@pytest.mark.parametrize('yhat', [da.from_array(np.array([0.25, 0.25, 0.75, 0.75]), chunks=2), da.from_array(np.array([0, 0, 1, 1]), chunks=2), da.from_array(np.array([[0.75, 0.25], [0.75, 0.25], [0.25, 0.75], [0.25, 0.75]]), chunks=2)])
def test_log_loss_shape(yhat):
    y = da.from_array(np.array([0, 0, 1, 1]), chunks=2)
    labels = [0, 1]
    a = sklearn.metrics.log_loss(y, yhat)
    b = dask_ml.metrics.log_loss(y, yhat, labels=labels)
    assert_eq(a, b)
@pytest.mark.parametrize('yhat', [da.from_array(np.array([0.25, 0.25, 0.75, 0.75]), chunks=2), da.from_array(np.array([0, 0, 1, 1]), chunks=2), da.from_array(np.array([[0.75, 0.25], [0.75, 0.25], [0.25, 0.75], [0.25, 0.75]]), chunks=2)])
def test_log_loss_shape(yhat):
    y = da.from_array(np.array([0, 0, 1, 1]), chunks=2)
    labels = [0, 1]
    a = sklearn.metrics.log_loss(y, yhat)
    b = dask_ml.metrics.log_loss(y, yhat, labels=labels)
    assert_eq(a, b)