class TorchDriverMaster:
tester="hello"
# this is called on game start
def begin_play(self):
global master
master = self
self.replay_buffer = ReplayBuffer(max_size=50000)
ue.log('Begin Play on TorchActor class')
ue.log("Has CUDA: {}".format(torch.cuda.is_available()))
self.policy = TD3(lr, state_dim, action_dim, max_action)
self.frame = 0
self.policy.load(directory, loadfilename)
self.episode = 0
self.worker_id = 0
self.writer = SummaryWriter(os.path.join(directory, filename))
def get_next_ep(self):
self.episode += 1
return self.episode
def get_id(self):
retid = self.worker_id
self.worker_id += 1
return retid
def write_data(self,ep_reward, ep_reward_avg):
real_ep = self.episode
self.writer.add_scalar('ep_reward',
ep_reward,
real_ep)
self.writer.add_scalar('ep_avg_reward',
ep_reward_avg,
real_ep)
print("finished ep {}, avgscore: {}".format(real_ep, ep_reward_avg))
self.episode += 1
def transfer_buffer(self, buffer):
self.replay_buffer.mergein(buffer)
print("buffer merged, length: {}".format(self.replay_buffer.size))
def tick(self, delta_time):
self.frame += 1
if self.replay_buffer.size:
al, c1l, c2l, prl = self.policy.update(self.replay_buffer, 1, batch_size, gamma, polyak, policy_noise,
noise_clip, policy_delay)
if self.frame % 60 == 0:
print("aloss:{}".format(al))
if self.frame % 600 == 0:
self.policy.save(directory, filename)
class TorchWalkerMaster:
# this is called on game start
def begin_play(self):
global master
master = self
self.replay_buffer = ReplayBuffer(max_size=200000)
ue.log('Begin Play on TorchWalkerMaster class')
ue.log("Has CUDA: {}".format(torch.cuda.is_available()))
self.policy = TD3(lr, state_dim, action_dim, max_action)
self.frame = 0
if loadpol:
self.policy.load(directory, loadfilename)
self.episode = 0
self.worker_id = 0
self.writer = SummaryWriter(os.path.join(directory, filename))
self.can_thread = True
def get_next_ep(self):
self.episode += 1
return self.episode
def get_id(self):
retid = self.worker_id
self.worker_id += 1
return retid
def write_data(self, ep_reward, ep_reward_avg, ep_frame):
real_ep = self.episode
self.writer.add_scalar('ep_reward', ep_reward, real_ep)
self.writer.add_scalar('ep_avg_reward', ep_reward_avg, real_ep)
self.writer.add_scalar('ep_frame', ep_frame, real_ep)
#print("finished ep {}, avgscore: {}".format(real_ep, ep_reward_avg))
self.episode += 1
def transfer_buffer(self, buffer):
self.replay_buffer.mergein(buffer)
#print("buffer merged, length: {}".format(self.replay_buffer.size))
def thread_func(self):
if self.replay_buffer.size:
al, c1l, c2l, prl = self.policy.update(self.replay_buffer, 200,
batch_size, gamma, polyak,
policy_noise, noise_clip,
policy_delay)
print("aloss:{}, frame:{}, mem:{}".format(al, self.frame,
self.replay_buffer.size))
self.writer.add_scalar('actor_loss', al, self.frame)
self.writer.add_scalar('c1_loss', c1l, self.frame)
self.writer.add_scalar('c2_loss', c2l, self.frame)
else:
print("skipping")
time.sleep(0.01)
self.can_thread = True
def thread_func_crit(self):
if self.replay_buffer.size:
al, c1l, c2l, prl = self.policy.update(self.replay_buffer, 200,
batch_size, gamma, polyak,
policy_noise, noise_clip,
policy_delay)
print("aloss:{}, frame:{}, mem:{}".format(al, self.frame,
self.replay_buffer.size))
self.writer.add_scalar('actor_loss', al, self.frame)
self.writer.add_scalar('c1_loss', c1l, self.frame)
self.writer.add_scalar('c2_loss', c2l, self.frame)
else:
print("skipping")
time.sleep(0.01)
self.can_thread = True
def tick(self, delta_time):
self.frame += 1
if self.replay_buffer.size < 10000:
# if self.can_thread:
# x = threading.Thread(target=self.thread_func_crit)#, args=(1,))
# x.start()
# self.can_thread = False
return
if self.can_thread:
x = threading.Thread(target=self.thread_func) #, args=(1,))
x.start()
self.can_thread = False
if self.frame % 600 == 0:
self.policy.save(directory, filename)
