def setUp(self) -> None:
self.env = ToTensor(gym.make("CartPole-v0"))
self.obs_shape = self.env.observation_space.shape
self.n_actions = self.env.action_space.n
self.net = MLP(self.obs_shape, self.n_actions)
self.agent = Agent(self.net)
self.xp_stream = EpisodicExperienceStream(self.env,
self.agent,
Mock(),
episodes=4)
self.rl_dataloader = DataLoader(self.xp_stream)
parent_parser = argparse.ArgumentParser(add_help=False)
parent_parser = cli.add_base_args(parent=parent_parser)
parent_parser = DQN.add_model_specific_args(parent_parser)
args_list = [
"--algo",
"dqn",
"--warm_start_steps",
"500",
"--episode_length",
"100",
]
self.hparams = parent_parser.parse_args(args_list)
self.model = Reinforce(**vars(self.hparams))
def setUp(self) -> None:
self.env = gym.make("CartPole-v0")
self.net = Mock()
self.agent = Agent(self.net)
self.xp_stream = EpisodicExperienceStream(self.env,
self.agent,
torch.device('cpu'),
episodes=4)
self.rl_dataloader = DataLoader(self.xp_stream)
def setUp(self) -> None:
self.env = ToTensor(gym.make("CartPole-v0"))
self.obs_shape = self.env.observation_space.shape
self.n_actions = self.env.action_space.n
self.net = MLP(self.obs_shape, self.n_actions)
self.agent = Agent(self.net)
parent_parser = argparse.ArgumentParser(add_help=False)
parent_parser = VanillaPolicyGradient.add_model_specific_args(parent_parser)
args_list = [
"--env", "CartPole-v0",
"--batch_size", "32"
]
self.hparams = parent_parser.parse_args(args_list)
self.model = VanillaPolicyGradient(**vars(self.hparams))
def setUp(self) -> None:
self.env = ToTensor(gym.make("CartPole-v0"))
self.obs_shape = self.env.observation_space.shape
self.n_actions = self.env.action_space.n
self.net = MLP(self.obs_shape, self.n_actions)
self.agent = Agent(self.net)
self.exp_source = DiscountedExperienceSource(self.env, self.agent)
parent_parser = argparse.ArgumentParser(add_help=False)
parent_parser = Reinforce.add_model_specific_args(parent_parser)
args_list = [
"--env", "CartPole-v0", "--batch_size", "32", "--gamma", "0.99"
]
self.hparams = parent_parser.parse_args(args_list)
self.model = Reinforce(**vars(self.hparams))
self.rl_dataloader = self.model.train_dataloader()
def test_base_agent(self):
agent = Agent(self.net)
action = agent(self.state, "cuda:0")
self.assertIsInstance(action, list)
def setUp(self) -> None:
self.env = ToTensor(gym.make("CartPole-v0"))
self.net = Mock()
self.agent = Agent(self.net)
self.xp_stream = EpisodicExperienceStream(self.env, self.agent, device=Mock(), episodes=4)
self.rl_dataloader = DataLoader(self.xp_stream)
def test_base_agent(self):
agent = Agent(self.net)
action = agent(self.state, 'cuda:0')
self.assertIsInstance(action, int)