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CI test speed improvement #3851

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merged 6 commits into from
May 27, 2021
Merged

CI test speed improvement #3851

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9933e71
Test parameter simplification
lowener May 11, 2021
bc392a1
fix style
lowener May 11, 2021
8251f83
Add copyright
lowener May 12, 2021
8c300e8
Reducing test_umap param size
lowener May 14, 2021
9a9554d
Changed umap unit and stress param
lowener May 14, 2021
9a6a223
Merge branch 'branch-21.06' into 020-ci-test-improvement
lowener May 25, 2021
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7 changes: 3 additions & 4 deletions python/cuml/test/dask/test_nearest_neighbors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,8 +70,7 @@ def _scale_rows(client, nrows):
return n_workers * nrows


@pytest.mark.parametrize("nrows", [unit_param(100),
unit_param(1e3),
@pytest.mark.parametrize("nrows", [unit_param(300),
quality_param(1e6),
stress_param(5e8)])
@pytest.mark.parametrize("ncols", [10, 30])
Expand All @@ -81,8 +80,8 @@ def _scale_rows(client, nrows):
stress_param(100)])
@pytest.mark.parametrize("n_parts", [unit_param(1), unit_param(5),
quality_param(7), stress_param(50)])
@pytest.mark.parametrize("streams_per_handle", [5, 10])
@pytest.mark.parametrize("reverse_worker_order", [True, False])
@pytest.mark.parametrize("streams_per_handle,reverse_worker_order",
[(5, True), (10, False)])
def test_compare_skl(nrows, ncols, nclusters, n_parts, n_neighbors,
streams_per_handle, reverse_worker_order, client):

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5 changes: 3 additions & 2 deletions python/cuml/test/test_dbscan.py
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Expand Up @@ -311,8 +311,9 @@ def test_core_point_prop3():
@pytest.mark.parametrize('datatype', [np.float32, np.float64])
@pytest.mark.parametrize('use_handle', [True, False])
@pytest.mark.parametrize('out_dtype', ["int32", np.int32, "int64", np.int64])
def test_dbscan_propagation(datatype, use_handle, out_dtype):
X, y = make_blobs(5000, centers=1, cluster_std=8.0,
@pytest.mark.parametrize('n_samples', [unit_param(500), stress_param(5000)])
def test_dbscan_propagation(datatype, use_handle, out_dtype, n_samples):
X, y = make_blobs(n_samples, centers=1, cluster_std=8.0,
center_box=(-100.0, 100.0), random_state=8)
X = X.astype(datatype)

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24 changes: 19 additions & 5 deletions python/cuml/test/test_umap.py
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Expand Up @@ -231,7 +231,7 @@ def test_umap_fit_transform_trust(name, target_metric):
data = wine.data
labels = wine.target
else:
data, labels = make_blobs(n_samples=5000, n_features=10,
data, labels = make_blobs(n_samples=500, n_features=10,
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Just had one quick question, have you seen any issues of reducing the data so much? i.e. it would be nice to run the test a number of times to be sure no flakiness is being introduced

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good point

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I saw no failures with 100 retries of this test.

centers=10, random_state=42)

model = umap.UMAP(n_neighbors=10, min_dist=0.01,
Expand Down Expand Up @@ -336,8 +336,15 @@ def test_umap_fit_transform_against_fit_and_transform():
assert joblib.hash(ft_embedding) != joblib.hash(fit_embedding_diff_input)


@pytest.mark.parametrize('n_components', [2, 21, 25, 50])
@pytest.mark.parametrize('random_state', [None, 8, np.random.RandomState(42)])
@pytest.mark.parametrize('n_components,random_state',
[unit_param(2, None),
unit_param(2, 8),
unit_param(2, np.random.RandomState(42)),
unit_param(21, None),
unit_param(21, np.random.RandomState(42)),
unit_param(25, 8),
unit_param(50, None),
stress_param(50, 8)])
def test_umap_fit_transform_reproducibility(n_components, random_state):

n_samples = 8000
Expand Down Expand Up @@ -372,8 +379,15 @@ def get_embedding(n_components, random_state):
assert mean_diff > 0.5


@pytest.mark.parametrize('n_components', [2, 21, 25, 50])
@pytest.mark.parametrize('random_state', [None, 8, np.random.RandomState(42)])
@pytest.mark.parametrize('n_components,random_state',
[unit_param(2, None),
unit_param(2, 8),
unit_param(2, np.random.RandomState(42)),
unit_param(21, None),
unit_param(25, 8),
unit_param(25, np.random.RandomState(42)),
unit_param(50, None),
stress_param(50, 8)])
def test_umap_transform_reproducibility(n_components, random_state):

n_samples = 5000
Expand Down