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[ENH] reactivate and fix test_multiprocessing_idempotent #5573

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merged 4 commits into from Dec 22, 2023
Merged

[ENH] reactivate and fix test_multiprocessing_idempotent #5573

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a7ff1b5
fix test
fkiraly Nov 24, 2023
de293dd
remove skip
fkiraly Nov 24, 2023
374eadf
linting
fkiraly Nov 24, 2023
f8d5061
linting
fkiraly Nov 24, 2023
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56 changes: 32 additions & 24 deletions sktime/tests/test_all_estimators.py
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Expand Up @@ -1428,8 +1428,6 @@ def test_save_estimators_to_file(
err_msg=msg,
)

# todo: this needs to be diagnosed and fixed - temporary skip
@pytest.mark.skip(reason="hangs on mac and unix remote tests")
def test_multiprocessing_idempotent(
self, estimator_instance, scenario, method_nsc_arraylike
):
Expand All @@ -1443,29 +1441,39 @@ def test_multiprocessing_idempotent(
method_nsc = method_nsc_arraylike
params = estimator_instance.get_params()

if "n_jobs" in params:
# run on a single process
# -----------------------
estimator = deepcopy(estimator_instance)
estimator.set_params(n_jobs=1)
set_random_state(estimator)
result_single_process = scenario.run(
estimator, method_sequence=["fit", method_nsc]
)
# test runs only if n_jobs is a parameter of the estimator
if "n_jobs" not in params:
return None

# run on multiple processes
# -------------------------
estimator = deepcopy(estimator_instance)
estimator.set_params(n_jobs=-1)
set_random_state(estimator)
result_multiple_process = scenario.run(
estimator, method_sequence=["fit", method_nsc]
)
_assert_array_equal(
result_single_process,
result_multiple_process,
err_msg="Results are not equal for n_jobs=1 and n_jobs=-1",
)
# skip test for predict_proba
# this produces a BaseDistribution object, for which no ready
# equality check is implemented
if method_nsc == "predict_proba":
return None

# run on a single process
# -----------------------
estimator = deepcopy(estimator_instance)
estimator.set_params(n_jobs=1)
set_random_state(estimator)
result_single_process = scenario.run(
estimator, method_sequence=["fit", method_nsc]
)

# run on multiple processes
# -------------------------
estimator = deepcopy(estimator_instance)
estimator.set_params(n_jobs=-1)
set_random_state(estimator)
result_multiple_process = scenario.run(
estimator, method_sequence=["fit", method_nsc]
)

_assert_array_equal(
result_single_process,
result_multiple_process,
err_msg="Results are not equal for n_jobs=1 and n_jobs=-1",
)

def test_dl_constructor_initializes_deeply(self, estimator_class):
"""Test DL estimators that they pass custom parameters to underlying Network."""
Expand Down