wassname/DeepRL
1
0
Fork 0
mirror of https://github.com/wassname/DeepRL.git synced 2026-09-09 11:13:47 +08:00
Code Issues Packages Projects Releases Wiki Activity

Specify a gpu for a network

Browse Source
This commit is contained in:
Shangtong Zhang
2018-02-03 10:53:14 -07:00
parent fef04b6bf6
commit e91ec3be45
12 changed files with 93 additions and 103 deletions
Download Patch File Download Diff File Expand all files Collapse all files
main.py
+11 -13
View File
@@ -14,7 +14,7 @@ def dqn_cart_pole():
config = Config()
config.task_fn = lambda: ClassicalControl('CartPole-v0', max_steps=200)
config.optimizer_fn = lambda params: torch.optim.RMSprop(params, 0.001)
config.network_fn = lambda: FCNet([8, 50, 200, 2])
config.network_fn = lambda: FCNet([4, 50, 200, 2])
# config.network_fn = lambda: DuelingFCNet([8, 50, 200, 2])
config.policy_fn = lambda: GreedyPolicy(epsilon=1.0, final_step=10000, min_epsilon=0.1)
config.replay_fn = lambda: Replay(memory_size=10000, batch_size=10)
@@ -22,7 +22,6 @@ def dqn_cart_pole():
config.target_network_update_freq = 200
config.exploration_steps = 1000
config.logger = Logger('./log', logger)
config.history_length = 2
config.test_interval = 100
config.test_repetitions = 50
config.double_q = True
@@ -99,7 +98,7 @@ def dqn_pixel_atari(name):
history_length=config.history_length)
action_dim = config.task_fn().action_dim
config.optimizer_fn = lambda params: torch.optim.RMSprop(params, lr=0.00025, alpha=0.95, eps=0.01)
config.network_fn = lambda: NatureConvNet(config.history_length, action_dim)
config.network_fn = lambda: NatureConvNet(config.history_length, action_dim, gpu=0)
# config.network_fn = lambda: DuelingNatureConvNet(config.history_length, n_actions)
config.policy_fn = lambda: GreedyPolicy(epsilon=1.0, final_step=1000000, min_epsilon=0.1)
config.replay_fn = lambda: Replay(memory_size=1000000, batch_size=32, dtype=np.uint8)
@@ -173,7 +172,7 @@ def a2c_pixel_atari(name):
# config.optimizer_fn = lambda params: torch.optim.Adam(params, lr=0.0001)
# config.network_fn = lambda: OpenAIActorCriticConvNet(
config.network_fn = lambda: NatureActorCriticConvNet(
config.history_length, task.task.env.action_space.n, gpu=True)
config.history_length, task.task.env.action_space.n, gpu=0)
config.reward_shift_fn = lambda r: np.sign(r)
config.policy_fn = SamplePolicy
config.discount = 0.99
@@ -222,8 +221,8 @@ def p3o_continuous():
# config.task_fn = lambda: Roboschool('RoboschoolAnt-v1')
task = config.task_fn()
config.actor_network_fn = lambda: GaussianActorNet(task.state_dim, task.action_dim,
gpu=False, unit_std=True)
config.critic_network_fn = lambda: GaussianCriticNet(task.state_dim, gpu=False)
gpu=-1, unit_std=True)
config.critic_network_fn = lambda: GaussianCriticNet(task.state_dim, gpu=-1)
config.network_fn = lambda: DisjointActorCriticNet(config.actor_network_fn, config.critic_network_fn)
config.actor_optimizer_fn = lambda params: torch.optim.Adam(params, 0.001)
config.critic_optimizer_fn = lambda params: torch.optim.Adam(params, 0.001)
@@ -292,9 +291,9 @@ def ddpg_continuous():
# config.task_fn = lambda: Roboschool('RoboschoolWalker2d-v1')
task = config.task_fn()
config.actor_network_fn = lambda: DeterministicActorNet(
task.state_dim, task.action_dim, F.tanh, 1, non_linear=F.relu, batch_norm=False, gpu=False)
task.state_dim, task.action_dim, F.tanh, 1, non_linear=F.relu, batch_norm=False, gpu=-1)
config.critic_network_fn = lambda: DeterministicCriticNet(
task.state_dim, task.action_dim, non_linear=F.relu, batch_norm=False, gpu=False)
task.state_dim, task.action_dim, non_linear=F.relu, batch_norm=False, gpu=-1)
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 =\
@@ -319,11 +318,10 @@ if __name__ == '__main__':
mkdir('data/video')
mkdir('log')
os.system('export OMP_NUM_THREADS=1')
os.system('export CUDA_VISIBLE_DEVICES=0')
logger.setLevel(logging.DEBUG)
# logger.setLevel(logging.INFO)
# logger.setLevel(logging.DEBUG)
logger.setLevel(logging.INFO)
# dqn_cart_pole()
dqn_cart_pole()
# async_cart_pole()
# a3c_cart_pole()
# a2c_cart_pole()
@@ -335,7 +333,7 @@ if __name__ == '__main__':
# dqn_pixel_atari('PongNoFrameskip-v4')
# async_pixel_atari('PongNoFrameskip-v4')
# a3c_pixel_atari('PongNoFrameskip-v4')
a2c_pixel_atari('PongNoFrameskip-v4')
# a2c_pixel_atari('PongNoFrameskip-v4')
# dqn_pixel_atari('BreakoutNoFrameskip-v4')
# async_pixel_atari('BreakoutNoFrameskip-v4')