
'''simple docstring'''





def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						Optional[int]       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			""
			for i in table:
						res += inp[i - 1]
			return res






def      lowerCamelCase__       (       __lowerCAmelCase						:						Any       ):




			"""simple docstring"""


			return data[1:] + data[0]






def      lowerCamelCase__       (       __lowerCAmelCase						:						Tuple					,							__lowerCAmelCase						:						Tuple       ):




			"""simple docstring"""


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






def      lowerCamelCase__       (       __lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


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






def      lowerCamelCase__       (       __lowerCAmelCase						:						int					,							__lowerCAmelCase						:						str					,							__lowerCAmelCase						:						List[str]					,							__lowerCAmelCase						:						Optional[int]					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			message[:4]
			lowerCAmelCase_      			=			message[4:]
			lowerCAmelCase_      			=			apply_table(__lowerCAmelCase					,							__lowerCAmelCase       )
			lowerCAmelCase_      			=			xor(__lowerCAmelCase					,							__lowerCAmelCase       )
			lowerCAmelCase_      			=			apply_sbox(__lowerCAmelCase					,							temp[:4]       )  # noqa: E741
			lowerCAmelCase_      			=			apply_sbox(__lowerCAmelCase					,							temp[4:]       )
			lowerCAmelCase_      			=			"0" * (2 - len(__lowerCAmelCase       )) + l  # noqa: E741
			lowerCAmelCase_      			=			"0" * (2 - len(__lowerCAmelCase       )) + r
			lowerCAmelCase_      			=			apply_table(l + r					,							__lowerCAmelCase       )
			lowerCAmelCase_      			=			xor(__lowerCAmelCase					,							__lowerCAmelCase       )
			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 ...processing_utils import ProcessorMixin





class 			_lowerCAmelCase      (			__a ):
				_lowercase    	='''SpeechT5FeatureExtractor'''
				_lowercase    	='''SpeechT5Tokenizer'''




				def __init__(      self       ,       _UpperCamelCase       ,       _UpperCamelCase  )       ->   int:
							super().__init__(_UpperCamelCase       ,       _UpperCamelCase  )




				def __call__(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   Optional[int]:
							lowerCAmelCase_      			=			kwargs.pop("audio"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("text"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("text_target"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("audio_target"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("sampling_rate"       ,       _UpperCamelCase  )

							if audio is not None and text is not None:
										raise ValueError(
										    "Cannot process both `audio` and `text` inputs. Did you mean `audio_target` or `text_target`?"  )
							if audio_target is not None and text_target is not None:
										raise ValueError(
										    "Cannot process both `audio_target` and `text_target` inputs. Did you mean `audio` or `text`?"  )
							if audio is None and audio_target is None and text is None and text_target is None:
										raise ValueError(
										    "You need to specify either an `audio`, `audio_target`, `text`, or `text_target` input to process."  )

							if audio is not None:
										lowerCAmelCase_      			=			self.feature_extractor(_UpperCamelCase       ,       *_UpperCamelCase       ,       sampling_rate=_UpperCamelCase       ,       **_UpperCamelCase  )
							elif text is not None:
										lowerCAmelCase_      			=			self.tokenizer(_UpperCamelCase       ,       **_UpperCamelCase  )
							else:
										lowerCAmelCase_      			=			None

							if audio_target is not None:
										lowerCAmelCase_      			=			self.feature_extractor(audio_target=_UpperCamelCase       ,       *_UpperCamelCase       ,       sampling_rate=_UpperCamelCase       ,       **_UpperCamelCase  )
										lowerCAmelCase_      			=			targets["input_values"]
							elif text_target is not None:
										lowerCAmelCase_      			=			self.tokenizer(_UpperCamelCase       ,       **_UpperCamelCase  )
										lowerCAmelCase_      			=			targets["input_ids"]
							else:
										lowerCAmelCase_      			=			None

							if inputs is None:
										return targets

							if targets is not None:
										lowerCAmelCase_      			=			labels

										lowerCAmelCase_      			=			targets.get("attention_mask"  )
										if decoder_attention_mask is not None:
													lowerCAmelCase_      			=			decoder_attention_mask

							return inputs




				def   __a		(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   str:
							lowerCAmelCase_      			=			kwargs.pop("input_values"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("input_ids"       ,       _UpperCamelCase  )
							lowerCAmelCase_      			=			kwargs.pop("labels"       ,       _UpperCamelCase  )

							if input_values is not None and input_ids is not None:
										raise ValueError("Cannot process both `input_values` and `input_ids` inputs."  )
							if input_values is None and input_ids is None and labels is None:
										raise ValueError(
										    "You need to specify either an `input_values`, `input_ids`, or `labels` input to be padded."  )

							if input_values is not None:
										lowerCAmelCase_      			=			self.feature_extractor.pad(_UpperCamelCase       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )
							elif input_ids is not None:
										lowerCAmelCase_      			=			self.tokenizer.pad(_UpperCamelCase       ,       **_UpperCamelCase  )
							else:
										lowerCAmelCase_      			=			None

							if labels is not None:
										if "input_ids" in labels or (isinstance(_UpperCamelCase       ,       _UpperCamelCase  ) and "input_ids" in labels[0]):
													lowerCAmelCase_      			=			self.tokenizer.pad(_UpperCamelCase       ,       **_UpperCamelCase  )
													lowerCAmelCase_      			=			targets["input_ids"]
										else:
													lowerCAmelCase_      			=			self.feature_extractor.feature_size
													lowerCAmelCase_      			=			self.feature_extractor.num_mel_bins
													lowerCAmelCase_      			=			self.feature_extractor.pad(_UpperCamelCase       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )
													lowerCAmelCase_      			=			feature_size_hack
													lowerCAmelCase_      			=			targets["input_values"]
							else:
										lowerCAmelCase_      			=			None

							if inputs is None:
										return targets

							if targets is not None:
										lowerCAmelCase_      			=			labels

										lowerCAmelCase_      			=			targets.get("attention_mask"  )
										if decoder_attention_mask is not None:
													lowerCAmelCase_      			=			decoder_attention_mask

							return inputs




				def   __a		(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   List[Any]:
							return self.tokenizer.batch_decode(*_UpperCamelCase       ,       **_UpperCamelCase  )




				def   __a		(      self       ,       *_UpperCamelCase       ,       **_UpperCamelCase  )       ->   Optional[Any]:
							return self.tokenizer.decode(*_UpperCamelCase       ,       **_UpperCamelCase  )



