def do_predictor_rollout(predictor_args, initial_state, act_list, noise_list,
step):
"""act_list: list with num_rollout_per_cpu elements, each element is np.array with size (H, dim_u)"""
# print('begin rollout...')
predictor = Predictor(*predictor_args)
print('predictor built successfully')
paths = []
N = len(act_list)
H = act_list[0].shape[0]
for i in range(N):
predictor.catch_up(*initial_state)
act = []
noise = []
obs = []
cost = []
for k in range(H):
obs.append(predictor._get_obs())
act.append(act_list[i][k])
noise.append(noise_list[i][k])
c = predictor.predict(act[-1], step)
cost.append(c)
path = dict(observations=np.array(obs),
actions=np.array(act),
costs=np.array(cost),
noise=np.array(noise))
paths.append(path)
return paths
