hartikainen
commented
4 years ago Just to confirm, does it work with git+https://github.com/hartikainen/mujoco-py.git@29fcd26290c9417aef0f82d0628d29fa0dbf0fab?
Closed Jendker closed 4 years ago
hartikainen
commented
4 years ago Just to confirm, does it work with git+https://github.com/hartikainen/mujoco-py.git@29fcd26290c9417aef0f82d0628d29fa0dbf0fab?
Jendker
commented
4 years ago As mentioned in this issue: https://github.com/avisingh599/reward-learning-rl/issues/19 there is an error if the installer is trying to checkout 29fcd26290c9417aef0f82d0628d29fa0dbf0fab. So I have to install newest mujoco-py from pip.
So following the recommendation from the other issue and merging the two issues:
after running pip install -U mujoco-py gym I still get the same errors.
In the errors there it is mentioned:
(pid=29180) F1120 22:20:14.298504 140157146002880 core.py:90] GLEW initalization error: Missing GL version
(pid=29180) Fatal Python error: Abortedso maybe GLEW is the problem here? But I was using mujoco with GLEW before without any issues, I have in .bashrc file.
export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libGLEW.so
avisingh599
commented
4 years ago Can you also try unset LD_PRELOAD and give it a shot, as pointed out by Vitchyr in this issue: https://github.com/openai/mujoco-py/issues/187
Jendker
commented
4 years ago Same issue. Trials did not complete.
avisingh599
commented
4 years ago "Trials did not complete" is a standard error that we get from ray when the program fails for any reason. To get slightly more informative error message, could you try any of the following commands:
softlearning run_example_debug examples.classifier_rl \
--n_goal_examples 10 \
--task=Image48SawyerDoorPullHookEnv-v0 \
--algorithm VICERAQ \
--n_epochs 300 \
--active_query_frequency 10Note that I have changed run_example_local with run_example_debug, and removed --num-samples.
Jendker
commented
4 years ago 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 10And the output is exactly the same either after unset LD_PRELOAD or without it.
avisingh599
commented
4 years ago 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 < notifications@github.com> 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 robosuiteto 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 GBUsing 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):
, 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
[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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Jendker
commented
4 years ago 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:
brew install glfwI didn't expect that it is necessary, because I never needed to have it installed when using mujoco-py before.
Besides I had to remove PyOpenGL-accelerate from requirements and it works fine now, problem solved.
fromWRF
commented
4 years ago 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 robosuiteto 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):, 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 [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. — You are receiving this because you commented. 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I use the Docker to install, but I meet the same problem: fatal: reference is not a tree: 29fcd26290c9417aef0f82d0628d29fa0dbf0fab
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?