Advanced¶

Settings¶

Data and Configuration Path¶

By default pistarlab stores data and configuration in the $HOME/pistarlab/ directory. (eg: /home/$USER/pistarlab) This can be changed by using the PISTARLAB_ROOT environment variable

If you are using Docker, PISTARLAB_ROOT is under $HOME/pistarlab_docker/. This has been changed for Docker to avoid permission issues that Docker may instroduce.

Configuration is stored in the config.yaml file located at PISTARLAB_ROOT

Data is stored under PISTARLAB_ROOT/data

Debugging¶

Our current solution uses the remote_pdb python module to enable remote debuging over telnet.

To use debugging, do the following:

Insert the following code snip where you want the debugger to started and wait for your input

from ..utils.remote_pdb import set_trace
set_trace() # you'll see the port number in the logs

When the above code is executed, it will print the port number to connect to in the logs.
use telnet to connect and use pdb as usual: for example `telnet 127.0.0.1 PORTNUM_HERE`

Cluster Mode¶

Warning

Experimental

Cluster mode is handled by Ray. For more information visit ray.io.

WIP, this documentation is incomplete and more testing needed.

Requirements * PostgreSQL to communicate over network (Temporary) * Python Version should be same on all nodes

with Docker¶

Switch to python env to 3.7.7

This is needed because the docker version of Ray uses 3.7.7 and multiple versions of python create problems when pickling.

conda install python=3.7.7

Docker Related Issue with using Ray

file permission issues when using docker. files copied using rsync get permissions
/tmp/ray_tmp_mount

without Docker¶

Install MINICONDA
1. wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
2. bash ~/Miniconda3-latest-Linux-x86_64.sh
3. login logout
4. conda install python=3.7.7

** Configuration **

Config file path: ~/pistarlab/cluster.yaml

TODO, see for details

Startup¶

Starting cluster
```
ray up -vvvv ~/pistarlab/cluster.yaml
```

Launch piSTAR Lab on head node

python pistarlab/launcher.py --ray_address="IP_ADDRESS:6379"

Install plugins on nodes¶

ray exec $HOME/pistarlab/cluster.yaml  "pip install --user -e /home/pistarlabuser/app/pistarlab/plugins/pistarlab-envs-gym-main"

Sync Data with Nodes¶

Before each task run

ray rsync-up -vvv ~/pistarlab/cluster.yaml

After each task (or as needed)

ray rsync-down -vvv ~/pistarlab/cluster.yaml /home/pistarlabuser/pistarlab/data/ $HOME/pistarlab/data/