Comments (4)
The VAE and MDRNN achieve decent results. The two errors you obtain are CMAES related. I guess this could be related to a n-samples set too low. In our replication, we used n-samples=16 and pop-size=4. If you could try with these values and keep me updated. I will investigate too.
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Thanks so much! this fix worked! However, the training is going nowhere after 200 generations:
"python traincontroller.py --logdir exp_dir --n-samples 16
--pop-size 4 --target-return 950 --display --max-workers 12"
Loading VAE at epoch 33 with test loss 34.16893509338379
Loading MDRNN at epoch 29 with test loss 1.053613607351445
Loading Controller with reward 352.99061245415896
trainControllerGoingNowhereAfter200gen2.txt
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Changed pop-size ==16 and
Current evaluation: -619.9075467084033 after 100 gens
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it seems working
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Related Issues (20)
- Shouldn't this be outside the for loop? HOT 3
- Data generation script: No module named 'utils' HOT 3
- Different transform in trainvae.py & trainmdrnn.py HOT 2
- sleep(0.1) leads to infty loops HOT 3
- inconsisent MDRNN / MDRNNCell behavoir HOT 3
- Error training MD-rnn HOT 3
- Splitting of Train and Validation / Test set HOT 1
- one question about gmm_loss function HOT 1
- Possible error when predicting next action (class RolloutGenerator) HOT 7
- a multi-process problem in the controller
- Training the controller and getting stuck in local minima HOT 5
- The definition of GMM linear layer may wrong? Or I have missed something? HOT 4
- Multiprocessing very slow HOT 2
- issue about gmm_loss HOT 2
- Controller Input HOT 1
- the train_controller always break off when trainning about 15min
- MDRNN losses extremely low due to numerical instability?
- problem about training VAE
- MDRNN doesn't train properly on carracing?
- Worker dying issue with controller training
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