CLI reference

Every subcommand of srn forwards to a Python module under swissrivernetwork.benchmark. Forwarding preserves __main__ semantics so the drivers can still be invoked via python -m if you prefer.

Command	Driver
srn prepare-data	swissrivernetwork.benchmark.data_preparation
srn tune -m <method> -g <graph> -n <n> -wl <wl> [-pe <pe>]	swissrivernetwork.benchmark.ray_tune
srn evaluate	swissrivernetwork.benchmark.ray_evaluation
srn sweep	swissrivernetwork.benchmark.run_win_len_sweep
srn train-single	swissrivernetwork.benchmark.train_single_model
srn train-isolated	swissrivernetwork.benchmark.train_isolated_station
srn app gradio	swissrivernetwork.app.gradio_app
srn app streamlit	Streamlit launches swissrivernetwork/app/streamlit_app.py
srn version	Print the installed package version

Driver-specific flags go after --:

uv run srn tune -- -m transformer_embedding -g swiss-2010 -n 200 -wl 90 -pe rope

Common flags

• -m / --method — one of lstm, lstm_embedding, graphlet, stgnn, transformer, transformer_graphlet, transformer_embedding, transformer_stgnn.
• -g / --graph — one of swiss-1990, swiss-2010, zurich.
• -n / --num-trials — Ray Tune trial count.
• -wl / --window-len — temporal window length (days).
• -pe / --positional-encoding — sinusoidal, learnable, rope.

See the .claude/skills/run-benchmark/SKILL.md playbook for the full reference including the environment variables that must stay set (notably RAY_CHDIR_TO_TRIAL_DIR=0).