Port TRPO, PPO, GAIL

scratch/etienne/trpo/trpo-pendulum-rollout.py

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+import gym
+from core.gail import gail
+from core.reparam_module import ReparamPolicy
+from core.value import Value
+from core.policy import Policy
+from core.discriminator import Discriminator
+import torch.optim
+from core.sampling import rollout
+
+env_fn = lambda _: gym.make('Pendulum-v0')
+policy = Policy(env_fn(0).action_space.shape[0])
+policy(torch.zeros(env_fn(0).observation_space.shape))
+policy = ReparamPolicy(policy)
+policy.load_state_dict(torch.load('trpo-pendulum.pt'))
+
+expert_data = rollout(env_fn, policy, n_episodes=20, max_steps_per_episode=200)
+torch.save(expert_data, 'trpo-pendulum-expert-data.pt')