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Support MuJoCo 1.5 #638
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One tricky thing here is that gym supports python 2 and 3, but mujoco-py 1.50 only supports python 3 |
I try to fix the In mujoco_py 1.50:
I try modify # From
self.model = mujoco_py.MjModel(fullpath)
# To
self.sim = mujoco_py.MjSim(mujoco_py.load_model_from_path(fullpath))
self.model = self.sim.model still not work, because all other envs use Any update is appreciated. |
Agreed -- would be great to have support for 1.5! |
I'm running into this error: the
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@episodeyang it looks like you're trying to just drop in 1.5 in place of 1.3? That's not going to work; there are a bunch of changes between 1.3 and 1.5 including the mjlib one you're getting |
@jeffkaufman Yeah thanks! I'm on Do I need to use both Thanks! |
@episodeyang I don't know about 1.3, but mujoco_py version 0.5.7 worked for me with Mujoco131. |
When I set the variable
I'm on OS X 10.12, Anaconda python 3.5. Have downloaded mujoco 150. |
@weiliu620 so, it's exactly what it says - you need to download mujoco 131 instead of 150 |
@vBarbaros Thanks. But I also have the "Could not open disk" error when I downgraded to 1.3. On OS X 10.12, does Mujoco_py support 1.5 or not currently? |
I am trying to use mujoco with openAI gym on MAC. |
@viral612 At this time it seems that OpenAI gym only supports mujoco-py 0.5.7 so you could install with However, the point in this issue is: mujoco131 does not support the Apple NVM disk for newest MacBook. We'd have to install mujoco150, which sadly does not work with OpenAI gym now. I did search for workaround but it seemed that there is no way to use gym.make('Humanoid-v1') on MacBooks with NVM disks. Please add this support and it will be greatly appreciated. |
+1 |
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+1, hope mujoco1.5 can be used on mac |
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This thread might be tracking more than one thing, but I want to add a specific point: The upgrade from
If you see an error about missing it, then you probably need to downgrade Hope this helps. |
This pull request should fix this. Please try it and let me know if you have any issues. |
@machinaut The error is still there, despite using previous mujoco-py version.
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@abhigenie92 In my pull request, the line that is throwing the error has been deleted. Are you sure that you are using the updated code?
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@lobachevzky Thx. I tested on recent Mac by running berkeleydeeprlcourse hw1 demo with mujoco 1.5. And it's working. |
thanks @lobachevzky ! |
Can anyone help me with the mujoco 1.5 fix ? where can I access it ? Otherwise, |
@rajeev595, you can access the 1.5 fix here. However, you should know that Tensorflow should work with python2 and mujoco 0.5.7 should work with python3. What are the errors that you have been encountering? |
@lobachevzky Your fix worked. Thanks for the fix and prompt response :) . I was confused with the python version requirements. Anyways it worked finally. |
Thanks! @lobachevzky I think the best way to make it work is to install modules we need in virtualenv, including TensorFlow, the modified gym and the mujoco 1.5. And that's my final solution. |
@InnerPeace-Wu - I'm trying to do the same thing at the moment and struggling. Please can you detail your install? |
@JamesOwers Hi, I just clone the pull request and install with official instructions. |
under the python 3.6.1 , when I "import mujoco_py" , it returns error "could not read activation key". |
CinderellaRobaker, do you have a mujoco key (see the mujoco website)? If so, I'd recommend creating a new issue and giving details on what your situation is since it sounds rather different from this thread. |
@vitchyr Yes, I have mujoco key by a student email and have solved the problem. Thank you very much. |
Why is this issue still open? Does gym work with mujuco 1.5? I'm trying to understand how much work it would take to use rllab with mujoco 1.5 (via gym). rllab only has official support for mujoco1.3.1 |
Gym now uses mujoco 1.5 #834 |
How did you solve it |
In order to use MuJoCo on a recent mac, you need to be using MuJoCo 1.5: openai/mujoco-py#36 Otherwise you get:
This is because MuJoCo before 1.5 doesn't support NVMe disks.
Gym depends on MuJoCo via mujoco-py, which just released support for MuJoCo 1.5.
It looks like maybe this is something you're already working on? Or would it be useful for me to look into fixing it?
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