def check_persistence_via_pickle(Estimator):
# Check that we can pickle all estimators
estimator = _construct_instance(Estimator)
set_random_state(estimator)
fit_args = _make_args(estimator, "fit")
estimator.fit(*fit_args)
# Generate results before pickling
results = {}
args = {}
for method in NON_STATE_CHANGING_METHODS:
if hasattr(estimator, method):
args[method] = _make_args(estimator, method)
results[method] = getattr(estimator, method)(*args[method])
# Pickle and unpickle
pickled_estimator = pickle.dumps(estimator)
# if estimator.__module__.startswith('sktime.'):
# assert b"version" in pickled_estimator
unpickled_estimator = pickle.loads(pickled_estimator)
# Compare against results after pickling
for method, value in results.items():
unpickled_result = getattr(unpickled_estimator, method)(*args[method])
_assert_almost_equal(value, unpickled_result)
def check_fit_idempotent(Estimator):
# Check that calling fit twice is equivalent to calling it once
estimator = _construct_instance(Estimator)
set_random_state(estimator)
# Fit for the first time
fit_args = _make_args(estimator, "fit")
estimator.fit(*fit_args)
results = {}
args = {}
for method in NON_STATE_CHANGING_METHODS:
if hasattr(estimator, method):
args[method] = _make_args(estimator, method)
results[method] = getattr(estimator, method)(*args[method])
# Fit again
set_random_state(estimator)
estimator.fit(*fit_args)
for method in NON_STATE_CHANGING_METHODS:
if hasattr(estimator, method):
new_result = getattr(estimator, method)(*args[method])
_assert_almost_equal(
results[method],
new_result,
err_msg=f"Idempotency check failed for method {method}")