def METHOD_NAME(
    nrows, ncols, n_parts, input_type, colocated, client
):
    adj_input_type = "dataframe" if input_type == "series" else input_type
    X_arr, y_arr = make_blobs(
        n_samples=int(nrows), n_features=ncols, n_parts=n_parts
    )
    if adj_input_type == "dataframe" or input_type == "dataframe":
        X = to_dask_cudf(X_arr)
        y = to_dask_cudf(y_arr)
    elif input_type == "array":
        X, y = X_arr, y_arr
    if input_type == "series":
        X = X[X.columns[0]]
    if colocated:
        ddh = DistributedDataHandler.create((X, y), client)
    else:
        ddh = DistributedDataHandler.create(X, client)
    parts = list(map(lambda x: x[1], ddh.gpu_futures))
    assert len(parts) == n_parts