
	_UpperCAmelCase    :							Optional[int]									=					gear_two.index(_lowerCAmelCase )
	_UpperCAmelCase    :							List[Any]									=					gear_one.index(_lowerCAmelCase )
	code.append(alphabets[target] )
	rotator()


if __name__ == "__main__":
						lowerCamelCase__				:  Any													=  list(input('''Type your message:\n'''))
						while True:
												try:
																		lowerCamelCase__				:  Any													=  int(input('''Please set token:(must be only digits)\n'''))
																		break
												except Exception as error:
																		print(error)
						for _ in range(token):
												rotator()
						for j in decode:
												engine(j)
						print('''\n''' + ''''''.join(code))
						print(
						    F'''\nYour Token is {token} please write it down.\nIf you want to decode '''
						    '''this message again you should input same digits as token!'''
						)








"""simple docstring"""






from typing import TYPE_CHECKING

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


lowerCamelCase__				:  Union[str, Any]													=  {
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__				:  List[Any]													=  [
						    '''DPRContextEncoderTokenizerFast''',
						    '''DPRQuestionEncoderTokenizerFast''',
						    '''DPRReaderTokenizerFast''',
						]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__				:  Dict													=  [
						    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''DPRContextEncoder''',
						    '''DPRPretrainedContextEncoder''',
						    '''DPRPreTrainedModel''',
						    '''DPRPretrainedQuestionEncoder''',
						    '''DPRPretrainedReader''',
						    '''DPRQuestionEncoder''',
						    '''DPRReader''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__				:  Any													=  [
						    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFDPRContextEncoder''',
						    '''TFDPRPretrainedContextEncoder''',
						    '''TFDPRPretrainedQuestionEncoder''',
						    '''TFDPRPretrainedReader''',
						    '''TFDPRQuestionEncoder''',
						    '''TFDPRReader''',
						]


if TYPE_CHECKING:
						from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
						from .tokenization_dpr import (
						    DPRContextEncoderTokenizer,
						    DPRQuestionEncoderTokenizer,
						    DPRReaderOutput,
						    DPRReaderTokenizer,
						)

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_dpr_fast import (
												    DPRContextEncoderTokenizerFast,
												    DPRQuestionEncoderTokenizerFast,
												    DPRReaderTokenizerFast,
												)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_dpr import (
												    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DPRContextEncoder,
												    DPRPretrainedContextEncoder,
												    DPRPreTrainedModel,
												    DPRPretrainedQuestionEncoder,
												    DPRPretrainedReader,
												    DPRQuestionEncoder,
												    DPRReader,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_dpr import (
												    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFDPRContextEncoder,
												    TFDPRPretrainedContextEncoder,
												    TFDPRPretrainedQuestionEncoder,
												    TFDPRPretrainedReader,
												    TFDPRQuestionEncoder,
												    TFDPRReader,
												)

else:
						import sys

						lowerCamelCase__				:  Optional[Any]													=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





