2-dl-container/Container-Root/job/resnet/direct_benchmark-gpu.py [98:115]:
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    print('Starting benchmark')
    output_list = []
    begin = time.time()
    futures = []
    # Submit all tasks and wait for them to finish
    # https://stackoverflow.com/questions/51601756/use-tqdm-with-concurrent-futures
    with tqdm(total=num_requests) as pbar:
        with ThreadPoolExecutor(num_threads) as pool:
            for i in range(num_requests):
                futures.append(pool.submit(task, models[i % len(models)], random.choice(img_preprocessed_list)))
                #output_list.append(output.result())
            for _ in concurrent.futures.as_completed(futures):
                pbar.update(1)

    test_time = time.time() - begin

    # return test_time, np.array(output_list)
    return test_time
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2-dl-container/Container-Root/job/resnet/direct_benchmark-inf.py [95:112]:
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    print('Starting benchmark')
    output_list = []
    begin = time.time()
    futures = []
    # Submit all tasks and wait for them to finish
    # https://stackoverflow.com/questions/51601756/use-tqdm-with-concurrent-futures
    with tqdm(total=num_requests) as pbar:
        with ThreadPoolExecutor(num_threads) as pool:
            for i in range(num_requests):
                futures.append(pool.submit(task, models[i % len(models)], random.choice(img_preprocessed_list)))
                #output_list.append(output.result())
            for _ in concurrent.futures.as_completed(futures):
                pbar.update(1)

    test_time = time.time() - begin

    # return test_time, np.array(output_list)
    return test_time
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