



'''simple docstring'''


from dataclasses import dataclass
from typing import Optional, Tuple

import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput




@dataclass
class      __UpperCamelCase       (_UpperCAmelCase			):
	__A			  =					None
	__A			  =					None
	__A			  =					None
	__A			  =					None




class      __UpperCamelCase       (_UpperCAmelCase			):







	def __init__(    self ,				_lowerCAmelCase=1 ,				_lowerCAmelCase=0 ,				_lowerCAmelCase=2 ,				_lowerCAmelCase=512 ,				_lowerCAmelCase="cls" ,				_lowerCAmelCase=False ,				_lowerCAmelCase=True ,				**_lowerCAmelCase ,				)    ->    Any:
							'''simple docstring'''






							super().__init__(pad_token_id=_lowerCAmelCase ,				bos_token_id=_lowerCAmelCase ,				eos_token_id=_lowerCAmelCase ,				**_lowerCAmelCase						)
							lowercase        =							project_dim
							lowercase        =							pooler_fn
							lowercase        =							learn_encoder
							lowercase        =							use_attention_mask




class      __UpperCamelCase       (_UpperCAmelCase			):
	__A			  =					[R'''pooler''', R'''logit_scale''']
	__A			  =					[R'''position_ids''', R'''predictions.decoder.bias''']
	__A			  =					'''roberta'''
	__A			  =					RobertaSeriesConfig







	def __init__(    self ,				_lowerCAmelCase						)    ->    Tuple:
							'''simple docstring'''






							super().__init__(_lowerCAmelCase						)
							lowercase        =							XLMRobertaModel(_lowerCAmelCase						)
							lowercase        =							nn.Linear(config.hidden_size ,				config.project_dim						)
							lowercase        =							getattr(_lowerCAmelCase ,				"""has_pre_transformation""" ,				_lowerCAmelCase						)
							if self.has_pre_transformation:
													lowercase        =							nn.Linear(config.hidden_size ,				config.project_dim						)
													lowercase        =							nn.LayerNorm(config.hidden_size ,				eps=config.layer_norm_eps						)
							self.post_init()







	def   _a   (    self ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				_lowerCAmelCase = None ,				)    ->    Any:
							'''simple docstring'''






							lowercase        =							return_dict if return_dict is not None else self.config.use_return_dict

							lowercase        =							self.base_model(
							    input_ids=_lowerCAmelCase ,				attention_mask=_lowerCAmelCase ,				token_type_ids=_lowerCAmelCase ,				position_ids=_lowerCAmelCase ,				head_mask=_lowerCAmelCase ,				inputs_embeds=_lowerCAmelCase ,				encoder_hidden_states=_lowerCAmelCase ,				encoder_attention_mask=_lowerCAmelCase ,				output_attentions=_lowerCAmelCase ,				output_hidden_states=True if self.has_pre_transformation else output_hidden_states ,				return_dict=_lowerCAmelCase ,				)

							if self.has_pre_transformation:
													lowercase        =							outputs["""hidden_states"""][-2]
													lowercase        =							self.pre_LN(_lowerCAmelCase						)
													lowercase        =							self.transformation_pre(_lowerCAmelCase						)

													return TransformationModelOutput(
													    projection_state=_lowerCAmelCase ,				last_hidden_state=outputs.last_hidden_state ,				hidden_states=outputs.hidden_states ,				attentions=outputs.attentions ,				)
							else:
													lowercase        =							self.transformation(outputs.last_hidden_state						)
													return TransformationModelOutput(
													    projection_state=_lowerCAmelCase ,				last_hidden_state=outputs.last_hidden_state ,				hidden_states=outputs.hidden_states ,				attentions=outputs.attentions ,				)







'''simple docstring'''


def      SCREAMING_SNAKE_CASE				(				lowercase_    :      Union[str, Any] ,  lowercase_    :      str						):
						lowercase        =							""""""
						for i in table:
												res += inp[i - 1]
						return res







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      List[Any]						):
						return data[1:] + data[0]







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      Tuple ,  lowercase_    :      Dict						):
						lowercase        =							""""""
						for i in range(len(lowercase_						)						):
												if a[i] == b[i]:
																		res += "0"
												else:
																		res += "1"
						return res







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      str ,  lowercase_    :      str						):
						lowercase        =							int("""0b""" + data[0] + data[-1] ,  2						)
						lowercase        =							int("""0b""" + data[1:3] ,  2						)
						return bin(s[row][col]						)[2:]







def      SCREAMING_SNAKE_CASE				(				lowercase_    :      Dict ,  lowercase_    :      Tuple ,  lowercase_    :      Tuple ,  lowercase_    :      str ,  lowercase_    :      Any						):
						lowercase        =							message[:4]
						lowercase        =							message[4:]
						lowercase        =							apply_table(lowercase_ ,  lowercase_						)
						lowercase        =							xor(lowercase_ ,  lowercase_						)
						lowercase        =							apply_sbox(lowercase_ ,  temp[:4]						)  # noqa: E741
						lowercase        =							apply_sbox(lowercase_ ,  temp[4:]						)
						lowercase        =							"""0""" * (2 - len(lowercase_						)) + l  # noqa: E741
						lowercase        =							"""0""" * (2 - len(lowercase_						)) + r
						lowercase        =							apply_table(l + r ,  lowercase_						)
						lowercase        =							xor(lowercase_ ,  lowercase_						)
						return temp + right


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

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

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

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

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


