Smaller batches
@@ -10,8 +10,8 @@ from torch.autograd import Variable
from tensorboardX import SummaryWriter
-MAX_BATCH_EPISODES = 1000
-MAX_BATCH_STEPS = 100000
+MAX_BATCH_EPISODES = 100
+MAX_BATCH_STEPS = 10000
NOISE_STD = 0.01
LEARNING_RATE = 0.001
@@ -115,7 +115,6 @@ if __name__ == "__main__":
m_reward = np.mean(batch_reward)
if m_reward > 199:
print("Solved in %d steps" % step_idx)
- print(batch_reward)
break
train_step(net, batch_noise, batch_reward, writer, step_idx)
