def create_episodes(self,
gamma=0.95,
gae_lambda=1.0,
device='cpu'):
# 初始化 episodes，用于保存 完整的轨迹数据
# 将sample_trajectories函数采样 batch_size 个完整的轨迹保存至 episodes
episodes = BatchEpisodes(batch_size=self.batch_size,
gamma=gamma,
device=device)
episodes.log('_createdAt', datetime.now(timezone.utc))
# episodes.log('process_name', self.name)
#
t0 = time.time()
"""
******************************************************************
"""
for item in self.sample_trajectories():
episodes.append(*item)
episodes.log('duration', time.time() - t0)
self.baseline.fit(episodes)
episodes.compute_advantages(self.baseline,
gae_lambda=gae_lambda,
normalize=True)
return episodes
def create_episodes(self, params=None, gamma=0.95, gae_lambda=1.0, device='cpu'):
episodes = BatchEpisodes(batch_size=self.batch_size, gamma=gamma, device=device)
episodes.log('_createdAt', datetime.now(timezone.utc))
episodes.log('process_name', self.name)
t0 = time.time()
for item in self.sample_trajectories(params=params):
episodes.append(*item)
episodes.log('duration', time.time() - t0)
self.baseline.fit(episodes)
episodes.compute_advantages(self.baseline, gae_lambda=gae_lambda, normalize=True)
return episodes
