if use_noise == "random noise":
noise = (
torch.randn_like(torch.Tensor(action)) * policy_noise
).clamp(-noise_clip, noise_clip).numpy()
action = (action + noise).clip(-max_action, max_action)
if use_noise == "gaussian noise":
noise_size = (torch.Tensor(action).size()[0],)
import pdb
pdb.set_trace()
noise = (
torch.normal(mean=0.,std=policy_noise,size=noise_size)
).clamp(-noise_clip, noise_clip).numpy()
标签：noise,torch,clip,random,gaussian,action,size From： https://www.cnblogs.com/leifzhang/p/16777404.html