Dockerfile does not support mujoco rendering
vib2810 opened this issue · 1 comments
vib2810 commented
The docker image that is provided (kchua/handful-of-trials) can run the mbexp.py script, but cannot run the render.py script. The error is as follows:
-> python scripts/render.py -env cartpole -logdir log/ -model-dir log/2021-11-06--06\:49\:30/
2022-04-21 09:37:34.268473: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2022-04-21 09:37:34.346063: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:897] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-04-21 09:37:34.346510: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1392] Found device 0 with properties:
name: NVIDIA GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
totalMemory: 3.95GiB freeMemory: 3.63GiB
2022-04-21 09:37:34.346552: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1471] Adding visible gpu devices: 0
2022-04-21 09:37:34.538159: I tensorflow/core/common_runtime/gpu/gpu_device.cc:952] Device interconnect StreamExecutor with strength 1 edge matrix:
2022-04-21 09:37:34.538212: I tensorflow/core/common_runtime/gpu/gpu_device.cc:958] 0
2022-04-21 09:37:34.538222: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: N
2022-04-21 09:37:34.538359: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1084] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3359 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
{'ctrl_cfg': {'env': <dmbrl.env.cartpole.CartpoleEnv object at 0x7fb8eb83fd68>,
'opt_cfg': {'ac_cost_fn': <function CartpoleConfigModule.ac_cost_fn at 0x7fb8eb8438c8>,
'cfg': {'alpha': 0.1,
'max_iters': 5,
'num_elites': 40,
'popsize': 400},
'mode': 'CEM',
'obs_cost_fn': <function CartpoleConfigModule.obs_cost_fn at 0x7fb8eb843840>,
'plan_hor': 25},
'prop_cfg': {'mode': 'TSinf',
'model_init_cfg': {'load_model': True,
'model_class': <class 'dmbrl.modeling.models.BNN.BNN'>,
'model_constructor': <bound method CartpoleConfigModule.nn_constructor of <cartpole.CartpoleConfigModule object at 0x7fb8eb83f9e8>>,
'model_dir': 'log/2021-11-06--06:49:30/',
'num_nets': 5},
'model_pretrained': True,
'model_train_cfg': {'epochs': 5},
'npart': 20,
'obs_postproc': <function CartpoleConfigModule.obs_postproc at 0x7fb8eb843730>,
'obs_preproc': <function CartpoleConfigModule.obs_preproc at 0x7fb8eb8436a8>,
'targ_proc': <function CartpoleConfigModule.targ_proc at 0x7fb8eb8437b8>}},
'exp_cfg': {'exp_cfg': {'ninit_rollouts': 0,
'nrollouts_per_iter': 1,
'ntrain_iters': 1},
'log_cfg': {'logdir': 'log/', 'nrecord': 1},
'sim_cfg': {'env': <dmbrl.env.cartpole.CartpoleEnv object at 0x7fb8eb83fd68>,
'task_hor': 200}}}
Model loaded from log/2021-11-06--06:49:30/.
Created an ensemble of 5 neural networks with variance predictions.
Created an MPC controller, prop mode TSinf, 20 particles.
Trajectory prediction logging is disabled.
####################################################################
Starting training iteration 1.
ERROR:mujoco_py.mjviewer:GLFW error: 65543, desc: b'GLX: Failed to create context: BadValue (integer parameter out of range for operation)'
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
Average action selection time: 1.2227837240695953
Rollout length: 200
Rewards obtained: [179.53440146325102]
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
ERROR:mujoco_py.mjviewer:GLFW error: 65537, desc: b'The GLFW library is not initialized'
Exception ignored in: <bound method Env.__del__ of <dmbrl.env.cartpole.CartpoleEnv object at 0x7fb8eb83fd68>>
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/gym/core.py", line 203, in __del__
self.close()
File "/usr/local/lib/python3.5/dist-packages/gym/core.py", line 164, in close
self.render(close=True)
File "/usr/local/lib/python3.5/dist-packages/gym/core.py", line 150, in render
return self._render(mode=mode, close=close)
File "/usr/local/lib/python3.5/dist-packages/gym/envs/mujoco/mujoco_env.py", line 105, in _render
self._get_viewer().finish()
File "/usr/local/lib/python3.5/dist-packages/mujoco_py/mjviewer.py", line 325, in finish
glfw.destroy_window(self.window)
File "/usr/local/lib/python3.5/dist-packages/mujoco_py/glfw.py", line 809, in destroy_window
window_addr = ctypes.cast(ctypes.pointer(window),
TypeError: _type_ must have storage info
vib2810 commented
Also, the docker file in the repository will not work, as different versions of packages will be installed by pip. I have added versions to each package in the docker file as follows:
FROM nvidia/cuda:9.0-cudnn7-runtime-ubuntu16.04
RUN rm /bin/sh && ln -s /bin/bash /bin/sh
# Install pip
RUN apt-get update
RUN apt-get -y install python3 python3-pip python3-dev python3-tk
RUN apt-get -y install libglu1-mesa libxi-dev libxmu-dev libglu1-mesa-dev
# Install basic libraries
RUN pip3 install --upgrade pip==10.0.1
RUN pip3 install grpcio==1.13.0 numpy==1.14.5 matplotlib==2.2.2 scipy==1.1.0 scikit-learn==0.19.2 future==0.16.0
RUN pip3 install tensorflow-gpu==1.9
# Install MuJoCo + OpenAI gym
RUN pip3 install gym==0.9.4
RUN apt-get update
RUN apt-get -y install unzip unetbootin wget
RUN mkdir -p /.mujoco && cd /.mujoco && wget https://www.roboti.us/download/mjpro131_linux.zip && unzip mjpro131_linux.zip
ENV MUJOCO_PY_MJKEY_PATH="/root/.mujoco/mjkey.txt"
ENV MUJOCO_PY_MJPRO_PATH="/root/.mujoco/mjpro131"
RUN pip3 install mujoco-py==0.5.7
# Install additional requirements
RUN pip3 install datetime==4.2 gitpython==2.1.11 h5py==2.8.0 tqdm==4.24.0 dotmap===1.2.20 cython==0.28.5
# GPFlow (Install using pip3)
RUN pip3 install gpflow==1.2.0
RUN apt-get -y install git
# RUN git clone https://github.com/GPflow/GPflow.git
RUN pip3 install pandas multipledispatch==0.6.0 pytest==3.7.1
# RUN cd GPflow/ && pip install . --no-deps
# Create copy of Deep MBRL repo and place in ~/handful-of-trials
RUN cd ~ && git clone https://github.com/kchua/handful-of-trials.git
#Some extra files to resolve errors with render.py
RUN apt-get install libxrandr2:amd64 libxinerama1:amd64 libxcursor1:amd64
RUN apt-get install -y libglfw3-dev libepoxy-dev libjsoncpp-dev libgtk-3-dev libx11-dev
RUN apt-get -y install eog ffmpeg
RUN apt-get install -y mesa-utils libgl1-mesa-glx
ENV LIBGL_ALWAYS_INDIRECT=1
# Environment setup
RUN echo 'LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/x86_64-linux-gnu' >> /root/.bashrc
RUN echo 'alias python=python3' >> /root/.bashrc
CMD /bin/bash