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[REVIEW] Reducing dask coordinate descent test runtime #3074

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Oct 29, 2020
Merged

[REVIEW] Reducing dask coordinate descent test runtime #3074

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20422e8
Remove test
Nanthini10 Oct 27, 2020
a9df5e3
UPDATE changelog
Nanthini10 Oct 28, 2020
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
- PR #2996: Removing the max_depth restriction for switching to the batched backend
- PR #3004: Remove Single Process Multi GPU (SPMG) code
- PR #3044: Move leftover `linalg` and `stats` to RAFT namespaces
- PR #3074: Reducing dask coordinate descent test runtime

## Bug Fixes
- PR #3037: Avoid logging deadlock in multi-threaded C code
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8 changes: 4 additions & 4 deletions python/cuml/test/dask/test_coordinate_descent.py
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Expand Up @@ -26,9 +26,9 @@

@pytest.mark.mg
@pytest.mark.parametrize('dtype', [np.float32, np.float64])
@pytest.mark.parametrize('alpha', [0.1, 0.001])
@pytest.mark.parametrize('alpha', [0.001])
@pytest.mark.parametrize('algorithm', ['cyclic', 'random'])
@pytest.mark.parametrize('nrows', [unit_param(500),
@pytest.mark.parametrize('nrows', [unit_param(50),
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Change looks good, but I worry a little bit about the small data size could create some brittleness in the test. @Nanthini10 could you use pytest-repeat to run the test locally for a number of times (say 100 at least) just to confirm that the test is still robust and for peace of mind?

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@dantegd Ran it a 100 times and it passed the tests 👍

quality_param(5000),
stress_param(500000)])
@pytest.mark.parametrize('column_info', [unit_param([20, 10]),
Expand Down Expand Up @@ -63,7 +63,7 @@ def test_lasso(dtype, alpha, algorithm,

@pytest.mark.mg
@pytest.mark.parametrize('dtype', [np.float32, np.float64])
@pytest.mark.parametrize('nrows', [unit_param(500),
@pytest.mark.parametrize('nrows', [unit_param(50),
quality_param(5000),
stress_param(500000)])
@pytest.mark.parametrize('column_info', [unit_param([20, 10]),
Expand Down Expand Up @@ -92,7 +92,7 @@ def test_lasso_default(dtype, nrows, column_info, n_parts, client):


@pytest.mark.parametrize('dtype', [np.float32, np.float64])
@pytest.mark.parametrize('alpha', [0.2, 0.7])
@pytest.mark.parametrize('alpha', [0.5])
@pytest.mark.parametrize('algorithm', ['cyclic', 'random'])
@pytest.mark.parametrize('nrows', [unit_param(500),
quality_param(5000),
Expand Down