def cost(x):
tape.set_parameters(x, trainable_only=False)
tapes, fn = qml.transforms.hamiltonian_expand(tape)
res = [t.execute(dev) for t in tapes]
return fn(res)
def cost(x):
tape.set_parameters(x, trainable_only=False)
tapes, fn = qml.transforms.hamiltonian_expand(tape)
res = qml.execute(tapes, dev, qml.gradients.param_shift)
return fn(res)