The --export-rvf handler ran *before* the --train/--pretrain handlers and
unconditionally wrote placeholder sine-wave weights, then returned. So the
documented `--train --dataset … --export-rvf <path>` workflow
(user-guide.md) short-circuited to a PLACEHOLDER model and never trained —
printing "exported successfully" for a non-functional model. Given the
project's anti-"is it fake" stance, silently emitting a fake model is the
wrong default.
Fix:
- Only emit the placeholder container-format demo when --export-rvf is used
*standalone* (new `export_emits_placeholder_demo` guard). With
--train/--pretrain, fall through so the real training pipeline runs and
exports calibrated weights.
- The standalone path now prints a clear WARNING that it writes a
container-format demo with placeholder weights — not a trained model —
pointing to --train / a pretrained encoder (#894).
- Docs: flag --export-rvf as a placeholder demo in the flag table, and fix
the Docker training example to use --save-rvf (consistent with the
from-source example) instead of the placeholder --export-rvf.
3 unit tests for the guard. Full crate unit suite: 429 + 117 passed, 0 failed.
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