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Permission denied when running bin/setup
bin/setup
This means you don't have sufficient privilege on your machine. Run it with sudo:
conda activate lab
fails
conda activate lab
failsWhen Conda complains about certain variables should not be in your PATH
:
CommandNotFoundError: Your shell has not been properly configured to use 'conda activate'. If your shell is Bash or a Bourne variant, enable conda for the current user with
$ echo ". /home/ubuntu/miniconda3/etc/profile.d/conda.sh" >> ~/.bashrc
or, for all users, enable conda with
$ sudo ln -s /home/ubuntu/miniconda3/etc/profile.d/conda.sh /etc/profile.d/conda.sh
The options above will permanently enable the 'conda' command, but they do NOT put conda's base (root) environment on PATH. To do so, run
$ conda activate
in your terminal, or to put the base environment on PATH permanently, run
$ echo "conda activate" >> ~/.bashrc
Previous to conda 4.4, the recommended way to activate conda was to modify PATH in your ~/.bashrc file. You should manually remove the line that looks like
export PATH="/home/ubuntu/miniconda3/bin:$PATH"
^^^ The above line should NO LONGER be in your ~/.bashrc file! ^^^
To fix it, do the first thing it recommends and refresh your terminal session:
Google Colab / Jupyter setup
For users of Google Colab or Jupyter, simply use the Conda environment lab
as the kernel setup by SLM Lab installation. SLM Lab setup installs Conda into the home directory ~/miniconda3
. Note that in each notebook cell a bash command is a entirely new session. We have to expose the lab
Conda environment directly and run the Python command. Furthermore, note that notebooks have no GUI thus have to be run headless. The following is an example for running the quickstart:
GLIBCXX_3.4.21
version errors due to gcc, g++, libstdc++
GLIBCXX_3.4.21
version errors due to gcc, g++, libstdc++
You encounter libgcc errors like:
ImportError: /home/deploy/miniconda3/envs/lab/lib/python3.6/site-packages/torch/../../.././libstdc++.so.6: version `GLIBCXX_3.4.21' not found (required by /home/deploy/miniconda3/envs/lab/lib/python3.6/site-packages/ray/pyarrow_files/pyarrow/lib.cpython-36m-x86_64-linux-gnu.so)
Try installing libgcc in Conda:
NVIDIA GPU driver problem
If you receive errors similar to the following when trying to use GPU:
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver
Building and setting up a Linux GPU server
Breakage from SLM-Lab update
Make sure you also install the packages after updating the repo. Run:
JSON parsing issue in spec
Newer dependencies of SLM Lab may cause issues when parsing JSON spec files. SLM Lab uses a looser JSON syntax which includes comma in the last element of enumerable. If you encounter a JSON parsing issue, simply edit the spec file to remove these extraneous commas.
Vizdoom installation fails or not found
Manually install it:
How to kill stuck processes?
No GUI or images saved on a headless remote server
When running SLM Lab on a remote server, you may get NoSuchDisplayException: Cannot connect to "None"
. Or your graphs may not be generated. This is because servers are typically headless, i.e. without a display. This error occurs when you're trying to render without a headless display.
First, try setting environment variable RENDER=false
before the lab command, for example:
Despite its simplicity, this option comes with the caveat that plots from Plotly cannot generated. The safer option is to install Xvfb, and prepend your command with xvfb-run -a
. For example:
How to forward GUI from a remote server?
If you are running via ssh
and want GUI forwarding from a server, do:
do
ssh
with a-X
flag, e.g.ssh -X foo@bar
.
How to sync data from a remote server?
What is SLM?
Reporting Issues
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