ray.exceptions.RayActoError when running examples #20
Comments
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Just to confirm, does it work with |
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As mentioned in this issue: #19 there is an error if the installer is trying to checkout So following the recommendation from the other issue and merging the two issues: In the errors there it is mentioned: so maybe GLEW is the problem here? But I was using mujoco with GLEW before without any issues, I have in .bashrc file. |
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Can you also try |
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Same issue. Trials did not complete.
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"Trials did not complete" is a standard error that we get from Note that I have changed |
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Thank you for your time! Now I get: And the output is exactly the same either after |
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Looks like it's the GLEW/OpenGL error that people often encounter when
using mujoco-py. Have you also tried using the Docker instructions? I would
suggest giving them a shot (the GPU version of them) if you haven't
already.
…On Wed, Nov 20, 2019 at 11:12 PM Jędrzej Beniamin Orbik < ***@***.***> wrote:
Thank you for your time! Now I get:
softlearning run_example_debug examples.classifier_rl \
--n_goal_examples 10 \
--task=Image48SawyerDoorPullHookEnv-v0 \
--algorithm VICERAQ \
--n_epochs 300 \
--active_query_frequency 10
/home/jedrzej/anaconda3/envs/reward-learning-rl/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:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.
WARNING: Logging before flag parsing goes to stderr.
I1121 08:06:22.704531 140455096169920 acceleratesupport.py:13] OpenGL_accelerate module loaded
I1121 08:06:22.737692 140455096169920 arraydatatype.py:270] Using accelerated ArrayDatatype
I1121 08:06:22.997218 140455096169920 __init__.py:34] MuJoCo library version is: 200
Warning: robosuite package not found. Run `pip install robosuite` to use robosuite environments.
I1121 08:06:23.037145 140455096169920 __init__.py:333] Registering multiworld mujoco gym environments
I1121 08:06:24.895683 140455096169920 __init__.py:14] Registering goal example multiworld mujoco gym environments
2019-11-21 08:06:25,012 INFO tune.py:64 -- Did not find checkpoint file in /home/jedrzej/ray_results/multiworld/mujoco/Image48SawyerDoorPullHookEnv-v0/2019-11-21T08-06-24-2019-11-21T08-06-24.
2019-11-21 08:06:25,012 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: 6.3/16.8 GB
Using seed 2637
2019-11-21 08:06:25.021778: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-11-21 08:06:25.134831: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-11-21 08:06:25.135436: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x562d63b5a2f0 executing computations on platform CUDA. Devices:
2019-11-21 08:06:25.135452: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): GeForce GTX 1060 6GB, Compute Capability 6.1
2019-11-21 08:06:25.137166: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3998440000 Hz
2019-11-21 08:06:25.138465: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x562d65141e00 executing computations on platform Host. Devices:
2019-11-21 08:06:25.138482: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): <undefined>, <undefined>
2019-11-21 08:06:25.138656: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: GeForce GTX 1060 6GB major: 6 minor: 1 memoryClockRate(GHz): 1.759
pciBusID: 0000:01:00.0
totalMemory: 5.93GiB freeMemory: 5.32GiB
2019-11-21 08:06:25.138674: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
2019-11-21 08:06:25.139460: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-11-21 08:06:25.139470: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0
2019-11-21 08:06:25.139476: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003] 0: N
2019-11-21 08:06:25.139607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 5151 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1060 6GB, pci bus id: 0000:01:00.0, compute capability: 6.1)
F1121 08:06:26.303420 140455096169920 core.py:90] GLEW initalization error: Missing GL version
Fatal Python error: Aborted
Stack (most recent call first):
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 841 in emit
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/logging/__init__.py", line 863 in handle
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 891 in handle
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/logging/__init__.py", line 1514 in callHandlers
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 1055 in handle
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/logging/__init__.py", line 1442 in _log
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/logging/__init__.py", line 1372 in log
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 1038 in log
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 476 in log
File "/home/jedrzej/.local/lib/python3.6/site-packages/absl/logging/__init__.py", line 309 in fatal
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/dm_control/mujoco/wrapper/core.py", line 90 in _error_callback
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/multiworld/envs/mujoco/mujoco_env.py", line 152 in initialize_camera
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/multiworld/core/image_env.py", line 75 in __init__
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/multiworld/envs/mujoco/__init__.py", line 324 in create_image_48_sawyer_door_pull_hook_v0
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/gym/envs/registration.py", line 70 in make
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/gym/envs/registration.py", line 101 in make
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/gym/envs/registration.py", line 156 in make
File "/home/jedrzej/GitHub/reward-learning-rl/softlearning/environments/utils.py", line 48 in get_goal_example_environment_from_variant
File "/home/jedrzej/GitHub/reward-learning-rl/examples/classifier_rl/main.py", line 30 in _build
File "/home/jedrzej/GitHub/reward-learning-rl/examples/development/main.py", line 77 in _train
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/trainable.py", line 151 in train
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/actor.py", line 479 in _actor_method_call
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/actor.py", line 138 in _remote
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/actor.py", line 124 in remote
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 111 in _train
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 143 in _start_trial
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/ray_trial_executor.py", line 201 in start_trial
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/trial_runner.py", line 271 in step
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/ray/tune/tune.py", line 235 in run
File "/home/jedrzej/GitHub/reward-learning-rl/examples/instrument.py", line 228 in run_example_local
File "/home/jedrzej/GitHub/reward-learning-rl/examples/instrument.py", line 254 in run_example_debug
File "/home/jedrzej/GitHub/reward-learning-rl/softlearning/scripts/console_scripts.py", line 81 in run_example_debug_cmd
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/click/core.py", line 555 in invoke
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/click/core.py", line 956 in invoke
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/click/core.py", line 1137 in invoke
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/click/core.py", line 717 in main
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/lib/python3.6/site-packages/click/core.py", line 764 in __call__
File "/home/jedrzej/GitHub/reward-learning-rl/softlearning/scripts/console_scripts.py", line 202 in main
File "/home/jedrzej/anaconda3/envs/reward-learning-rl/bin/softlearning", line 11 in <module>
[1] 7269 abort (core dumped) softlearning run_example_debug examples.classifier_rl --n_goal_examples 10
And the output is exactly the same either after unset LD_PRELOAD or
without it.
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I tried to use docker (cpu version), but on Mac unfortunately it does not work, because of some issues with OpenGL (probably again Apple lagging behind with drivers)... But I was able to install and run the examples correctly after installing glfw: I didn't expect that it is necessary, because I never needed to have it installed when using mujoco-py before. |
I use the Docker to install, but I meet the same problem: |
I use anaconda version on Ubuntu 18.04.
I installed conda version with slightly changed requirements.txt:
instead of :
The when running the example program from README I get the following errors for every algorithm:
Any thoughts?
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