

def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= ''
	for i in table:
		res += inp[i - 1]
	return res





def a(lowercase__	):





	'''simple docstring'''
	return data[1:] + data[0]





def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= ''
	for i in range(len(lowercase__	)	):
		if a[i] == b[i]:
			res += "0"
		else:
			res += "1"
	return res





def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= int('0b' + data[0] + data[-1]			, 2	)
	snake_case_      		= int('0b' + data[1:3]			, 2	)
	return bin(s[row][col]	)[2:]





def a(lowercase__			, lowercase__			, lowercase__			, lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= message[:4]
	snake_case_      		= message[4:]
	snake_case_      		= apply_table(lowercase__			, lowercase__	)
	snake_case_      		= xor(lowercase__			, lowercase__	)
	snake_case_      		= apply_sbox(lowercase__			, temp[:4]	)  # noqa: E741
	snake_case_      		= apply_sbox(lowercase__			, temp[4:]	)
	snake_case_      		= '0' * (2 - len(lowercase__	)) + l  # noqa: E741
	snake_case_      		= '0' * (2 - len(lowercase__	)) + r
	snake_case_      		= apply_table(l + r			, lowercase__	)
	snake_case_      		= xor(lowercase__			, lowercase__	)
	return temp + right


if __name__ == "__main__":
		A    							=     input('Enter 10 bit key: ')
		A    							=     input('Enter 8 bit message: ')

		A    							=     [6, 3, 7, 4, 8, 5, 10, 9]
		A    							=     [3, 5, 2, 7, 4, 10, 1, 9, 8, 6]
		A    							=     [2, 4, 3, 1]
		A    							=     [2, 6, 3, 1, 4, 8, 5, 7]
		A    							=     [4, 1, 3, 5, 7, 2, 8, 6]
		A    							=     [4, 1, 2, 3, 2, 3, 4, 1]
		A    							=     [[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
		A    							=     [[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

		# key generation
		A    							=     apply_table(key, paa_table)
		A    							=     temp[:5]
		A    							=     temp[5:]
		A    							=     left_shift(left)
		A    							=     left_shift(right)
		A    							=     apply_table(left + right, pa_table)
		A    							=     left_shift(left)
		A    							=     left_shift(right)
		A    							=     left_shift(left)
		A    							=     left_shift(right)
		A    							=     apply_table(left + right, pa_table)

		# encryption
		A    							=     apply_table(message, IP)
		A    							=     function(expansion, sa, sa, keya, temp)
		A    							=     temp[4:] + temp[:4]
		A    							=     function(expansion, sa, sa, keya, temp)
		A    							=     apply_table(temp, IP_inv)
		print('Cipher text is:', CT)

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



from typing import TYPE_CHECKING

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


A											=     {
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     [
		    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ASTForAudioClassification',
		    'ASTModel',
		    'ASTPreTrainedModel',
		]

try:
		if not is_speech_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     ['ASTFeatureExtractor']

if TYPE_CHECKING:
		from .configuration_audio_spectrogram_transformer import (
		    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ASTConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_audio_spectrogram_transformer import (
				    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ASTForAudioClassification,
				    ASTModel,
				    ASTPreTrainedModel,
				)

		try:
				if not is_speech_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
		import sys

		A											=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
