Add run_ablations_v2.py: v2 ablation runner with OGM-GE experiments

src/run_ablations_v2.py

@@ -0,0 +1,138 @@
+"""
+Multimodal PC Fault Detection - Ablation Runner v2
+====================================================
+Runs all ablation experiments using train_v2.py with OGM-GE.
+
+Usage: python run_ablations_v2.py [--quick_test]
+"""
+
+import os, sys, json, subprocess
+from config import FAULT_CLASSES
+
+
+def run_ablation_suite(quick_test=False):
+    experiments = [
+        {
+            "name": "Multimodal + LoRA + OGM-GE",
+            "args": [
+                "--mode", "multimodal", "--finetune", "lora",
+                "--fusion", "concat", "--eval_robustness",
+                "--output_dir", "./results/multimodal_lora_ogmge",
+                "--hub_model_id", "Ellaft/pc-fault-multimodal-lora-ogmge",
+            ],
+        },
+        {
+            "name": "Visual Only + LoRA",
+            "args": [
+                "--mode", "visual_only", "--finetune", "lora",
+                "--output_dir", "./results/visual_only_lora",
+                "--hub_model_id", "Ellaft/pc-fault-visual-only",
+            ],
+        },
+        {
+            "name": "Audio Only + LoRA",
+            "args": [
+                "--mode", "audio_only", "--finetune", "lora",
+                "--output_dir", "./results/audio_only_lora",
+                "--hub_model_id", "Ellaft/pc-fault-audio-only",
+            ],
+        },
+        {
+            "name": "Multimodal + Full FT + OGM-GE",
+            "args": [
+                "--mode", "multimodal", "--finetune", "full",
+                "--lr", "2e-5", "--fusion", "concat",
+                "--output_dir", "./results/multimodal_full_ft_ogmge",
+                "--hub_model_id", "Ellaft/pc-fault-multimodal-full-ft",
+            ],
+        },
+        {
+            "name": "Multimodal + Linear Probe + OGM-GE",
+            "args": [
+                "--mode", "multimodal", "--finetune", "linear_probe",
+                "--lr", "1e-3", "--fusion", "concat",
+                "--output_dir", "./results/multimodal_linear_probe_ogmge",
+                "--hub_model_id", "Ellaft/pc-fault-multimodal-linear-probe",
+            ],
+        },
+        {
+            "name": "Multimodal + LoRA + High Dropout + OGM-GE",
+            "args": [
+                "--mode", "multimodal", "--finetune", "lora",
+                "--modality_dropout", "0.5", "--fusion", "concat",
+                "--eval_robustness",
+                "--output_dir", "./results/multimodal_robust_ogmge",
+                "--hub_model_id", "Ellaft/pc-fault-multimodal-robust",
+            ],
+        },
+    ]
+
+    if quick_test:
+        for exp in experiments:
+            exp["args"].append("--quick_test")
+
+    all_results = {}
+    for exp in experiments:
+        print(f"\n{'='*60}")
+        print(f"Running: {exp['name']}")
+        print(f"{'='*60}")
+        result = subprocess.run(
+            [sys.executable, "train_v2.py"] + exp["args"],
+            capture_output=False)
+
+        results_dir = exp["args"][exp["args"].index("--output_dir") + 1]
+        rpath = os.path.join(results_dir, "results_v2.json")
+        if os.path.exists(rpath):
+            all_results[exp["name"]] = json.load(open(rpath))
+        else:
+            all_results[exp["name"]] = {"error": f"rc={result.returncode}"}
+
+    # Summary table
+    print(f"\n\n{'='*80}")
+    print(f"ABLATION STUDY RESULTS (v2 — with OGM-GE anti-collapse)")
+    print(f"{'='*80}")
+    print(f"{'Experiment':<42s} {'Accuracy':>10s} {'Macro-F1':>10s} {'Weighted-F1':>12s}")
+    print("-" * 76)
+    for name, r in all_results.items():
+        if "error" in r:
+            print(f"{name:<42s} {'ERROR':>10s}")
+        else:
+            m = r["final_metrics"]
+            print(f"{name:<42s} {m['accuracy']:>10.4f} {m['macro_f1']:>10.4f} {m['weighted_f1']:>12.4f}")
+
+    # Robustness comparison (if available)
+    print(f"\n{'='*80}")
+    print(f"MISSING MODALITY ROBUSTNESS")
+    print(f"{'='*80}")
+    print(f"{'Experiment':<42s} {'Both':>10s} {'Vis-Only':>10s} {'Aud-Only':>10s}")
+    print("-" * 76)
+    for name, r in all_results.items():
+        if "robustness" in r:
+            rb = r["robustness"]
+            print(f"{name:<42s} "
+                  f"{rb.get('both_modalities', {}).get('macro_f1', 0):>10.4f} "
+                  f"{rb.get('visual_only', {}).get('macro_f1', 0):>10.4f} "
+                  f"{rb.get('audio_only', {}).get('macro_f1', 0):>10.4f}")
+
+    # v1 vs v2 comparison reminder
+    print(f"\n{'='*80}")
+    print("v1 BASELINE (for comparison):")
+    print("  Both modalities: Acc=0.9423 F1=0.9481")
+    print("  Audio only:      Acc=0.9231 F1=0.9316")
+    print("  Visual only:     Acc=0.2308 F1=0.0750  ← MODALITY COLLAPSE")
+    print(f"{'='*80}")
+
+    # Save summary
+    os.makedirs("./results", exist_ok=True)
+    with open("./results/ablation_summary_v2.json", "w") as f:
+        json.dump(all_results, f, indent=2)
+    print(f"\nFull results saved to ./results/ablation_summary_v2.json")
+
+    return all_results
+
+
+if __name__ == "__main__":
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--quick_test", action="store_true")
+    run_ablation_suite(quick_test=parser.parse_args().quick_test)