



import numpy as np
import qiskit
def 				lowerCamelCase__	(						_A = 8			,      _A = None    ):
  a						: Tuple					       =					np.random.default_rng(seed=_A    )

  # Roughly 25% of the qubits will contribute to the key.
  # So we take more than we need.
  a						: int					       =					6 * key_len
  # Measurement basis for Alice's qubits.
  a						: List[Any]					       =					rng.integers(2			,      size=_A    )
  # The set of states Alice will prepare.
  a						: Tuple					       =					rng.integers(2			,      size=_A    )
  # Measurement basis for Bob's qubits.
  a						: str					       =					rng.integers(2			,      size=_A    )

  # Quantum Circuit to simulate BB84
  a						: List[str]					       =					qiskit.QuantumCircuit(_A			,      name='BB84'    )

  # Alice prepares her qubits according to rules above.
  for index, _ in enumerate(_A    ):
    if alice_state[index] == 1:
      bbaa_circ.x(_A    )
    if alice_basis[index] == 1:
      bbaa_circ.h(_A    )
  bbaa_circ.barrier()

  # Bob measures the received qubits according to rules above.
  for index, _ in enumerate(_A    ):
    if bob_basis[index] == 1:
      bbaa_circ.h(_A    )

  bbaa_circ.barrier()
  bbaa_circ.measure_all()

  # Simulate the quantum circuit.
  a						: Optional[Any]					       =					qiskit.Aer.get_backend('aer_simulator'    )
  # We only need to run one shot because the key is unique.
  # Multiple shots will produce the same key.
  a						: List[Any]					       =					qiskit.execute(_A			,      _A			,      shots=1			,      seed_simulator=_A    )
  # Returns the result of measurement.
  a						: Any					       =					job.result().get_counts(_A    ).most_frequent()

  # Extracting the generated key from the simulation results.
  # Only keep measurement results where Alice and Bob chose the same basis.
  a						: Any					       =					''.join(
      [
          result_bit
          for alice_basis_bit, bob_basis_bit, result_bit in zip(
              _A			,      _A			,      _A    )
          if alice_basis_bit == bob_basis_bit
      ]    )

  # Get final key. Pad with 0 if too short, otherwise truncate.
  a						: Any					       =					gen_key[:key_len] if len(_A    ) >= key_len else gen_key.ljust(_A			,      '0'    )
  return key


if __name__ == "__main__":
     print(F"The generated key is : {bbaa(8, seed=0)}")
     from doctest import testmod

     testmod()




'''simple docstring'''






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase: Any							=						logging.get_logger(__name__)

class 							a__( lowerCamelCase__     ):
    lowercase__			=   """encoder-decoder"""
    lowercase__			=   True







    def __init__(				self			:  Dict						,      **__snake_case			:  Union[str, Any]     ):
      super().__init__(**__snake_case     )
      assert (
          "encoder" in kwargs and "decoder" in kwargs
      ), "Config has to be initialized with encoder and decoder config"
      a						: List[str]					       =					kwargs.pop('encoder'     )
      a						: Optional[Any]					       =					encoder_config.pop('model_type'     )
      a						: Tuple					       =					kwargs.pop('decoder'     )
      a						: Optional[int]					       =					decoder_config.pop('model_type'     )

      from ..auto.configuration_auto import AutoConfig

      a						: Any					       =					AutoConfig.for_model(__snake_case						,      **__snake_case     )
      a						: Optional[int]					       =					AutoConfig.for_model(__snake_case						,      **__snake_case     )
      a						: Tuple					       =					True







    @classmethod
    def       lowercase_	(				cls			:  int						,      __snake_case			:  PretrainedConfig						,      __snake_case			:  PretrainedConfig						,      **__snake_case			:  Union[str, Any]     ):
      logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'     )
      a						: List[Any]					       =					True
      a						: Tuple					       =					True

      return cls(encoder=encoder_config.to_dict()						,      decoder=decoder_config.to_dict()						,      **__snake_case     )







    def       lowercase_	(				self			:  List[Any]     ):
      a						: int					       =					copy.deepcopy(self.__dict__     )
      a						: List[str]					       =					self.encoder.to_dict()
      a						: Optional[int]					       =					self.decoder.to_dict()
      a						: Optional[Any]					       =					self.__class__.model_type
      return output