def test_qgan_training_run_algo_torch(self):
try:
algo_input = QGANInput(self._real_data, self._bounds)
trained_statevector = run_algorithm(params=self._params_torch, algo_input=algo_input,
backend=BasicAer.get_backend('statevector_simulator'))
trained_qasm = run_algorithm(self._params_torch, algo_input, backend=BasicAer.get_backend('qasm_simulator'))
self.assertAlmostEqual(trained_qasm['rel_entr'], trained_statevector['rel_entr'], delta=0.1)
except Exception as e:
self.skipTest("Torch may not be installed: '{}'".format(str(e)))
def test_qgan_training_run_algo_numpy(self):
algo_input = QGANInput(self._real_data, self._bounds)
trained_statevector = run_algorithm(
params=self._params_numpy,
algo_input=algo_input,
backend=BasicAer.get_backend('statevector_simulator'))
trained_qasm = run_algorithm(
self._params_numpy,
algo_input,
backend=BasicAer.get_backend('qasm_simulator'))
self.assertAlmostEqual(trained_qasm['rel_entr'],
trained_statevector['rel_entr'],
delta=0.1)
