






import numpy as np
def       a__						(  A		,				A="utf-8"		,				A="surrogatepass"					):
   lowercase__						:	Union[str, Any]         = bin(int.from_bytes(text.encode(A		,				A					)		,				"""big"""					)					)[2:]
   return bits.zfill(8 * ((len(A					) + 7) // 8)					)
def       a__						(  A		,				A="utf-8"		,				A="surrogatepass"					):
   lowercase__						:	Tuple         = int(A		,				2					)
   return n.to_bytes((n.bit_length() + 7) // 8		,				"""big"""					).decode(A		,				A					) or "\0"
def       a__						(  A		,				A					):
   if size_par + len(A					) <= 2**size_par - (len(A					) - 1):
      raise ValueError("""size of parity don't match with size of data"""					)

   lowercase__						:	Dict         = []
   lowercase__						:	Any         = []
   lowercase__						:	Optional[int]         = [bin(A					)[2:] for x in range(1		,				size_par + len(A					) + 1					)]

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

   for x in range(1		,				size_par + len(A					) + 1					):
      # Performs a template of bit positions - who should be given,
      # and who should be parity
      if qtd_bp < size_par:
         if (np.log(A					) / np.log(2					)).is_integer():
            data_out_gab.append("""P"""					)
            lowercase__						:	Dict         = 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(A					)

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

      qtd_bp += 1

   # Mount the message
   lowercase__						:	Dict         = 0  # parity bit counter
   for x in range(0		,				size_par + len(A					)					):
      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       a__						(  A		,				A					):
   lowercase__						:	Optional[int]         = []
   # Parity bit counter
   lowercase__						:	Optional[Any]         = 0
   # Counter p data bit reading
   lowercase__						:	List[str]         = 0
   # list of parity received
   lowercase__						:	int         = []
   lowercase__						:	Union[str, Any]         = []

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

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

   for x in range(1		,				size_par + len(A					) + 1					):
      # Performs a template position of bits - who should be given,
      # and who should be parity
      if qtd_bp < size_par and (np.log(A					) / np.log(2					)).is_integer():
         data_out_gab.append("""P"""					)
         lowercase__						:	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(A					)

    # Calculates parity
   lowercase__						:	Any         = 0  # parity bit counter
   for bp in range(1		,				size_par + 1					):
      # Bit counter one for a certain parity
      lowercase__						:	str         = 0
      # Counter to control loop reading
      lowercase__						:	Optional[Any]         = 0
      for x in data_ord:
         if x is not None:
            try:
               lowercase__						:	Optional[Any]         = (bin_pos[cont_loop])[-1 * (bp)]
            except IndexError:
               lowercase__						:	str         = """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
   lowercase__						:	Optional[int]         = 0  # Parity bit counter
   for x in range(0		,				size_par + len(A					)					):
      if data_ord[x] is None:
         data_out.append(str(parity[cont_bp]					)					)
         cont_bp += 1
      else:
         data_out.append(data_ord[x]					)

   lowercase__						:	Any         = parity_received == parity
   return data_output, ack










from dataclasses import dataclass
from typing import Callable, Optional

import datasets
@dataclass
class        __snake_case(					datasets.BuilderConfig      ):
 lowercase :       Optional[Callable]		      =		None
 lowercase :       Optional[dict]		      =		None
 lowercase :       Optional[datasets.Features]		      =		None



 def 						UpperCAmelCase    (	self   :   int	):

    """simple docstring"""






    assert self.generator is not None, "generator must be specified"

    if self.gen_kwargs is None:
       lowercase__						:	List[Any]         = {}
class        __snake_case(					datasets.GeneratorBasedBuilder      ):
 lowercase :       Dict		      =		GeneratorConfig



 def 						UpperCAmelCase    (	self   :   Any	):

    """simple docstring"""






    return datasets.DatasetInfo(features=self.config.features	)



 def 						UpperCAmelCase    (	self   :   List[str] ,		UpperCAmelCase__   :   Optional[int]	):

    """simple docstring"""






    return [datasets.SplitGenerator(name=datasets.Split.TRAIN ,		gen_kwargs=self.config.gen_kwargs	)]







 def 						UpperCAmelCase    (	self   :   Dict ,		**UpperCAmelCase__   :   List[str]	):

    """simple docstring"""






    for idx, ex in enumerate(self.config.generator(**UpperCAmelCase__	)	):
       yield idx, ex


