fix: --export-rvf no longer silently produces a placeholder model

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.

Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv 2026-06-02 20:21:01 +02:00
parent f5d0e1e69e
commit b2c115ec50
2 changed files with 63 additions and 5 deletions

View File

@ -1048,7 +1048,7 @@ The Rust sensing server binary accepts the following flags:
| `--dataset` | (none) | Path to dataset directory (MM-Fi or Wi-Pose) |
| `--dataset-type` | `mmfi` | Dataset format: `mmfi` or `wipose` |
| `--epochs` | `100` | Training epochs |
| `--export-rvf` | (none) | Export RVF model container and exit |
| `--export-rvf` | (none) | Export a **placeholder** RVF container-format demo and exit — **not a trained model**. For a real model use `--train` (+ `--save-rvf`) or download a pretrained encoder. |
| `--save-rvf` | (none) | Save model state to RVF on shutdown |
| `--model` | (none) | Load a trained `.rvf` model for inference |
| `--load-rvf` | (none) | Load model config from RVF container |
@ -1359,7 +1359,7 @@ docker run --rm \
-v $(pwd)/output:/output \
--entrypoint /app/sensing-server \
ruvnet/wifi-densepose:latest \
--train --dataset /data --epochs 100 --export-rvf /output/model.rvf
--train --dataset /data --epochs 100 --save-rvf /output/model.rvf
```
The pipeline runs 10 phases:

View File

@ -5619,6 +5619,16 @@ fn diagnose_model_load_error(path: &std::path::Path, data: &[u8], err: &str) ->
)
}
/// Whether `--export-rvf` should emit the placeholder container-format demo.
///
/// It must only do so **standalone**. Combined with `--train`/`--pretrain` the
/// real model is produced by the training pipeline, so short-circuiting here
/// would silently skip training and write placeholder weights — the #894 bug
/// where the documented `--train … --export-rvf` workflow produced a fake model.
fn export_emits_placeholder_demo(export_set: bool, train: bool, pretrain: bool) -> bool {
export_set && !train && !pretrain
}
// ── Main ─────────────────────────────────────────────────────────────────────
/// If `--ui-path` points nowhere (wrong cwd), try common repo layouts relative to cwd.
@ -5662,9 +5672,24 @@ async fn main() {
return;
}
// Handle --export-rvf mode: build an RVF container package and exit
if let Some(ref rvf_path) = args.export_rvf {
eprintln!("Exporting RVF container package...");
// Handle --export-rvf: writes a CONTAINER-FORMAT DEMO with placeholder
// weights — it is NOT a trained model. Only short-circuit when standalone:
// combined with --train/--pretrain the real model is exported by the
// training pipeline, and short-circuiting here would silently skip training
// and write placeholder weights (#894 — the documented `--train …
// --export-rvf` workflow produced a placeholder and never trained).
if export_emits_placeholder_demo(args.export_rvf.is_some(), args.train, args.pretrain) {
let rvf_path = args
.export_rvf
.as_ref()
.expect("export_emits_placeholder_demo implies export_rvf is set");
eprintln!(
"WARNING: --export-rvf writes a CONTAINER-FORMAT DEMO with placeholder \
weights it is NOT a trained model. Train one with \
`--train --dataset <DIR>` (which exports a calibrated .rvf to the \
models/ directory), or download a pretrained encoder. See issue #894."
);
eprintln!("Exporting RVF container package (placeholder weights)...");
use rvf_pipeline::RvfModelBuilder;
let mut builder = RvfModelBuilder::new("wifi-densepose", "1.0.0");
@ -5713,6 +5738,13 @@ async fn main() {
}
}
return;
} else if args.export_rvf.is_some() {
// --export-rvf alongside --train/--pretrain: don't emit a placeholder.
// Fall through so training runs; it exports the real calibrated model.
eprintln!(
"Note: --export-rvf is ignored in training mode — the trained model \
is exported by the training pipeline to the models/ directory."
);
}
// Handle --pretrain mode: self-supervised contrastive pretraining (ADR-024)
@ -7310,3 +7342,29 @@ mod model_load_diagnostic_tests {
assert!(msg.contains("wifi-densepose-train"), "{msg}");
}
}
#[cfg(test)]
mod export_rvf_mode_tests {
use super::export_emits_placeholder_demo;
#[test]
fn standalone_export_emits_placeholder() {
// --export-rvf alone → the container-format demo (placeholder weights).
assert!(export_emits_placeholder_demo(true, false, false));
}
#[test]
fn export_with_train_does_not_short_circuit() {
// #894: `--train --export-rvf` must NOT emit a placeholder + skip
// training — it must fall through to the real training pipeline.
assert!(!export_emits_placeholder_demo(true, true, false));
assert!(!export_emits_placeholder_demo(true, false, true));
assert!(!export_emits_placeholder_demo(true, true, true));
}
#[test]
fn no_export_flag_never_emits() {
assert!(!export_emits_placeholder_demo(false, false, false));
assert!(!export_emits_placeholder_demo(false, true, false));
}
}