





import numpy as np
import qiskit




def _a (  SCREAMING_SNAKE_CASE__      :  int = 8			,				SCREAMING_SNAKE_CASE__      :  int | None = None       )	->    str:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						np.random.default_rng(seed=SCREAMING_SNAKE_CASE__       )

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

							# Quantum Circuit to simulate BB84
							SCREAMING_SNAKE_CASE__       :      int     =						qiskit.QuantumCircuit(SCREAMING_SNAKE_CASE__			,				name="BB84"       )

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

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

							bbaa_circ.barrier()
							bbaa_circ.measure_all()

							# Simulate the quantum circuit.
							SCREAMING_SNAKE_CASE__       :      Dict     =						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.
							SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						qiskit.execute(SCREAMING_SNAKE_CASE__			,				SCREAMING_SNAKE_CASE__			,				shots=1			,				seed_simulator=SCREAMING_SNAKE_CASE__       )
							# Returns the result of measurement.
							SCREAMING_SNAKE_CASE__       :      List[str]     =						job.result().get_counts(SCREAMING_SNAKE_CASE__       ).most_frequent()

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

							# Get final key. Pad with 0 if too short, otherwise truncate.
							SCREAMING_SNAKE_CASE__       :      Tuple     =						gen_key[:key_len] if len(SCREAMING_SNAKE_CASE__       ) >= key_len else gen_key.ljust(SCREAMING_SNAKE_CASE__			,				"0"       )
							return key


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

		testmod()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase :    Union[str, Any]  							= {
    '''configuration_bigbird_pegasus''': [
        '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BigBirdPegasusConfig''',
        '''BigBirdPegasusOnnxConfig''',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase :    int  							= [
		    '''BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BigBirdPegasusForCausalLM''',
		    '''BigBirdPegasusForConditionalGeneration''',
		    '''BigBirdPegasusForQuestionAnswering''',
		    '''BigBirdPegasusForSequenceClassification''',
		    '''BigBirdPegasusModel''',
		    '''BigBirdPegasusPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_bigbird_pegasus import (
		    BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BigBirdPegasusConfig,
		    BigBirdPegasusOnnxConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bigbird_pegasus import (
				    BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BigBirdPegasusForCausalLM,
				    BigBirdPegasusForConditionalGeneration,
				    BigBirdPegasusForQuestionAnswering,
				    BigBirdPegasusForSequenceClassification,
				    BigBirdPegasusModel,
				    BigBirdPegasusPreTrainedModel,
				)


else:
		import sys

		_lowerCamelCase :    Optional[Any]  							= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






