# ========================================== # PROBE ROOT - can the root be heard in a 0.77 s window at all? # ========================================== # The model memorises quality on the training set (98%) but not the root (83%). # When a model with full capacity cannot memorise a label, the same audio must be # carrying different root labels - i.e. the label is partly not derivable from the # signal, whatever the architecture. # # This computes a CEILING for the root head from the ANNOTATIONS ALONE (no audio, # no model, no training - seconds of CPU): # # 1. How often the labelled root actually sounds in the window (note_midi). # That is the upper bound for any model that listens rather than guesses. # 2. How often the root is the lowest sounding note (bass). # 3. Whether the INTENDED and PLAYED annotations agree on the root. # 4. How the ceiling changes with a longer window (48 / 96 / 144 frames). # # Reading: # ceiling ~= 100% -> the root is audible; the model is at fault # ceiling ~= 85% -> the model already extracts nearly everything audible # ceiling grows with the window -> widen CTX_FRAMES # ceiling flat -> the root is simply not played; it would have to come # from context rather than from the window # # KAGGLE: put it next to model_trainer.py (or let it download), paste, main(). # ========================================== import glob import os import sys from collections import Counter, defaultdict TRAINER_URL = "https://raw.githubusercontent.com/greblus/solitito/v2/dist/model_trainer.py" # Window sizes to measure. 48 frames = 0.768 s = the current CTX_FRAMES. WINDOW_SIZES = [48, 96, 144] STRIDE = 16 # frames between successive windows when scanning def _locate_trainer(): """Locates model_trainer.py (locally or from the repo) and adds it to sys.path.""" for pat in ("model_trainer.py", "/kaggle/working/model_trainer.py", "/kaggle/input/*/model_trainer.py", "/kaggle/input/*/*/model_trainer.py", "./dist/model_trainer.py", "../model_trainer.py"): for hit in glob.glob(pat): d = os.path.dirname(os.path.abspath(hit)) if d not in sys.path: sys.path.insert(0, d) print(f"📎 model_trainer.py: {hit}") return True print("📥 Not found locally - downloading from the repo...") try: import urllib.request dst = os.path.join(os.getcwd(), "model_trainer.py") with urllib.request.urlopen(TRAINER_URL, timeout=30) as r: body = r.read() if len(body) < 10000: print(" ⚠️ The download is suspiciously small - check the URL/branch.") return False open(dst, "wb").write(body) sys.path.insert(0, os.getcwd()) print(f" ✓ {dst} ({len(body)//1024} kB)") return True except Exception as e: print(f" ❌ {e}") return False def find_jams(): out = [] for base in ("/kaggle/input", ".", "/kaggle/working"): if not os.path.isdir(base): continue for r, _, files in os.walk(base): for f in files: if f.endswith(".jams"): out.append(os.path.join(r, f)) return sorted(set(out)) def main(): if not _locate_trainer(): sys.exit("❌ No model_trainer.py - without it the label parser would diverge.") import json import numpy as np import model_trainer as T jams = find_jams() if not jams: sys.exit("❌ No .jams files found - is GuitarSet attached?") print(f"🔍 JAMS files: {len(jams)}") print(f" base window: {T.CTX_FRAMES} frames = " f"{T.CTX_FRAMES * T.HOP_LENGTH / T.SR:.3f} s " f"(note coverage >= {T.NOTE_MIN_COVER:.0%})\n") hop_s = T.HOP_LENGTH / T.SR maxw = max(WINDOW_SIZES) # counter[window_size] -> [hits, total] audible = {w: [0, 0] for w in WINDOW_SIZES} is_bass = {w: [0, 0] for w in WINDOW_SIZES} too_short = {w: 0 for w in WINDOW_SIZES} # segments shorter than the window # GuitarSet has a COMP (chords) and a SOLO (improvisation over the same # progression) version of every excerpt, with the SAME chord annotation. # Mixing them understates root audibility - a solo sounds one note at a time. by_kind = {"comp": [0, 0], "solo": [0, 0]} by_fam = defaultdict(lambda: [0, 0]) # base-window ceiling by chord family root_disagree = [0, 0] # intended vs played disagree_ex = Counter() files_used = 0 no_notes = 0 for p in jams: try: j = json.load(open(p)) except Exception: continue # --- notes actually played: (start, end, midi) --- notes = [] chords = {"instructed": [], "performed": []} for a in j.get("annotations", []): ns = a.get("namespace", "") if ns == "note_midi": for o in T.jams_observations(a): t, dur, v = o.get("time"), o.get("duration"), o.get("value") if t is None or v is None: continue notes.append((float(t), float(t) + float(dur or 0.0), float(v))) elif ns == "chord": src = str(a.get("annotation_metadata", {}).get("data_source", "")).lower() key = "performed" if "transcription" in src else "instructed" for o in T.jams_observations(a): t, dur, v = o.get("time"), o.get("duration"), o.get("value") if t is None or v is None: continue r, q = T.parse_raw(str(v)) if not r: continue r = T.NORM_MAP.get(r, r) if r not in T.ROOTS: continue chords[key].append((float(t), float(t) + float(dur or 0.0), r, q)) if not chords["instructed"]: continue files_used += 1 if not notes: no_notes += 1 continue # --- frame grid --- # pres[f, pc] = 1 when pitch class pc sounds in frame f # low[f] = lowest sounding midi in frame f (for the "root = bass" test) t_end = max(max(e for _, e, _ in notes), max(e for _, e, _, _ in chords["instructed"])) n_fr = int(t_end / hop_s) + maxw + 2 pres = np.zeros((n_fr, 12), dtype=np.int32) low = np.full(n_fr, np.inf, dtype=np.float64) for t0, t1, midi in notes: f0 = max(0, int(t0 / hop_s)) f1 = min(n_fr, int(np.ceil(t1 / hop_s))) if f1 <= f0: continue pres[f0:f1, int(round(midi)) % 12] = 1 np.minimum(low[f0:f1], midi, out=low[f0:f1]) # cum[f] = frames < f in which pc sounded -> window coverage in O(1) cum = np.vstack([np.zeros((1, 12), np.int32), np.cumsum(pres, axis=0)]) # --- 3. root agreement: intended vs played, frame by frame --- if chords["performed"]: def root_at(seq, t): for t0, t1, r, _ in seq: if t0 <= t < t1: return r return None for f in range(0, n_fr - maxw, STRIDE): t = f * hop_s ri, rp = root_at(chords["instructed"], t), root_at(chords["performed"], t) if ri is None or rp is None: continue root_disagree[1] += 1 if ri != rp: root_disagree[0] += 1 disagree_ex[f"{ri}->{rp}"] += 1 # --- 1./2./4. root audibility ceiling for the INTENDED label --- # The window must fit ENTIRELY inside the chord segment, otherwise we would # count notes from the neighbouring chord and longer windows would look # better by accident. for t0, t1, r, q in chords["instructed"]: root_pc = T.ROOTS.index(r) f0, f1 = int(t0 / hop_s), int(t1 / hop_s) for w in WINDOW_SIZES: if f1 - f0 < w: too_short[w] += 1 continue for f in range(f0, f1 - w + 1, STRIDE): cover = cum[f + w] - cum[f] # (12,) frames per pitch class present = np.nonzero(cover >= T.NOTE_MIN_COVER * w)[0] if not len(present): continue audible[w][1] += 1 hit = root_pc in present audible[w][0] += hit lo = low[f:f + w].min() if np.isfinite(lo): is_bass[w][1] += 1 is_bass[w][0] += (int(round(lo)) % 12 == root_pc) if w == T.CTX_FRAMES: fam = T.get_family(q) by_fam[fam][1] += 1 by_fam[fam][0] += hit kind = "solo" if "_solo" in os.path.basename(p).lower() else "comp" by_kind[kind][1] += 1 by_kind[kind][0] += hit def pct(a): return f"{100.0 * a[0] / a[1]:.1f}%" if a[1] else " n/d" print("=" * 68) print("1./4. IS THE LABELLED ROOT AUDIBLE IN THE WINDOW AT ALL?") print("=" * 68) print(f"{'window':>6} {'time':>8} {'windows':>9} {'audible':>11} {'= bass':>8} {'segs too short':>18}") print("-" * 68) for w in WINDOW_SIZES: mark = " <- CTX_FRAMES" if w == T.CTX_FRAMES else "" print(f"{w:>6} {w*hop_s:>7.2f}s {audible[w][1]:>9} " f"{pct(audible[w]):>11} {pct(is_bass[w]):>8} {too_short[w]:>18}{mark}") print("\n 'segs too short' = chords shorter than the window, skipped. When that") print(" number grows with the window, a longer frame would span a chord change.") print(f"\n{'='*68}\n1b. ACCOMPANIMENT vs IMPROVISATION (window {T.CTX_FRAMES})\n{'='*68}") for kind, a in (("comp (chords)", by_kind["comp"]), ("solo (improvisation)", by_kind["solo"])): print(f" {kind:<22} root audible: {pct(a):>7} ({a[1]} windows)") print(" A solo file carries a monophonic line while the label describes the") print(" accompaniment chord; counting them together lowers the ceiling.") print(f"\n{'='*68}\n2. CEILING BY CHORD FAMILY (window {T.CTX_FRAMES})\n{'='*68}") for fam, a in sorted(by_fam.items(), key=lambda kv: -kv[1][1]): print(f" {str(fam):<16} {pct(a):>7} ({a[1]} windows)") print(f"\n{'='*68}\n3. ROOT: INTENDED vs PLAYED\n{'='*68}") if root_disagree[1]: d = 100.0 * root_disagree[0] / root_disagree[1] print(f" disagreements: {root_disagree[0]}/{root_disagree[1]} = {d:.1f}%") if disagree_ex: print(" most common: " + " ".join(f"{k}:{v}" for k, v in disagree_ex.most_common(8))) else: print(" no 'performed' annotations to compare against") print(f"\n{'='*68}\nVERDICT\n{'='*68}") base = audible[T.CTX_FRAMES] ceil = 100.0 * base[0] / base[1] if base[1] else 0.0 print(f" files with chords: {files_used} without note_midi: {no_notes}") print(f" CEILING for a {T.CTX_FRAMES}-frame window ({T.CTX_FRAMES*hop_s:.2f} s): {ceil:.1f}%") print(f" TRAIN Root in v2_take2 (epoch 36): 83.0%") if ceil < 88: print("\n -> The model already extracts nearly everything audible.") print(" The bottleneck is NOT capacity or regularisation but that the") print(" root is simply not played. Either a wider window, or a root") print(" derived from context rather than from one frame.") else: print("\n -> The root is audible far more often than the model gets it.") print(" The ceiling is not the limit; the problem is model/training.") gain = (100.0 * audible[maxw][0] / audible[maxw][1] - ceil) if audible[maxw][1] else 0.0 print(f" gain from a {maxw}-frame window ({maxw*hop_s:.2f} s): {gain:+.1f} pp") if __name__ == "__main__": main()