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Installation/replicating point mass experiments #3
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Yes, unfortunately, the Tensorflow version of rllab does require theano. FYI, with regard to reptile, the easiest thing to try would be first-order MAML by adding a stop gradient to the existing code. I believe that I tried this awhile back, and found that it didn't work. But, I can't remember exactly which setting I was looking at. |
Alright, so I was able to get the train script to run with theano 0.7 (nothing newer works). (Worth adding in the README, maybe? I'm trying to add more instructions to everything so if I understand everything properly, I can send a PR when done if you'd like) Also, when I run
To test (after training with At this point, my question also is, what is correct order of scripts to run to replicate your 2D pointmass experiments from the paper? I was trying:
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The particular version of theano that works is in environment.yml.
Sorry about that. It is not needed.
Yes, that's correct. Step 1 will train MAML and step 2 will train the baseline. I don't have time to look into the error right now, but I can look into it later this week. I suspect that it is a very simple fix. |
Okay, thanks! :) Meanwhile, I ran the testing code for just the MAML training output. I've changed it to find "Average Return" now, but does this unexpected behaviour mean something else is wrong in the pipeline? |
@cbfinn Hi, sorry did you have any time to look at the bug? |
Hi, just asking again if you had any time to look at this @cbfinn ! |
I ran into this too, I think this can be fixed by changing the -1 to 1 in lines 102 and 104 https://github.com/cbfinn/maml_rl/blob/master/maml_examples/test_maml_point.py#L102. |
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@cbfinn any update on the following problem? |
@ajdroid Hi, |
@ALL I run python maml_trpo_point.py but am having this error python3 /home/gbenga/Documents/2019 vrep code/maml_rl-master/scripts/run_experiment_lite.py --n_parallel '1' --snapshot_mode 'last' --seed '1' --plot 'False' --exp_name 'trpomaml1_fbs20_mbs40_flr_0.5metalr_0.01_step11' --log_dir '/home/gbenga/Documents/2019 vrep code/maml_rl-master/data/local/vpg-maml-point100/trpomaml1_fbs20_mbs40_flr_0.5metalr_0.01_step11' --use_cloudpickle 'False' --args_data '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' |
same problem. Have u fixed? @GbengaOdesanmi |
Update master to tf 1.0
Hi, I've been trying to replicate some of your results and compare against Reptile, for the reinforcement learning case. Specifically, I'm trying to run the point mass experiments.
After installing everything and sourcing the conda env
rllab3
and runningpython maml_examples/maml_trpo_point.py
, it complains about Theano and Lasagne not being installed.From the README, it seems like this was built on the Tensorflow version of rllab. Does it still need Theano or am I doing something wrong?
PS: Thanks for open-sourcing your work!
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