README.md

catalyst_example

an example of the training file supporting distributed training and curriculum learning with Catalyst

Installation

1. Create and populate the environment

MYNEWENV="" # write a name of your environment in quotes, like "torch"
conda create --name ${MYNEWENV} python=3.9
conda activate ${MYNEWENV}
pip install -r requirements.txt

2. Training Setup
   1. The main training script is curriculum_training.py
   2. Mainly make sure that get_model method of the CustomRunner class initializes your model
   3. Create or modify the config file (e.g. conf/vanilla_3class_gn_11chan32.16.1_exp01.yaml) as follows:
      • Set wandb.team to your team name for proper logging

How to run the code on Slurm

1. Configure submit-job.sh by changing the following:

   # Required changes:
   #SBATCH --job-name # Set meaningful job name
   #SBATCH --mail-user=your.email@domain.com
   #SBATCH -p your_partition
   #SBATCH -A your_account
   MYNEWENV=""        # Set to your conda environment name
   CONFIG_NAME="your_config"
   CONFIG_PATH="path/to/config"

2. Submit the job:

sbatch submit-job.sh

Troubleshooting

1. Wandb Connection Issues

   • Create a wandb account and obtain an API token
   • Run wandb login with your token
   • Update wandb.team and wandb.project in your config file

2. MongoDB Connection

   • Development node: Uses "10.245.12.58"
   • Slurm nodes: Uses "arctrdcn018.rs.gsu.edu"
   • Connection is automatically handled based on SLURM_JOB_ID environment variable but you can also switch things up under the mongo section of the config file when you run into issues.