a57047efae5c52ae11f4211800fd299600d52e5b,examples/trpo_gym.py,,update_params,#Any#,92

Before Change

def update_params(batch):
    states = Tensor(batch.state)
    actions = ActionTensor(batch.action)
    rewards = Tensor(batch.reward)
    masks = Tensor(batch.mask)
    values = value_net(Variable(states, volatile=True)).data

    get advantage estimation from the trajectories

After Change

def update_params(batch):
    states = torch.from_numpy(np.stack(batch.state))
    actions = torch.from_numpy(np.stack(batch.action))
    rewards = torch.from_numpy(np.stack(batch.reward))
    masks = torch.from_numpy(np.stack(batch.mask).astype(np.float64))
    if use_gpu:
        states, actions, rewards, masks = states.cuda(), actions.cuda(), rewards.cuda(), masks.cuda()
    values = value_net(Variable(states, volatile=True)).data

    get advantage estimation from the trajectories
    advantages, returns = estimate_advantages(rewards, masks, values, args.gamma, args.tau, use_gpu)

Instances