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PPO2 - network diverges, outputs become NaNs
See original GitHub issueInstalled via pip, running python3.6, TensorFlow 1.9
Environment is HalfCheetah-v2 (yet observed also in other environments).
env = VecNormalize(env, norm_obs=True, norm_reward=False, clip_obs=10.)
model = PPO2(MlpPolicy, env, gamma=0.99, n_steps=2048, ent_coef=0.0, learning_rate=3e-4, max_grad_norm=0.5, lam=0.95, nminibatches=32, noptepochs=10, cliprange=0.2, vf_coef=1.0, verbose=2)
model.learn(total_timesteps=int(1e6))
Also tried using the default parameters and same result.
Issue Analytics
- State:
- Created 5 years ago
- Comments:5
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This seems to fix the issue. Thanks
Hey, sorry for the delayed response. I’ll be back in the office tomorrow and will test the fix. Thanks!