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