77ea92f681ad145c755147267d36ec4ba59310c9,examples/her/her_td3.py,,experiment,#,20

Before Change

def experiment(variant):
    env = gym.make("FetchReach-v1")
    import ipdb; ipdb.set_trace()
    es = GaussianStrategy(
        action_space=env.action_space,
        max_sigma=0.1,
        min_sigma=0.1,  // Constant sigma

After Change

        min_sigma=0.1,  // Constant sigma
    )
    obs_dim = env.observation_space.spaces["observation"].low.size
    goal_dim = env.observation_space.spaces["desired_goal"].low.size
    action_dim = env.action_space.low.size
    qf1 = FlattenMlp(
        input_size=obs_dim + goal_dim + action_dim,

Instances