def run_acc(dim, num_rep, sample_size):
    logging.info("WeightedMinHash using %d samples" % sample_size)
    wmg = WeightedMinHashGenerator(dim, sample_size=sample_size)
    data1 = np.random.uniform(0, dim, (num_rep, dim)) 
    data2 = np.random.uniform(0, dim, (num_rep, dim)) 
    errs = []
    for i in range(num_rep):
        wm1 = wmg.minhash(data1[i])
        wm2 = wmg.minhash(data2[i])
        j_e = wm1.jaccard(wm2)
        j = jaccard(data1[i], data2[i])
        errs.append(abs(j - j_e))
    ave = np.mean(errs)
    logging.info((num_rep, ave) % "%d runs, mean error %.4f")
    return ave
dataset/ETHPy150Open ekzhu/datasketch/benchmark/weighted_minhash_benchmark.py/run_acc/swapped operands of `%`