1.3 KiB
1.3 KiB
Brittle Star
Quick Start
Installation
To set up the UV module, you can run the following command:
uv sync --frozen
Configuration
-
Copy the default configuration:
cp configs/default_ppo.yaml configs/my_experiment.yaml -
Edit
configs/my_experiment.yamlto set your WandB credentials:track: true # Enable WandB logging wandb_entity: "your-wandb-username" # Replace with your username/team wandb_project_name: "PPO-Modularity" -
(Optional) Login to WandB:
uv run wandb login
Training
example command:
uv run python src/train.py
Or use a custom config file:
uv run python src/train.py --config configs/my_experiment.yaml
Override specific parameters:
uv run python src/train.py --learning-rate 0.001 --num-envs 32 --track
Logging
The training script uses a unified logging framework that:
- Logs to WandB (when enabled)
- Saves metrics to local disk (JSON files in
runs/) - Displays progress in stdout
All experiment data is preserved locally, even if WandB is unavailable.
HPC
See docs/HPC.md for the full guide, including environment setup, cluster selection, interactive debugging, and job submission.