feat: add SelVA TI Scheduler for sweep-based textual inversion experiments

- SelvaTiScheduler: runs a JSON-defined sweep of TI training experiments,
  loading the dataset once and reusing it across runs
- Collects per-experiment loss history, final/min loss, stability metric
  (loss_std_last_quarter), and duration — written to experiment_summary.json
  after each completed run so partial sweeps survive interruption
- Resume-aware: skips experiments already marked completed in an existing
  summary file
- Outputs smoothed loss comparison chart (same axes, one curve per experiment)
- SelvaTextualInversionTrainer._train_inner now returns a dict
  {embeddings_path, loss_history} so the scheduler can read results;
  train() extracts just the path for ComfyUI

JSON format: name, description, data_dir, output_root, base config,
experiments list with id + param overrides

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/__init__.py

@@ -16,6 +16,7 @@ _NODES = {
     "SelvaSpectralMatcher":  (".selva_audio_preprocessors", "SelvaSpectralMatcher",  "SelVA Spectral Matcher"),
     "SelvaTextualInversionTrainer": (".selva_textual_inversion_trainer", "SelvaTextualInversionTrainer", "SelVA Textual Inversion Trainer"),
     "SelvaTextualInversionLoader":  (".selva_textual_inversion_loader",  "SelvaTextualInversionLoader",  "SelVA Textual Inversion Loader"),
+    "SelvaTiScheduler":             (".selva_ti_scheduler",              "SelvaTiScheduler",              "SelVA TI Scheduler"),
 }
 
 for key, (module_path, class_name, display_name) in _NODES.items():