





"""simple docstring"""




def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Union[str, Any]					, _lowercase		:					Any      )				->Optional[Any]:






	'''simple docstring'''






	a   :	Union[str, Any]			=       ""
	for i in table:
		res += inp[i - 1]
	return res






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					str      )				->Tuple:






	'''simple docstring'''






	return data[1:] + data[0]






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Tuple					, _lowercase		:					List[str]      )				->Optional[Any]:






	'''simple docstring'''






	a   :	Any			=       ""
	for i in range(len(_lowercase      )      ):
		if a[i] == b[i]:
			res += "0"
		else:
			res += "1"
	return res






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Optional[Any]					, _lowercase		:					Dict      )				->Tuple:






	'''simple docstring'''






	a   :	Any			=       int("0b" + data[0] + data[-1]					, 2      )
	a   :	Optional[Any]			=       int("0b" + data[1:3]					, 2      )
	return bin(s[row][col]      )[2:]






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Dict					, _lowercase		:					List[Any]					, _lowercase		:					Dict					, _lowercase		:					Union[str, Any]					, _lowercase		:					Union[str, Any]      )				->List[str]:






	'''simple docstring'''






	a   :	Optional[Any]			=       message[:4]
	a   :	str			=       message[4:]
	a   :	Optional[int]			=       apply_table(_lowercase					, _lowercase      )
	a   :	Optional[int]			=       xor(_lowercase					, _lowercase      )
	a   :	Optional[Any]			=       apply_sbox(_lowercase					, temp[:4]      )  # noqa: E741
	a   :	List[Any]			=       apply_sbox(_lowercase					, temp[4:]      )
	a   :	int			=       "0" * (2 - len(_lowercase      )) + l  # noqa: E741
	a   :	Union[str, Any]			=       "0" * (2 - len(_lowercase      )) + r
	a   :	Optional[Any]			=       apply_table(l + r					, _lowercase      )
	a   :	List[str]			=       xor(_lowercase					, _lowercase      )
	return temp + right


if __name__ == "__main__":
		_A		:				str  			=    input('''Enter 10 bit key: ''')
		_A		:				Optional[Any]  			=    input('''Enter 8 bit message: ''')

		_A		:				Dict  			=    [6, 3, 7, 4, 8, 5, 10, 9]
		_A		:				List[Any]  			=    [3, 5, 2, 7, 4, 10, 1, 9, 8, 6]
		_A		:				Any  			=    [2, 4, 3, 1]
		_A		:				Optional[int]  			=    [2, 6, 3, 1, 4, 8, 5, 7]
		_A		:				List[str]  			=    [4, 1, 3, 5, 7, 2, 8, 6]
		_A		:				int  			=    [4, 1, 2, 3, 2, 3, 4, 1]
		_A		:				List[str]  			=    [[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
		_A		:				Optional[Any]  			=    [[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

		# key generation
		_A		:				List[str]  			=    apply_table(key, paa_table)
		_A		:				Dict  			=    temp[:5]
		_A		:				Tuple  			=    temp[5:]
		_A		:				List[Any]  			=    left_shift(left)
		_A		:				Tuple  			=    left_shift(right)
		_A		:				List[Any]  			=    apply_table(left + right, pa_table)
		_A		:				Union[str, Any]  			=    left_shift(left)
		_A		:				Dict  			=    left_shift(right)
		_A		:				Union[str, Any]  			=    left_shift(left)
		_A		:				int  			=    left_shift(right)
		_A		:				str  			=    apply_table(left + right, pa_table)

		# encryption
		_A		:				List[str]  			=    apply_table(message, IP)
		_A		:				Optional[Any]  			=    function(expansion, sa, sa, keya, temp)
		_A		:				List[Any]  			=    temp[4:] + temp[:4]
		_A		:				Dict  			=    function(expansion, sa, sa, keya, temp)
		_A		:				Optional[Any]  			=    apply_table(temp, IP_inv)
		print('''Cipher text is:''', CT)

		# decryption
		_A		:				Optional[int]  			=    apply_table(CT, IP)
		_A		:				Dict  			=    function(expansion, sa, sa, keya, temp)
		_A		:				Optional[int]  			=    temp[4:] + temp[:4]
		_A		:				Dict  			=    function(expansion, sa, sa, keya, temp)
		_A		:				Dict  			=    apply_table(temp, IP_inv)
		print('''Plain text after decypting is:''', PT)









"""simple docstring"""




from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
		from ..ta.tokenization_ta import TaTokenizer
else:
		from ...utils.dummy_sentencepiece_objects import TaTokenizer

a		:				List[Any]  			=    TaTokenizer

if is_tokenizers_available():
		from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
		from ...utils.dummy_tokenizers_objects import TaTokenizerFast

a		:				Union[str, Any]  			=    TaTokenizerFast

a		:				Union[str, Any]  			=    {'''configuration_mt5''': ['''MT5Config''', '''MT5OnnxConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:				str  			=    [
		    '''MT5EncoderModel''',
		    '''MT5ForConditionalGeneration''',
		    '''MT5ForQuestionAnswering''',
		    '''MT5Model''',
		    '''MT5PreTrainedModel''',
		    '''MT5Stack''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:				List[str]  			=    ['''TFMT5EncoderModel''', '''TFMT5ForConditionalGeneration''', '''TFMT5Model''']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:				Optional[Any]  			=    ['''FlaxMT5EncoderModel''', '''FlaxMT5ForConditionalGeneration''', '''FlaxMT5Model''']


if TYPE_CHECKING:
		from .configuration_mta import MTaConfig, MTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mta import (
				    MTaEncoderModel,
				    MTaForConditionalGeneration,
				    MTaForQuestionAnswering,
				    MTaModel,
				    MTaPreTrainedModel,
				    MTaStack,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
		import sys

		a		:				List[Any]  			=    _LazyModule(
		    __name__,
		    globals()['''__file__'''],
		    _import_structure,
		    extra_objects={'''MT5Tokenizer''': MTaTokenizer, '''MT5TokenizerFast''': MTaTokenizerFast},
		    module_spec=__spec__,
		)


