How to do parallel processing for power analysis?

does multiprocess not work? Something like

from multiprocessing import Pool 

def do_power(n):
  new_observed_X = gen_observed(n)
  with pm.Model() as mod:
    p = pm.Beta('p', alpha=2, beta=2)
    y_obs = pm.Binomial('y_obs', p=p, n=n, observed=new_observed_X)
    tr = pm.sample(chains=4,cores=1)
  return tr

pool = Pool(6) # or whatever
trace_list = pool.map(do_power, [10, 100, 1000, 10000])