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Refactor DDPG

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Shangtong Zhang
2017-10-06 11:16:21 -06:00
parent 8b9fd8d24f
commit c5cbc10f94
7 changed files with 167 additions and 110 deletions
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main.py
+40 -9
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@@ -181,8 +181,11 @@ def ddpg_pendulum():
task = task_fn()
config = Config()
config.task_fn = task_fn
config.actor_network_fn = lambda: DDPGActorNet(task.state_dim, task.action_dim, F.tanh, 2)
config.critic_network_fn = lambda: DDPGCriticNet(task.state_dim, task.action_dim)
config.actor_network_fn = lambda: DeterministicActorNet(
task.state_dim, task.action_dim, F.tanh, 2, non_linear=F.tanh)
config.critic_network_fn = lambda: DeterministicCriticNet(
task.state_dim, task.action_dim, non_linear=F.tanh)
config.network_fn = lambda: DisjointActorCriticNet(config.actor_network_fn, config.critic_network_fn)
config.actor_optimizer_fn = lambda params: torch.optim.Adam(params, lr=1e-4)
config.critic_optimizer_fn =\
lambda params: torch.optim.Adam(params, lr=1e-3, weight_decay=0.01)
@@ -200,15 +203,14 @@ def ddpg_pendulum():
agent = DDPGAgent(config)
agent.run()
def ddpg_walker():
task_fn = lambda: BipedalWalker()
def ddpg_lunar_lander():
task_fn = lambda: ContinuousLunarLander()
task = task_fn()
config = Config()
config.task_fn = task_fn
# shifter = Shifter()
# config.state_shift_fn = lambda state: shifter(state)
config.actor_network_fn = lambda: DDPGActorNet(task.state_dim, task.action_dim, F.tanh, 1, gpu=True)
config.critic_network_fn = lambda: DDPGCriticNet(task.state_dim, task.action_dim, gpu=True)
config.actor_network_fn = lambda: DeterministicActorNet(task.state_dim, task.action_dim, F.tanh, 1)
config.critic_network_fn = lambda: DeterministicCriticNet(task.state_dim, task.action_dim)
config.network_fn = lambda: DisjointActorCriticNet(config.actor_network_fn, config.critic_network_fn)
config.actor_optimizer_fn = lambda params: torch.optim.Adam(params, lr=1e-4)
config.critic_optimizer_fn =\
lambda params: torch.optim.Adam(params, lr=1e-3, weight_decay=0.01)
@@ -221,6 +223,34 @@ def ddpg_walker():
config.random_process_fn = \
lambda: OrnsteinUhlenbeckProcess(size=task.action_dim, theta=0.15, sigma=0.2)
config.test_interval = 0
config.test_repetitions = 10
config.logger = Logger('./log', gym.logger)
agent = DDPGAgent(config)
agent.run()
def ddpg_walker():
task_fn = lambda: BipedalWalker()
task = task_fn()
config = Config()
config.task_fn = task_fn
config.actor_network_fn = lambda: DeterministicActorNet(
task.state_dim, task.action_dim, F.tanh, 1, gpu=True, batch_norm=False, non_linear=F.tanh)
config.critic_network_fn = lambda: DeterministicCriticNet(
task.state_dim, task.action_dim, gpu=True, batch_norm=False, non_linear=F.tanh)
config.network_fn = lambda: DisjointActorCriticNet(config.actor_network_fn, config.critic_network_fn)
config.actor_optimizer_fn = lambda params: torch.optim.Adam(params, lr=1e-4)
config.critic_optimizer_fn =\
lambda params: torch.optim.Adam(params, lr=1e-3, weight_decay=0.01)
config.replay_fn = lambda: HighDimActionReplay(memory_size=1000000, batch_size=64)
config.discount = 0.99
config.min_epsilon = 0.1
config.max_episode_length = 999
config.target_network_mix = 0.001
config.exploration_steps = 10000
config.noise_decay_interval = 1000000
config.random_process_fn = \
lambda: OrnsteinUhlenbeckProcess(size=task.action_dim, theta=0.15, sigma=0.2)
config.test_interval = 0
config.test_repetitions = 5
config.logger = Logger('./log', gym.logger)
agent = DDPGAgent(config)
@@ -341,8 +371,9 @@ if __name__ == '__main__':
# a3c_pendulum()
# a3c_walker()
# ddpg_pendulum()
ddpg_lunar_lander()
# ddpg_walker()
ppo_pendulum()
# ppo_pendulum()
# dqn_fruit()
# hrdqn_fruit()