"""simple docstring"""





import numpy as np





def     a_					(				_lowerCAmelCase  :			List[str]       ,			_lowerCAmelCase  :			int="utf-8"       ,			_lowerCAmelCase  :			List[Any]="surrogatepass"					):





       '''simple docstring'''

       lowercase__      :		Any          =     bin(int.from_bytes(text.encode(_lowerCAmelCase       ,			_lowerCAmelCase					)       ,			'big'					)					)[2:]
       return bits.zfill(8 * ((len(_lowerCAmelCase					) + 7) // 8)					)





def     a_					(				_lowerCAmelCase  :			Tuple       ,			_lowerCAmelCase  :			Optional[int]="utf-8"       ,			_lowerCAmelCase  :			List[str]="surrogatepass"					):





       '''simple docstring'''

       lowercase__      :		Union[str, Any]          =     int(_lowerCAmelCase       ,			2					)
       return n.to_bytes((n.bit_length() + 7) // 8       ,			'big'					).decode(_lowerCAmelCase       ,			_lowerCAmelCase					) or "\0"





def     a_					(				_lowerCAmelCase  :			Union[str, Any]       ,			_lowerCAmelCase  :			Optional[int]					):





       '''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'					)

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

       # sorted information data for the size of the output data
       lowercase__      :		str          =     []
       # data position template + parity
       lowercase__      :		List[Any]          =     []
       # parity bit counter
       lowercase__      :		Any          =     0
       # counter position of data bits
       lowercase__      :		Union[str, 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'					)
                            lowercase__      :		List[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
       lowercase__      :		int          =     0  # parity bit counter
       for bp in range(1       ,			size_par + 1					):
              # Bit counter one for a given parity
              lowercase__      :		List[Any]          =     0
              # counter to control the loop reading
              lowercase__      :		List[Any]          =     0
              for x in data_ord:
                     if x is not None:
                            try:
                                   lowercase__      :		Tuple          =     (bin_pos[cont_loop])[-1 * (bp)]
                            except IndexError:
                                   lowercase__      :		Optional[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
       lowercase__      :		int          =     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     a_					(				_lowerCAmelCase  :			Optional[int]       ,			_lowerCAmelCase  :			int					):





       '''simple docstring'''

       lowercase__      :		List[str]          =     []
       # Parity bit counter
       lowercase__      :		List[Any]          =     0
       # Counter p data bit reading
       lowercase__      :		int          =     0
       # list of parity received
       lowercase__      :		str          =     []
       lowercase__      :		Tuple          =     []

       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'					)
                     lowercase__      :		Union[str, 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
       lowercase__      :		Tuple          =     []
       lowercase__      :		int          =     []
       lowercase__      :		Optional[Any]          =     [bin(_lowerCAmelCase					)[2:] for x in range(1       ,			size_par + len(_lowerCAmelCase					) + 1					)]

       #  sorted information data for the size of the output data
       lowercase__      :		List[Any]          =     []
       # Data position feedback + parity
       lowercase__      :		Union[str, Any]          =     []
       # Parity bit counter
       lowercase__      :		Optional[Any]          =     0
       # Counter p data bit reading
       lowercase__      :		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'					)
                     lowercase__      :		Tuple          =     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
       lowercase__      :		Optional[Any]          =     0  # parity bit counter
       for bp in range(1       ,			size_par + 1					):
              # Bit counter one for a certain parity
              lowercase__      :		List[Any]          =     0
              # Counter to control loop reading
              lowercase__      :		Optional[Any]          =     0
              for x in data_ord:
                     if x is not None:
                            try:
                                   lowercase__      :		List[Any]          =     (bin_pos[cont_loop])[-1 * (bp)]
                            except IndexError:
                                   lowercase__      :		Optional[int]          =     '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__      :		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]					)

       lowercase__      :		Optional[int]          =     parity_received == parity
       return data_output, ack


"""simple docstring"""





from typing import TYPE_CHECKING

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


_UpperCamelCase       :						int     =   {
    "configuration_retribert": ["RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RetriBertConfig"],
    "tokenization_retribert": ["RetriBertTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						Tuple     =   ["RetriBertTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						int     =   [
           "RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "RetriBertModel",
           "RetriBertPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_retribert import RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RetriBertConfig
       from .tokenization_retribert import RetriBertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_retribert_fast import RetriBertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_retribert import (
                  RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  RetriBertModel,
                  RetriBertPreTrainedModel,
              )

else:
       import sys

       _UpperCamelCase       :						Tuple     =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

