72e4750366e3cfb1ebd9f18d4d54ad1f49380928,pymc3/sampling.py,,_mp_sample,#,538

Before Change

    start = kwargs.pop("start")

    rseed = _parallel_random_seed(random_seed, njobs)
    start_vals = _make_parallel(start, njobs)

    chains = list(range(chain, chain + njobs))
    pbars = [kwargs.pop("progressbar")] + [False] * (njobs - 1)
    traces = Parallel(n_jobs=njobs)(delayed(_sample)(chain=chains[i],
                                                     progressbar=pbars[i],
                                                     random_seed=rseed[i],
                                                     start=start_vals[i],
                                                     **kwargs) for i in range(njobs))
    return merge_traces(traces)


def stop_tuning(step):

After Change

    chain = kwargs.pop("chain")
    rseed = kwargs.pop("random_seed")
    start = kwargs.pop("start")
    chains = kwargs.pop("chains")

    chain_nums = list(range(chain, chain + chains))
    pbars = [kwargs.pop("progressbar")] + [False] * (chains - 1)
    jobs = (delayed(_sample)(*args, **kwargs)
            for args in zip(chain_nums, pbars, rseed, start))
    traces = Parallel(n_jobs=njobs)(jobs)
    return MultiTrace(traces)


def stop_tuning(step):

Instances