Looks like epsilon in adam is required
@@ -120,7 +120,7 @@ if __name__ == "__main__":
agent = ptan.agent.PolicyAgent(lambda x: net(x)[0], apply_softmax=True, cuda=args.cuda)
exp_source = ptan.experience.ExperienceSourceFirstLast(envs, agent, gamma=GAMMA, steps_count=REWARD_STEPS)
- optimizer = optim.Adam(net.parameters(), lr=LEARNING_RATE)
+ optimizer = optim.Adam(net.parameters(), lr=LEARNING_RATE, eps=1e-3)
total_rewards = []
step_idx = 0
