Files
coorl-lost-cities/AGENTS.md
T
coolguyandClaude Opus 4.7 04ef99e7ef Document wandb integration in AGENTS.md; require AGENTS.md read upfront
- AGENTS.md: add Weights & Biases section covering install (extra),
  online/offline modes, per-run wandb/ layout, sync command, and the
  source-of-truth note (metrics.jsonl, not W&B).
- CLAUDE.md: replace soft "before making changes" wording with a
  mandatory session-start instruction to read AGENTS.md in full.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-07 16:48:33 +09:00

319 lines
8.7 KiB
Markdown

# AGENTS.md
This repository is managed with `uv`. Use `uv run ...` for commands so the
project environment and Cython extensions are built/loaded consistently.
## Project Layout
- `src/coolrl_lost_cities/games/classic/game.pyx`: Cython Lost Cities engine.
- `src/coolrl_lost_cities/games/classic/deep_cfr/`: Deep CFR training,
traversal, evaluation, analysis, and CLI code.
- `configs/deep_cfr/`: Deep CFR YAML configs (kebab-case filenames).
- `runs/`: generated training runs. Gitignored, may be a symlink to larger
storage. Layout:
- `runs/archive/`: past runs. **Do not modify or delete.**
- `runs/tmp/`: smoke, tests, throwaway. Free to `rm -rf` anytime.
- `runs/<YYYY-MM-DD_HHMMSS>_<kebab-name>/`: real experiments (flat).
Promote a `runs/<...>` directory to `runs/archive/` with a manual `mv`
once analysis is complete.
- `docs/`: profiling notes, migration notes, and experiment documentation.
## Core Commands
Run lint:
```bash
uv run ruff check .
```
Run all tests:
```bash
uv run pytest -q
```
Run focused Deep CFR tests:
```bash
uv run pytest -q tests/games/classic/test_deep_cfr_trainer.py
```
Run the CLI through the console script:
```bash
uv run lost-cities-deep-cfr --help
```
Equivalent module form:
```bash
uv run python -m coolrl_lost_cities.games.classic.deep_cfr.cli --help
```
## Deep CFR Training
The CLI auto-derives the run directory from `run.experiment_name` plus a
timestamp. By default runs land under `runs/tmp/`; pass `--keep` for a real
experiment that should live under `runs/`.
Smoke / throwaway run (lands in `runs/tmp/`):
```bash
uv run lost-cities-deep-cfr train --config configs/deep_cfr/smoke.yaml
# → runs/tmp/<YYYY-MM-DD_HHMMSS>_smoke/
```
Real experiment (lands in `runs/`):
```bash
uv run lost-cities-deep-cfr train \
--config configs/deep_cfr/deep-cfr-selfplay-full-depth-slot-playability.yaml \
--keep
# → runs/<YYYY-MM-DD_HHMMSS>_lost-cities-deep-cfr-selfplay-full-depth-slot-playability/
```
Variant of the same config (override slug):
```bash
uv run lost-cities-deep-cfr train \
--config configs/deep_cfr/deep-cfr-color-shared-attention-512x3.yaml \
--keep \
--set run.experiment_name=color-attn-v2
# → runs/<YYYY-MM-DD_HHMMSS>_color-attn-v2/
```
Short fixed-iteration run:
```bash
uv run lost-cities-deep-cfr train \
--config configs/deep_cfr/deep-cfr-selfplay-full-depth-slot-playability.yaml \
--set run.max_iterations=100 \
--set run.max_minutes=null \
--set checkpoint.save_every=0
```
Resume (path required, no shortcut):
```bash
uv run lost-cities-deep-cfr train \
--config configs/deep_cfr/deep-cfr-selfplay-full-depth-slot-playability.yaml \
--resume runs/<YYYY-MM-DD_HHMMSS>_<slug>/latest.pt
```
When `--resume` is given, the trainer reuses the resumed checkpoint's parent
directory; no new timestamped folder is created.
Useful train controls:
- `--keep`: real experiment, write under `runs/` (default is `runs/tmp/`).
- `--resume PATH`: resume from a specific checkpoint. `PATH` is required.
- `--set PATH=VALUE`: override config fields. Repeatable, parses values as
YAML (e.g. `--set traversal.num_workers=4`, `--set run.max_minutes=null`).
Common `--set` overrides:
- `--set run.device=cuda`: set the trainer device.
- `--set run.experiment_name=foo-v2`: change the slug used in the run dir
name (kebab-case).
- `--set checkpoint.exact_resume=true`: require checkpoint config compatibility.
- `--set checkpoint.save_latest=false --set checkpoint.save_every=0`:
disable checkpoint writes.
- `--set checkpoint.save_every=0`: keep only `latest.pt` (no archives).
- `--set checkpoint.save_every=N`: archive every N iterations.
## Naming Conventions
- **Directory names, run dirs, config filenames, `experiment_name` values**:
kebab-case (`deep-cfr-color-shared-512x3.yaml`,
`runs/2026-05-08_103045_color-attn-v2/`).
- **YAML keys, Python identifiers, config field names**: snake_case
(unchanged: `hidden_size`, `traversals_per_player`, `experiment_name`).
- The CLI converts `run.experiment_name` to a kebab slug when building the
run directory, so values may contain spaces or mixed case.
## Long Runs
Run long jobs in a real `tmux` session so the user can attach and stop them.
Do not rely on Codex command sessions for long user-observable training runs.
Start a long unbounded run:
```bash
tmux new-session -s coolrl-deepcfr-unbounded \
-c /home/coolguy/dev/coolrl-lost-cities \
'uv run lost-cities-deep-cfr train \
--config configs/deep_cfr/deep-cfr-selfplay-full-depth-slot-playability-unbounded.yaml \
--keep'
```
Attach later:
```bash
tmux attach -t coolrl-deepcfr-unbounded
```
Detach without stopping:
```text
Ctrl+B, D
```
Stop training:
```text
Ctrl+C
```
Follow logs from another terminal:
```bash
tail -f runs/<YYYY-MM-DD_HHMMSS>_<slug>/train.log
```
The unbounded config intentionally has:
```yaml
run:
max_iterations: null
max_minutes: null
checkpoint:
save_every: 100
```
`latest.pt` is updated continuously; archive checkpoints are written every 100
iterations. If disk is tight, set `--set checkpoint.save_every=0` (keep only
`latest.pt`) or increase `save_every`.
## Evaluation And Analysis
Evaluate a checkpoint:
```bash
uv run lost-cities-deep-cfr eval \
--checkpoint runs/<run-dir>/latest.pt \
--opponent random \
--games 100 \
--device cpu
```
Save evaluation game records:
```bash
uv run lost-cities-deep-cfr eval \
--checkpoint runs/<run-dir>/latest.pt \
--opponent random \
--games 100 \
--device cpu \
--save-games runs/<run-dir>/eval_random_games.json
```
Generate analysis plots from `metrics.jsonl`:
```bash
uv run lost-cities-deep-cfr analyze \
--run runs/<run-dir>
```
Write plots to a separate directory:
```bash
uv run lost-cities-deep-cfr analyze \
--run runs/<run-dir> \
--output-dir runs/<run-dir>/analysis
```
The analyzer reads `metrics.jsonl` and writes PNG files grouped by diagnostic
section. Opponents are compared within each plot using fixed colors. The
`lost-cities-deep-cfr analyze` subcommand uses the analyzer default smoothing
window, currently 1 iteration (no smoothing), and supports `--max-iteration`.
For smoothing controls, run the analyzer module directly:
```bash
uv run python -m coolrl_lost_cities.games.classic.deep_cfr.analyze \
--run runs/<run-dir> \
--smoothing-window 5
```
Use `--no-smoothing` to force no moving average.
Current output files:
- `analysis_01_loss.png`
- `analysis_02_match.png`
- `analysis_03_action.png`
- `analysis_04_gameflow.png`
- `analysis_05_open_quality.png`
- `analysis_06_expedition_outcomes.png`
- `analysis_07_calibration.png`
- `analysis_08_traversal.png`
- `analysis_09_selectivity.png`
- `analysis_final_eval_summary.png`
## Runtime Artifacts
Each training run writes:
- `metrics.jsonl`: structured metrics, one completed iteration per line.
- `train.log`: human-readable timestamped logs.
- `runtime_progress.json`: latest progress snapshot.
- `latest.pt`: latest checkpoint.
- `iteration_*.pt`: archive checkpoints when enabled.
- `config.json`: resolved config for the run.
If a run is stopped mid-iteration, the in-progress iteration may not appear in
`metrics.jsonl`. Analyze the latest completed metric row.
## Weights & Biases (Optional)
Metrics can be mirrored to W&B. `wandb` is an optional extra; default
installs and runs do not require it.
Install:
```bash
uv sync --extra wandb
```
Run with W&B:
```bash
# Offline: no login, writes to <run_dir>/wandb/offline-run-*/
uv run lost-cities-deep-cfr train --config <...> --wandb --wandb-mode offline
# Online: requires `uv run wandb login` once, then real-time upload
uv run lost-cities-deep-cfr train --config <...> --wandb
```
W&B data is stored **per run** at `<run_dir>/wandb/`, not at a global
`runs/wandb/`. Each training run gets its own subfolder, so moving or
deleting a run directory carries its W&B data along with it.
Sync offline runs to wandb.ai later:
```bash
wandb sync runs/<run-dir>/wandb/offline-run-*
```
Flags:
- `--wandb`: enable W&B mirroring.
- `--wandb-project <name>`: defaults to `coolrl-lost-cities`.
- `--wandb-name <name>`: W&B run name; defaults to `run.experiment_name`.
- `--wandb-mode {online,offline,disabled}`: default `online`.
- `--wandb-tag <tag>`: tag the run; repeatable.
W&B is purely additive — `metrics.jsonl` remains the source of truth, and
`analyze` reads `metrics.jsonl`, not W&B. Disabling W&B never breaks
training, resume, or analysis.
## Notes For Future Agents
- Prefer `rg`/`rg --files` for search.
- Use `apply_patch` for manual edits.
- Do not commit generated run artifacts from `runs/`.
- Cython-generated `.c` files are gitignored; edit `.pyx`/`.pxd` sources.
- Before committing, run `uv run ruff check .` and at least the relevant pytest
subset. For Deep CFR changes, run
`uv run pytest -q tests/games/classic/test_deep_cfr_trainer.py`.