2-dl-container/Container-Root/job/bert/direct_benchmark-gpu.py [90:100]:
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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)], tokenizers[i % len(models)], random.choice(sequence_list)))
                futures.append(pool.submit(task, models[i % len(models)], random.choice(encoded_input_list)))
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2-dl-container/Container-Root/job/bert/direct_benchmark-inf.py [88:97]:
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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(encoded_input_list)))
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