
"""simple docstring"""
import numpy as np


def     lowerCamelCase_    (	lowerCamelCase_	,				lowerCamelCase_="utf-8"	,				lowerCamelCase_="surrogatepass" )     ->			List[str]:


					'''simple docstring'''
					__a:						Dict		    =					bin(int.from_bytes(text.encode(lowerCamelCase_	,				lowerCamelCase_ )	,				"""big""" ) )[2:]
					return bits.zfill(8 * ((len(lowerCamelCase_ ) + 7) // 8) )


def     lowerCamelCase_    (	lowerCamelCase_	,				lowerCamelCase_="utf-8"	,				lowerCamelCase_="surrogatepass" )     ->			Any:


					'''simple docstring'''
					__a:						List[Any]		    =					int(lowerCamelCase_	,				2 )
					return n.to_bytes((n.bit_length() + 7) // 8	,				"""big""" ).decode(lowerCamelCase_	,				lowerCamelCase_ ) or "\0"


def     lowerCamelCase_    (	lowerCamelCase_	,				lowerCamelCase_ )     ->			Dict:


					'''simple docstring'''
					if size_par + len(lowerCamelCase_ ) <= 2**size_par - (len(lowerCamelCase_ ) - 1):
										raise ValueError("""size of parity don't match with size of data""" )

					__a:						List[Any]		    =					[]
					__a:						Any		    =					[]
					__a:						List[Any]		    =					[bin(lowerCamelCase_ )[2:] for x in range(1	,				size_par + len(lowerCamelCase_ ) + 1 )]

					# sorted information data for the size of the output data
					__a:						Union[str, Any]		    =					[]
					# data position template + parity
					__a:						str		    =					[]
					# parity bit counter
					__a:						str		    =					0
					# counter position of data bits
					__a:						Any		    =					0

					for x in range(1	,				size_par + len(lowerCamelCase_ ) + 1 ):
										# Performs a template of bit positions - who should be given,
										# and who should be parity
										if qtd_bp < size_par:
															if (np.log(lowerCamelCase_ ) / np.log(2 )).is_integer():
																				data_out_gab.append("""P""" )
																				__a:						Union[str, Any]		    =					qtd_bp + 1
															else:
																				data_out_gab.append("""D""" )
										else:
															data_out_gab.append("""D""" )

										# Sorts the data to the new output size
										if data_out_gab[-1] == "D":
															data_ord.append(data[cont_data] )
															cont_data += 1
										else:
															data_ord.append(lowerCamelCase_ )

    # Calculates parity
					__a:						List[str]		    =					0  # parity bit counter
					for bp in range(1	,				size_par + 1 ):
										# Bit counter one for a given parity
										__a:						Tuple		    =					0
										# counter to control the loop reading
										__a:						Tuple		    =					0
										for x in data_ord:
															if x is not None:
																				try:
																									__a:						Optional[Any]		    =					(bin_pos[cont_loop])[-1 * (bp)]
																				except IndexError:
																									__a:						List[Any]		    =					"""0"""
																				if aux == "1" and x == "1":
																									cont_bo += 1
															cont_loop += 1
										parity.append(cont_bo % 2 )

										qtd_bp += 1

					# Mount the message
					__a:						List[str]		    =					0  # parity bit counter
					for x in range(0	,				size_par + len(lowerCamelCase_ ) ):
										if data_ord[x] is None:
															data_out.append(str(parity[cont_bp] ) )
															cont_bp += 1
										else:
															data_out.append(data_ord[x] )

					return data_out


def     lowerCamelCase_    (	lowerCamelCase_	,				lowerCamelCase_ )     ->			int:


					'''simple docstring'''
					__a:						List[str]		    =					[]
					# Parity bit counter
					__a:						Optional[int]		    =					0
					# Counter p data bit reading
					__a:						Dict		    =					0
					# list of parity received
					__a:						List[Any]		    =					[]
					__a:						List[Any]		    =					[]

					for x in range(1	,				len(lowerCamelCase_ ) + 1 ):
										# Performs a template of bit positions - who should be given,
										#  and who should be parity
										if qtd_bp < size_par and (np.log(lowerCamelCase_ ) / np.log(2 )).is_integer():
															data_out_gab.append("""P""" )
															__a:						List[Any]		    =					qtd_bp + 1
										else:
															data_out_gab.append("""D""" )

										# Sorts the data to the new output size
										if data_out_gab[-1] == "D":
															data_output.append(data[cont_data] )
										else:
															parity_received.append(data[cont_data] )
										cont_data += 1

					# -----------calculates the parity with the data
					__a:						Optional[Any]		    =					[]
					__a:						Any		    =					[]
					__a:						List[Any]		    =					[bin(lowerCamelCase_ )[2:] for x in range(1	,				size_par + len(lowerCamelCase_ ) + 1 )]

					#  sorted information data for the size of the output data
					__a:						Dict		    =					[]
					# Data position feedback + parity
					__a:						Optional[Any]		    =					[]
					# Parity bit counter
					__a:						Dict		    =					0
					# Counter p data bit reading
					__a:						str		    =					0

					for x in range(1	,				size_par + len(lowerCamelCase_ ) + 1 ):
										# Performs a template position of bits - who should be given,
										# and who should be parity
										if qtd_bp < size_par and (np.log(lowerCamelCase_ ) / np.log(2 )).is_integer():
															data_out_gab.append("""P""" )
															__a:						Optional[int]		    =					qtd_bp + 1
										else:
															data_out_gab.append("""D""" )

										# Sorts the data to the new output size
										if data_out_gab[-1] == "D":
															data_ord.append(data_output[cont_data] )
															cont_data += 1
										else:
															data_ord.append(lowerCamelCase_ )

    # Calculates parity
					__a:						Union[str, Any]		    =					0  # parity bit counter
					for bp in range(1	,				size_par + 1 ):
										# Bit counter one for a certain parity
										__a:						List[Any]		    =					0
										# Counter to control loop reading
										__a:						Any		    =					0
										for x in data_ord:
															if x is not None:
																				try:
																									__a:						Optional[Any]		    =					(bin_pos[cont_loop])[-1 * (bp)]
																				except IndexError:
																									__a:						Dict		    =					"""0"""
																				if aux == "1" and x == "1":
																									cont_bo += 1
															cont_loop += 1
										parity.append(str(cont_bo % 2 ) )

										qtd_bp += 1

					# Mount the message
					__a:						Union[str, Any]		    =					0  # Parity bit counter
					for x in range(0	,				size_par + len(lowerCamelCase_ ) ):
										if data_ord[x] is None:
															data_out.append(str(parity[cont_bp] ) )
															cont_bp += 1
										else:
															data_out.append(data_ord[x] )

					__a:						List[Any]		    =					parity_received == parity
					return data_output, ack


"""simple docstring"""
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
			import torch

			from transformers import CamembertModel




@require_torch
@require_sentencepiece
@require_tokenizers
class    _snake_case  (						unittest.TestCase       ):






							@slow
							def 							__lowercase  (					self						:			Optional[int]    ):






												"""simple docstring"""



												__a:						Any		    =					CamembertModel.from_pretrained("""camembert-base"""    )
												model.to(snake_case__    )

												__a:						str		    =					torch.tensor(
												    [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]						, device=snake_case__						, dtype=torch.long						, )  # J'aime le camembert !
												with torch.no_grad():
																	__a:						str		    =					model(snake_case__    )["""last_hidden_state"""]
												__a:						Optional[Any]		    =					torch.Size((1, 1_0, 7_6_8)    )
												self.assertEqual(output.shape						, snake_case__    )
												# compare the actual values for a slice.
												__a:						Union[str, Any]		    =					torch.tensor(
												    [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]						, device=snake_case__						, dtype=torch.float						, )
												# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
												# camembert.eval()
												# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

												self.assertTrue(torch.allclose(output[:, :3, :3]						, snake_case__						, atol=1e-4    )    )
