Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Docker Installation #6

Open
NasimShafiee opened this issue May 17, 2019 · 14 comments
Open

Docker Installation #6

NasimShafiee opened this issue May 17, 2019 · 14 comments

Comments

@NasimShafiee
Copy link

Hi,

The docker installation is not complete or the docker is not working. I would appreciate you put the complete installation here.

Thanks,
@avisingh599
Copy link
Owner

Could you tell me what steps you followed and what errors you ran into when attempting the docker installation? Do you have nvidia-docker and docker-compose installed and setup on your machine?

@NasimShafiee
Copy link
Author

NasimShafiee commented May 23, 2019 •
edited
Loading

I have both of them installed.
Here are the steps I followed to both install and run the docker:

nasimshafiee@riverlab-asi:~$ export MJKEY="$(cat ~/.mujoco/mjkey.txt)" && sudo docker-compose -f reward-learning-rl/docker/docker-compose.dev.cpu.yml up -d --force-recreate
Recreating softlearning-dev-cpu ... done

sudo docker container list
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
ba72506cc7d9 softlearning:latest-cpu "/usr/bin/tini -- /e…" About a minute ago Up About a minute 0.0.0.0:32773->5000/tcp, 0.0.0.0:32772->6006/tcp, 0.0.0.0:32771->8888/tcp softlearning-dev-cpu

nasimshafiee@riverlab-asi:$ sudo docker exec -it softlearning-dev-cpu bash
(softlearning) root@ba72506cc7d9:/softlearning#

(softlearning) root@ba72506cc7d9:~/softlearning# softlearning run_example_local examples.classifier_rl \

--n_goal_examples 10
--task=Image48SawyerDoorPullHookEnv-v0
--algorithm VICERAQ
--num-samples 5
--n_epochs 300
--active_query_frequency 10
bash: softlearning: command not found

@avisingh599
Copy link
Owner

Could you try pip install -e . and then try running the same command again?

@NasimShafiee
Copy link
Author

pip install -e .
Obtaining file:///root/softlearning
Installing collected packages: softlearning
Found existing installation: softlearning 0.0.1
Uninstalling softlearning-0.0.1:
Successfully uninstalled softlearning-0.0.1
Running setup.py develop for softlearning
Successfully installed softlearning
(softlearning) root@ba72506cc7d9:~/softlearning# softlearning run_example_local examples.classifier_rl --n_goal_examples 10 --task=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --num-samples 5 --n_epochs 300 --active_query_frequency 10
/opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
RequestsDependencyWarning)

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:

Traceback (most recent call last):
File "/opt/conda/envs/softlearning/bin/softlearning", line 11, in
load_entry_point('softlearning', 'console_scripts', 'softlearning')()
File "/root/softlearning/softlearning/scripts/console_scripts.py", line 202, in main
return cli()
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 764, in call
return self.main(*args, **kwargs)
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 717, in main
rv = self.invoke(ctx)
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 1137, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 956, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/click/core.py", line 555, in invoke
return callback(*args, **kwargs)
File "/root/softlearning/softlearning/scripts/console_scripts.py", line 71, in run_example_local_cmd
return run_example_local(example_module_name, example_argv)
File "/root/softlearning/examples/instrument.py", line 208, in run_example_local
example_args = example_module.get_parser().parse_args(example_argv)
File "/root/softlearning/examples/classifier_rl/init.py", line 26, in get_parser
from .utils import get_parser
File "/root/softlearning/examples/classifier_rl/utils.py", line 8, in
import softlearning.environments.utils as env_utils
File "/root/softlearning/softlearning/environments/utils.py", line 8, in
from .adapters.dm_control_adapter import DmControlAdapter
File "/root/softlearning/softlearning/environments/adapters/dm_control_adapter.py", line 6, in
from dm_control import suite
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/suite/init.py", line 28, in
from dm_control.suite import acrobot
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/suite/acrobot.py", line 24, in
from dm_control import mujoco
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/mujoco/init.py", line 18, in
from dm_control.mujoco.engine import action_spec
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/mujoco/engine.py", line 43, in
from dm_control import _render
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/_render/init.py", line 70, in
Renderer = import_func()
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/_render/init.py", line 35, in _import_egl
from dm_control._render.pyopengl.egl_renderer import EGLContext
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/_render/pyopengl/egl_renderer.py", line 43, in
from dm_control._render.pyopengl import egl_ext as EGL
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/dm_control/_render/pyopengl/egl_ext.py", line 33, in
from OpenGL import EGL
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/OpenGL/EGL/init.py", line 2, in
from OpenGL.raw.EGL._types import *
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/OpenGL/raw/EGL/_types.py", line 73, in
CALLBACK_TYPE = _p.PLATFORM.functionTypeFor( _p.PLATFORM.EGL )
AttributeError: 'GLXPlatform' object has no attribute 'EGL'

@avisingh599
Copy link
Owner

Interesting. Looks like dm_control is causing problems, but I don't see these on my end. @hartikainen any idea what might be going on?

@hartikainen
Copy link
Contributor

hartikainen commented May 24, 2019 •
edited
Loading

Unfortunately, I don't know exactly what's causing the dm_control import to fail. The latest softlearning has a fix that makes the dm_control and robosuite packages optional: https://github.com/rail-berkeley/softlearning/blob/1f6686d765052c874dcf28f8036acde742decd79/softlearning/environments/utils.py#L7.

@Mehrdad-Dorostian
Copy link

Hi,
I faced problem using Docker Installation. I will be appreciated if you can help me with that. Here is my log:

(softlearning) root@fdcf41e30e0c:~/softlearning# softlearning run_example_local examples.classifier_rl --n_goal_examples 10 --task=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --num-samples 5 --n_epochs 300 --active_query_frequency 10
/opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
RequestsDependencyWarning)

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:

WARNING: Logging before flag parsing goes to stderr.
I0524 16:18:57.085572 139928440866624 acceleratesupport.py:13] OpenGL_accelerate module loaded
I0524 16:18:57.091506 139928440866624 arraydatatype.py:270] Using accelerated ArrayDatatype
I0524 16:18:57.219949 139928440866624 init.py:34] MuJoCo library version is: 200
I0524 16:18:58.361702 139928440866624 init.py:333] Registering multiworld mujoco gym environments
I0524 16:18:58.415774 139928440866624 init.py:14] Registering goal example multiworld mujoco gym environments
2019-05-24 16:18:58,483 INFO node.py:469 -- Process STDOUT and STDERR is being redirected to /tmp/ray/session_2019-05-24_16-18-58_657/logs.
2019-05-24 16:18:58,592 INFO services.py:407 -- Waiting for redis server at 127.0.0.1:27938 to respond...
2019-05-24 16:18:58,717 INFO services.py:407 -- Waiting for redis server at 127.0.0.1:27410 to respond...
2019-05-24 16:18:58,720 INFO services.py:804 -- Starting Redis shard with 1.65 GB max memory.

======================================================================
View the dashboard at http://172.18.0.2:8080/?token=94f192e32354ed6911bacd705f2ed3d4f494466516bddbdb

2019-05-24 16:18:58,839 INFO node.py:483 -- Process STDOUT and STDERR is being redirected to /tmp/ray/session_2019-05-24_16-18-58_657/logs.
2019-05-24 16:18:58,839 WARNING services.py:1304 -- WARNING: The object store is using /tmp instead of /dev/shm because /dev/shm has only 67108864 bytes available. This may slow down performance! You may be able to free up space by deleting files in /dev/shm or terminating any running plasma_store_server processes. If you are inside a Docker container, you may need to pass an argument with the flag '--shm-size' to 'docker run'.
2019-05-24 16:18:58,839 INFO services.py:1427 -- Starting the Plasma object store with 2.48 GB memory using /tmp.
2019-05-24 16:18:58,996 INFO tune.py:64 -- Did not find checkpoint file in /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-24T16-18-58-2019-05-24T16-18-58.
2019-05-24 16:18:58,996 INFO tune.py:211 -- Starting a new experiment.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/8 CPUs, 0/0 GPUs
Memory usage on this node: 5.6/8.3 GB

== Status ==
Using FIFO scheduling algorithm.
Resources requested: 8/8 CPUs, 0/0 GPUs
Memory usage on this node: 5.6/8.3 GB
Result logdir: /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-24T16-18-58-2019-05-24T16-18-58
Number of trials: 5 ({'RUNNING': 1, 'PENDING': 4})
PENDING trials:

  • 5933374b-algorithm=VICERAQ-seed=9594: PENDING
  • 97f1498b-algorithm=VICERAQ-seed=6933: PENDING
  • af9f5ddb-algorithm=VICERAQ-seed=2833: PENDING
  • b4794683-algorithm=VICERAQ-seed=2191: PENDING
    RUNNING trials:
  • 79f20978-algorithm=VICERAQ-seed=3699: RUNNING

(pid=729) /opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
(pid=729) RequestsDependencyWarning)
(pid=729)
(pid=729) WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
(pid=729) For more information, please see:
(pid=729) * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
(pid=729) * https://github.com/tensorflow/addons
(pid=729) If you depend on functionality not listed there, please file an issue.
(pid=729)
(pid=729) 2019-05-24 16:19:02.423031: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
(pid=729) Using seed 3699
(pid=729) 2019-05-24 16:19:02.449192: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3392375000 Hz
(pid=729) 2019-05-24 16:19:02.449746: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x563b744be830 executing computations on platform Host. Devices:
(pid=729) 2019-05-24 16:19:02.449773: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,

(pid=729) ERROR: GLEW initalization error: Missing GL version
(pid=729)
(pid=729) Press Enter to exit ...
2019-05-24 16:37:11,180 ERROR worker.py:1672 -- A worker died or was killed while executing task 000000009edd923385c29d9598c6c72491af0aac.
2019-05-24 16:37:11,180 ERROR trial_runner.py:494 -- Error processing event.
Traceback (most recent call last):
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/ray/tune/trial_runner.py", line 443, in _process_trial
result = self.trial_executor.fetch_result(trial)
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 315, in fetch_result
result = ray.get(trial_future[0])
File "/opt/conda/envs/softlearning/lib/python3.6/site-packages/ray/worker.py", line 2193, in get
raise value
ray.exceptions.RayActorError: The actor died unexpectedly before finishing this task.
2019-05-24 16:37:11,181 INFO ray_trial_executor.py:179 -- Destroying actor for trial 79f20978-algorithm=VICERAQ-seed=3699. If your trainable is slow to initialize, consider setting reuse_actors=True to reduce actor creation overheads.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/8 CPUs, 0/0 GPUs
Memory usage on this node: 5.9/8.3 GB
Result logdir: /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-24T16-18-58-2019-05-24T16-18-58
Number of trials: 5 ({'ERROR': 1, 'PENDING': 4})
ERROR trials:

  • 79f20978-algorithm=VICERAQ-seed=3699: ERROR, 1 failures: /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-24T16-18-58-2019-05-24T16-18-58/79f20978-algorithm=VICERAQ-seed=3699_2019-05-24_16-18-593ri44dsa/error_2019-05-24_16-37-11.txt
    PENDING trials:
  • 5933374b-algorithm=VICERAQ-seed=9594: PENDING
  • 97f1498b-algorithm=VICERAQ-seed=6933: PENDING
  • af9f5ddb-algorithm=VICERAQ-seed=2833: PENDING
  • b4794683-algorithm=VICERAQ-seed=2191: PENDING

(pid=823) /opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
(pid=823) RequestsDependencyWarning)
(pid=823)
(pid=823) WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
(pid=823) For more information, please see:
(pid=823) * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
(pid=823) * https://github.com/tensorflow/addons
(pid=823) If you depend on functionality not listed there, please file an issue.
(pid=823)
(pid=823) 2019-05-24 16:37:14.102711: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
(pid=823) Using seed 9594
(pid=823) 2019-05-24 16:37:14.125247: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3392375000 Hz
(pid=823) 2019-05-24 16:37:14.125840: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x55dff0c2fa80 executing computations on platform Host. Devices:
(pid=823) 2019-05-24 16:37:14.125871: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,

@avisingh599
Copy link
Owner

@Mehrdad-Dorostian This error is a bit hard to interpret because of all the ray messages. Could you try running softlearning run_example_debug examples.classifier_rl --n_goal_examples 10 --task=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --n_epochs 300 --active_query_frequency 10 and post the output here?

@NasimShafiee
Copy link
Author

I have the same issue when I'm running run_example_debug command:

softlearning run_example_debug examples.classifier_rl --n_goal_examples 10 --task=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --n_epochs 300 --active_query_frequency 10

/opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
RequestsDependencyWarning)

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:

WARNING: Logging before flag parsing goes to stderr.
I0528 19:15:46.675933 139764420859712 acceleratesupport.py:13] OpenGL_accelerate module loaded
I0528 19:15:46.681612 139764420859712 arraydatatype.py:270] Using accelerated ArrayDatatype
I0528 19:15:46.935050 139764420859712 init.py:34] MuJoCo library version is: 200

I0528 19:15:48.273273 139764420859712 init.py:333] Registering multiworld mujoco gym environments
I0528 19:15:48.326326 139764420859712 init.py:14] Registering goal example multiworld mujoco gym environments
2019-05-28 19:15:48,394 INFO tune.py:64 -- Did not find checkpoint file in /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-28T19-15-48-2019-05-28T19-15-48.
2019-05-28 19:15:48,394 INFO tune.py:211 -- Starting a new experiment.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/8 CPUs, 0/1 GPUs
Memory usage on this node: 10.6/33.6 GB

Using seed 2866
2019-05-28 19:15:48.405032: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-05-28 19:15:48.428803: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz
2019-05-28 19:15:48.429511: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x5627fe6bb0c0 executing computations on platform Host. Devices:
2019-05-28 19:15:48.429537: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,
ERROR: GLEW initalization error: Missing GL version

Press Enter to exit

@Mehrdad-Dorostian
Copy link

Thanks for your response!
I ran "softlearning run_example_debug examples.classifier_rl --n_goal_examples 10 --task=Image48SawyerDoorPullHookEnv-v0 --algorithm VICERAQ --n_epochs 300 --active_query_frequency 10" and this is my log:

/opt/conda/envs/softlearning/lib/python3.6/site-packages/requests/init.py:91: RequestsDependencyWarning: urllib3 (1.25.1) or chardet (3.0.4) doesn't match a supported version!
RequestsDependencyWarning)

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:

WARNING: Logging before flag parsing goes to stderr.
I0528 17:41:52.373401 139931832047424 acceleratesupport.py:13] OpenGL_accelerate module loaded
I0528 17:41:52.378882 139931832047424 arraydatatype.py:270] Using accelerated ArrayDatatype
I0528 17:41:52.512549 139931832047424 init.py:34] MuJoCo library version is: 200
I0528 17:41:53.840228 139931832047424 init.py:333] Registering multiworld mujoco gym environments
I0528 17:41:53.892477 139931832047424 init.py:14] Registering goal example multiworld mujoco gym environments
2019-05-28 17:41:53,958 INFO tune.py:64 -- Did not find checkpoint file in /root/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-05-28T17-41-53-2019-05-28T17-41-53.
2019-05-28 17:41:53,958 INFO tune.py:211 -- Starting a new experiment.
== Status ==
Using FIFO scheduling algorithm.
Resources requested: 0/8 CPUs, 0/1 GPUs
Memory usage on this node: 10.4/33.6 GB

Using seed 4148
2019-05-28 17:41:53.969472: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-05-28 17:41:53.992703: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2904000000 Hz
2019-05-28 17:41:53.993372: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x55a06bd030c0 executing computations on platform Host. Devices:
2019-05-28 17:41:53.993388: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,
ERROR: GLEW initalization error: Missing GL version

Press Enter to exit ...

@avisingh599
Copy link
Owner

avisingh599 commented Jun 1, 2019 •
edited
Loading

@Mehrdad-Dorostian @NasimShafiee Could you tell me what GPU do you have on your system? What's the output of nvidia-smi when you run it from within the docker container?

@NasimShafiee
Copy link
Author

Fri Jun 7 18:08:52 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 415.27 Driver Version: 415.27 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 208... Off | 00000000:01:00.0 On | N/A |
| 45% 61C P2 117W / 260W | 707MiB / 10988MiB | 43% Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1224 G /usr/lib/xorg/Xorg 202MiB |
| 0 2780 G compiz 79MiB |
| 0 4555 C+G python3.6 373MiB |
| 0 4626 G ...uest-channel-token=14554047989433986600 47MiB |
+-----------------------------------------------------------------------------+

@NasimShafiee
Copy link
Author

NasimShafiee commented Jun 7, 2019 •
edited
Loading

I cannot access nvidia-smi inside softlearning-dev-cpu.
Also, I cannot create softlearning-dev-gpu image:

WARNING: The SOFTLEARNING_DEV_GPU_TAG variable is not set. Defaulting to a blank string.
ERROR: no such image: avi-softlearning:: invalid reference format

@fromWRF
Copy link

fromWRF commented May 5, 2020 •
edited
Loading

I have some problems in using docker installation.
pip subprocess error:
Running command git clone -q https://github.com/deepmind/dm_control.git /tmp/pip-req-build-f94_w0g4
Running command git checkout -q 0260f3effcfe2b0fdb25d9652dc27ba34b52d226
Running command git clone -q https://github.com/avisingh599/multiworld.git /tmp/pip-req-build-3wyolddc
Running command git checkout -q 19bf319422c0016260166bf64e194552bf2a9e68
Running command git clone -q https://github.com/hartikainen/mujoco-py.git /tmp/pip-req-build-5687gubb
Running command git checkout -q 29fcd26290c9417aef0f82d0628d29fa0dbf0fab
fatal: reference is not a tree: 29fcd26290c9417aef0f82d0628d29fa0dbf0fab
ERROR: Command errored out with exit status 128: git checkout -q 29fcd26290c9417aef0f82d0628d29fa0dbf0fab Check the logs for full command output.

CondaEnvException: Pip failed

ERROR: Service 'softlearning-dev-cpu' failed to build: The command '/bin/bash -c echo "${MJKEY}" > ~/.mujoco/mjkey.txt && conda env update -f /tmp/environment.yml && conda clean --all -y && rm ~/.mujoco/mjkey.txt' returned a non-zero code: 1

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
5 participants
@hartikainen @avisingh599 @fromWRF @NasimShafiee @Mehrdad-Dorostian