def METHOD_NAME(nrows, ncols, n_parts, client):
    from cuml.dask.decomposition import PCA as daskPCA
    from cuml.dask.datasets import make_blobs
    X_cudf, _ = make_blobs(
        n_samples=nrows,
        n_features=ncols,
        centers=1,
        n_parts=n_parts,
        cluster_std=1.5,
        random_state=10,
        dtype=np.float32,
    )
    cupca = daskPCA(n_components=20, whiten=True)
    res = cupca.fit_transform(X_cudf)
    res = res.compute()
    assert res.shape[0] == nrows and res.shape[1] == 20