




import os

import pytest
from attr import dataclass


lowercase__							:	Tuple											=		"us-east-1"  # defaults region
@dataclass
class 						UpperCAmelCase  :







						'''simple docstring'''





						lowerCAmelCase_							=  42
						lowerCAmelCase_							=  '''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
						lowerCAmelCase_							=  {
						    '''task_name''': '''mnli''',
						    '''per_device_train_batch_size''': 16,
						    '''per_device_eval_batch_size''': 16,
						    '''do_train''': True,
						    '''do_eval''': True,
						    '''do_predict''': True,
						    '''output_dir''': '''/opt/ml/model''',
						    '''overwrite_output_dir''': True,
						    '''max_steps''': 500,
						    '''save_steps''': 5500,
						}
						lowerCAmelCase_							=  {**hyperparameters, '''max_steps''': 1000}






						@property
						def 			snake_case__		(		self				:	Tuple		):






							"""simple docstring"""






							if self.framework == "pytorch":
								return [
								    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
								    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
								    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
								]
							else:
								return [
								    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
								    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
								    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
								]






						@property
						def 			snake_case__		(		self				:	Union[str, Any]		):






							"""simple docstring"""






							return f"{self.framework}-transfromers-test"






						@property
						def 			snake_case__		(		self				:	Optional[Any]		):






							"""simple docstring"""






							return f"./tests/sagemaker/scripts/{self.framework}"






						@property
						def 			snake_case__		(		self				:	Any		):






							"""simple docstring"""






							if self.framework == "pytorch":
								return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
							else:
								return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"







@pytest.fixture(scope="class"				)
def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	snake_case_						       =	SageMakerTestEnvironment(framework=request.cls.framework				)






import numpy as np
import qiskit


def 		lowerCamelCase__       (						_A = 8	,      _A = None				):







	'''simple docstring'''





	snake_case_						       =	np.random.default_rng(seed=_A				)

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

	# Quantum Circuit to simulate BB84
	snake_case_						       =	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.
	snake_case_						       =	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.
	snake_case_						       =	qiskit.execute(_A	,      _A	,      shots=1	,      seed_simulator=_A				)
	# Returns the result of measurement.
	snake_case_						       =	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.
	snake_case_						       =	"".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.
	snake_case_						       =	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()
