



'''simple docstring'''



_lowercase       :						Optional[int]						=[chr(i) for i in range(32, 126)]
_lowercase       :						Tuple						=list(range(len(alphabets)))
_lowercase       :						Any						=list(range(len(alphabets)))
_lowercase       :						List[Any]						=list(range(len(alphabets)))
_lowercase       :						Dict						=list(reversed(range(len(alphabets))))
_lowercase       :						Dict						=[]
_lowercase       :						List[str]						=0


def 							__UpperCAmelCase				(				)		->						Tuple:
				global gear_one_pos
				global gear_two_pos
				global gear_three_pos
				snake_case__      :   Union[str, Any]      =    gear_one[0]
				gear_one.append(UpperCamelCase__			)
				del gear_one[0]
				gear_one_pos += 1
				if gear_one_pos % int(len(UpperCamelCase__			)			) == 0:
								snake_case__      :   Dict      =    gear_two[0]
								gear_two.append(UpperCamelCase__			)
								del gear_two[0]
								gear_two_pos += 1
								if gear_two_pos % int(len(UpperCamelCase__			)			) == 0:
												snake_case__      :   List[str]      =    gear_three[0]
												gear_three.append(UpperCamelCase__			)
												del gear_three[0]
												gear_three_pos += 1


def 							__UpperCAmelCase				(				UpperCamelCase__				:Tuple			)		->						List[Any]:
				snake_case__      :   List[Any]      =    alphabets.index(UpperCamelCase__			)
				snake_case__      :   List[Any]      =    gear_one[target]
				snake_case__      :   List[str]      =    gear_two[target]
				snake_case__      :   Optional[int]      =    gear_three[target]
				snake_case__      :   Union[str, Any]      =    reflector[target]
				snake_case__      :   Tuple      =    gear_three.index(UpperCamelCase__			)
				snake_case__      :   str      =    gear_two.index(UpperCamelCase__			)
				snake_case__      :   str      =    gear_one.index(UpperCamelCase__			)
				code.append(alphabets[target]			)
				rotator()


if __name__ == "__main__":
				_lowercase       :						List[str]						=list(input("Type your message:\n"))
				while True:
								try:
												_lowercase       :						Dict						=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!"
				)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase_    ={
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

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

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_    =[
		    """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """SplinterForQuestionAnswering""",
		    """SplinterForPreTraining""",
		    """SplinterLayer""",
		    """SplinterModel""",
		    """SplinterPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
		from .tokenization_splinter import SplinterTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_splinter_fast import SplinterTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_splinter import (
				    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SplinterForPreTraining,
				    SplinterForQuestionAnswering,
				    SplinterLayer,
				    SplinterModel,
				    SplinterPreTrainedModel,
				)


else:
		import sys

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



