"Routes BAPPS training, fine-tuning, checkpointing, and smoke-test
Scanned 9/8/2026
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---
name: bapps-training
description: "Routes BAPPS training, fine-tuning, checkpointing, and smoke-test
workflows for the PerceptualSimilarity package."
disable-model-invocation: true
metadata:
disco-role: operating
license: BSD 2-Clause
---
# BAPPS Training
Use this sub-skill when the task is about training or fine-tuning the LPIPS metric on BAPPS-style 2AFC data.
## Trigger phrases
- "train LPIPS"
- "fine-tune on BAPPS"
- "run the scratch variant"
- "run the tune variant"
- "smoke-test the training path"
- "save checkpoints"
## What this route covers
- LPIPS/BAPPS ranking-loss training.
- Checkpoint directory creation and file naming.
- Smoke-friendly one-step or one-epoch runs.
- Scratch and trunk-tuning modes.
- Training-specific troubleshooting.
## What this route excludes
- Direct image-pair comparison.
- Benchmark scoring only.
- Dataset-download automation.
If the task is only about scoring a split, route to `bapps-evaluation`. If the task is about direct LPIPS distances or LPIPS loss visualization, route to `metric-usage`.
## Read these next
- `references/workflows.md` for the training command matrix.
- `references/troubleshooting.md` for checkpoint, dependency, and runtime issues.
- `../../references/bapps-dataset.md` for the expected split layout.
- `../../references/api-reference.md` for the verified `Trainer` API.
## Run these helpers
- `scripts/train_bapps.py` for the bundled training loop.
- `scripts/train_test_metric.sh` for the standard train-then-score wrapper.
- `scripts/train_test_metric_scratch.sh` for the scratch variant.
- `scripts/train_test_metric_tune.sh` for the trunk-tune variant.
- `../../scripts/make_tiny_bapps_fixture.py` to create a tiny BAPPS-style smoke fixture.
## Working assumptions
- Training uses 2AFC splits with `ref/`, `p0/`, `p1/`, and `judge/`.
- The bundled helper creates the checkpoint directory automatically.
- The bundled helper avoids the old HTML/visdom stack used by the stock `train.py`.
- The smoke default is intentionally bounded so it is safe to run on small fixtures.
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