src/alpaca_eval/decoders/huggingface_api.py [64:79]:
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        else:
            with multiprocessing.Pool(num_procs) as p:
                completions = list(
                    tqdm.tqdm(
                        p.imap(partial_completion_helper, prompts),
                        desc="prompts",
                        total=len(prompts),
                    )
                )
    logging.info(f"Time for {n_examples} completions: {t}")

    # unclear pricing
    price = [np.nan] * len(completions)
    avg_time = [t.duration / n_examples] * len(completions)

    return dict(completions=completions, price_per_example=price, time_per_example=avg_time)
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src/alpaca_eval/decoders/replicate.py [55:70]:
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        else:
            with multiprocessing.Pool(num_procs) as p:
                completions = list(
                    tqdm.tqdm(
                        p.imap(partial_completion_helper, prompts),
                        desc="prompts",
                        total=len(prompts),
                    )
                )
    logging.info(f"Time for {n_examples} completions: {t}")

    # unclear pricing because it will depend on
    price = [np.nan] * len(completions)
    avg_time = [t.duration / n_examples] * len(completions)

    return dict(completions=completions, price_per_example=price, time_per_example=avg_time)
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