release candidate: 4000 steps, seeded teacher, keep audio

kaggle/notebook_final.py

@@ -0,0 +1,58 @@
+"""Kaggle notebook body: release-candidate run at the operating point.
+
+4000 steps was the best configuration; 8000 regressed. This run reproduces it
+with the teacher seeded, and this time keeps the audio so the result can be
+judged by ear rather than only by CER.
+
+Produces:
+  train/student4.pt        weights
+  train/dit4.onnx          412 MB fp32
+  train/dit4_int4.onnx     70 MB int4
+  train/eval_rows*.json    teacher / student / int4 on a07 + a08
+  train/eval_wavs/*.wav    teacher and student audio for the same cells
+
+Uses the cached trajectories, so no regeneration.
+"""
+import os
+import subprocess
+import sys
+
+from notebook_eval import BUNDLE, MODEL, ROOT, WEIGHTS, pull, stage_deps, stage_repo
+
+BUNDLE_REPO = "idefinity/webfm-eval"
+HOLDOUT = "a07"
+EVAL_VOICES = "a07,a08"
+TRAIN_STEPS = "4000"
+
+
+def run(tag: str, extra: dict, gpu: int = 0) -> int:
+    env = dict(os.environ, WORK_ROOT=str(ROOT), HOLDOUT=HOLDOUT, **extra)
+    env["CUDA_VISIBLE_DEVICES"] = str(gpu)
+    env["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
+    log = open(ROOT / f"final_{tag}.log", "w")
+    p = subprocess.Popen([sys.executable, str(BUNDLE / "kaggle/train_voices.py")],
+                         env=env, stdout=log, stderr=subprocess.STDOUT, cwd=str(ROOT))
+    rc = p.wait()
+    print(f"[{tag}] rc={rc}", flush=True)
+    if rc != 0:
+        print((ROOT / f"final_{tag}.log").read_text()[-2500:])
+    return rc
+
+
+def main() -> None:
+    stage_repo()
+    stage_deps()
+    pull(WEIGHTS, MODEL)
+    pull(BUNDLE_REPO, BUNDLE, repo_type="dataset")
+    if not (BUNDLE / "traj.zip").exists():
+        raise SystemExit("traj.zip missing")
+
+    if run("main", {"STAGE": "all", "TRAIN_STEPS": TRAIN_STEPS, "BATCH": "16",
+                    "EVAL_VOICES": EVAL_VOICES, "SAVE_WAVS": "1"}) != 0:
+        raise SystemExit("train/export/eval failed")
+
+    run("int4", {"STAGE": "eval_int4", "EVAL_VOICES": EVAL_VOICES})
+
+
+if __name__ == "__main__":
+    main()