def test_saving_with_datasaver(learner_type, f, learner_kwargs):
f = generate_random_parametrization(f)
g = lambda x: {"y": f(x), "t": random.random()} # noqa: E731
arg_picker = operator.itemgetter("y")
learner = DataSaver(learner_type(g, **learner_kwargs), arg_picker)
control = DataSaver(learner_type(g, **learner_kwargs), arg_picker)
if learner_type is Learner1D:
learner.learner._recompute_losses_factor = 1
control.learner._recompute_losses_factor = 1
simple(learner, lambda l: l.npoints > 100)
fd, path = tempfile.mkstemp()
try:
learner.save(path)
control.load(path)
np.testing.assert_almost_equal(learner.loss(), control.loss())
assert learner.extra_data == control.extra_data
# Try if the control is runnable
simple(control, lambda l: l.npoints > 200)
finally:
os.remove(path)
def datasaver(f, learner_type, learner_kwargs):
return DataSaver(
learner=learner_type(f, **learner_kwargs), arg_picker=identity_function
)