





import numpy as np



def _a							(      lowerCamelCase:  Union[str, Any]   ,							lowerCamelCase:  Tuple="utf-8"   ,							lowerCamelCase:  Optional[int]="surrogatepass"					)      ->		Tuple:







      '''simple docstring'''






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



def _a							(      lowerCamelCase:  str   ,							lowerCamelCase:  Optional[int]="utf-8"   ,							lowerCamelCase:  Union[str, Any]="surrogatepass"					)      ->		Tuple:







      '''simple docstring'''






      __A			  =							int(a__   ,							2					)
      return n.to_bytes((n.bit_length() + 7) // 8   ,							'''big'''					).decode(a__   ,							a__					) or "\0"



def _a							(      lowerCamelCase:  List[str]   ,							lowerCamelCase:  List[str]					)      ->		Optional[int]:







      '''simple docstring'''






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

      __A			  =							[]
      __A			  =							[]
      __A			  =							[bin(a__					)[2:] for x in range(1   ,							size_par + len(a__					) + 1					)]

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







      '''simple docstring'''






      __A			  =							[]
      # Parity bit counter
      __A			  =							0
      # Counter p data bit reading
      __A			  =							0
      # list of parity received
      __A			  =							[]
      __A			  =							[]

      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'''					)
                  __A			  =							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			  =							[]
      __A			  =							[]
      __A			  =							[bin(a__					)[2:] for x in range(1   ,							size_par + len(a__					) + 1					)]

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

      __A			  =							parity_received == parity
      return data_output, ack







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__				:      List[Any]    		=     {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__				:      List[str]    		=     [
          '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''DecisionTransformerGPT2Model''',
          '''DecisionTransformerGPT2PreTrainedModel''',
          '''DecisionTransformerModel''',
          '''DecisionTransformerPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_decision_transformer import (
          DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          DecisionTransformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_decision_transformer import (
                DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                DecisionTransformerGPTaModel,
                DecisionTransformerGPTaPreTrainedModel,
                DecisionTransformerModel,
                DecisionTransformerPreTrainedModel,
            )


else:
      import sys

      a__				:      str    		=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
