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>
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@ -1048,7 +1048,7 @@ The Rust sensing server binary accepts the following flags:
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| `--dataset` | (none) | Path to dataset directory (MM-Fi or Wi-Pose) |
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| `--dataset-type` | `mmfi` | Dataset format: `mmfi` or `wipose` |
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| `--epochs` | `100` | Training epochs |
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| `--export-rvf` | (none) | Export RVF model container and exit |
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| `--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. |
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| `--save-rvf` | (none) | Save model state to RVF on shutdown |
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| `--model` | (none) | Load a trained `.rvf` model for inference |
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| `--load-rvf` | (none) | Load model config from RVF container |
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@ -1359,7 +1359,7 @@ docker run --rm \
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-v $(pwd)/output:/output \
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--entrypoint /app/sensing-server \
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ruvnet/wifi-densepose:latest \
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--train --dataset /data --epochs 100 --export-rvf /output/model.rvf
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--train --dataset /data --epochs 100 --save-rvf /output/model.rvf
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```
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The pipeline runs 10 phases:
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@ -5619,6 +5619,16 @@ fn diagnose_model_load_error(path: &std::path::Path, data: &[u8], err: &str) ->
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)
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}
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/// Whether `--export-rvf` should emit the placeholder container-format demo.
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///
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/// It must only do so **standalone**. Combined with `--train`/`--pretrain` the
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/// real model is produced by the training pipeline, so short-circuiting here
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/// would silently skip training and write placeholder weights — the #894 bug
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/// where the documented `--train … --export-rvf` workflow produced a fake model.
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fn export_emits_placeholder_demo(export_set: bool, train: bool, pretrain: bool) -> bool {
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export_set && !train && !pretrain
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}
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// ── Main ─────────────────────────────────────────────────────────────────────
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/// If `--ui-path` points nowhere (wrong cwd), try common repo layouts relative to cwd.
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@ -5662,9 +5672,24 @@ async fn main() {
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return;
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}
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// Handle --export-rvf mode: build an RVF container package and exit
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if let Some(ref rvf_path) = args.export_rvf {
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eprintln!("Exporting RVF container package...");
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// Handle --export-rvf: writes a CONTAINER-FORMAT DEMO with placeholder
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// weights — it is NOT a trained model. Only short-circuit when standalone:
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// combined with --train/--pretrain the real model is exported by the
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// training pipeline, and short-circuiting here would silently skip training
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// and write placeholder weights (#894 — the documented `--train …
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// --export-rvf` workflow produced a placeholder and never trained).
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if export_emits_placeholder_demo(args.export_rvf.is_some(), args.train, args.pretrain) {
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let rvf_path = args
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.export_rvf
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.as_ref()
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.expect("export_emits_placeholder_demo implies export_rvf is set");
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eprintln!(
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"WARNING: --export-rvf writes a CONTAINER-FORMAT DEMO with placeholder \
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weights — it is NOT a trained model. Train one with \
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`--train --dataset <DIR>` (which exports a calibrated .rvf to the \
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models/ directory), or download a pretrained encoder. See issue #894."
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);
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eprintln!("Exporting RVF container package (placeholder weights)...");
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use rvf_pipeline::RvfModelBuilder;
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let mut builder = RvfModelBuilder::new("wifi-densepose", "1.0.0");
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@ -5713,6 +5738,13 @@ async fn main() {
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}
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}
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return;
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} else if args.export_rvf.is_some() {
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// --export-rvf alongside --train/--pretrain: don't emit a placeholder.
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// Fall through so training runs; it exports the real calibrated model.
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eprintln!(
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"Note: --export-rvf is ignored in training mode — the trained model \
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is exported by the training pipeline to the models/ directory."
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);
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}
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// Handle --pretrain mode: self-supervised contrastive pretraining (ADR-024)
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@ -7310,3 +7342,29 @@ mod model_load_diagnostic_tests {
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assert!(msg.contains("wifi-densepose-train"), "{msg}");
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}
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}
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#[cfg(test)]
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mod export_rvf_mode_tests {
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use super::export_emits_placeholder_demo;
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#[test]
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fn standalone_export_emits_placeholder() {
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// --export-rvf alone → the container-format demo (placeholder weights).
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assert!(export_emits_placeholder_demo(true, false, false));
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}
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#[test]
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fn export_with_train_does_not_short_circuit() {
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// #894: `--train --export-rvf` must NOT emit a placeholder + skip
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// training — it must fall through to the real training pipeline.
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assert!(!export_emits_placeholder_demo(true, true, false));
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assert!(!export_emits_placeholder_demo(true, false, true));
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assert!(!export_emits_placeholder_demo(true, true, true));
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}
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#[test]
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fn no_export_flag_never_emits() {
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assert!(!export_emits_placeholder_demo(false, false, false));
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assert!(!export_emits_placeholder_demo(false, true, false));
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}
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}
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