Description

TODO

Running

Make sure that conda is installed on your server, and that it's present in $PATH. You may want to install it by yourself, or ask whether conda is already installed somewhere and just add it to $PATH.
If effbench_env is not visible in conda, e.g it's a fresh conda installation, create this environment: bash create_env.sh
Optionally create a W&B account and add the following content to your ~/.bashrc: export WANDB_API_KEY="<YOUR_KEY>"
Copy the user_example.env file and fill in the paths: cp user_example.env user.env vi user.env
Edit the submitit/slurm run script to run the experiments you need: vi scripts/your_run_script_name.py
Run the experiment using that script with slurm: bash run.sh your_run_script_name

A few things to keep in mind:

The code generates a unique run name based on the command line arguments passed to the script. When adding new CLI argument that should not affect the run name you have to update the generate_run_name() function appropriately.
The weights are saved every N minutes.
The training will continue from the last checkpoint if the run with the generated name is present.
Use the use_wandb flag to log and save/load models to W&B.
Remember that changing the code will not change the generated experiment name.