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-rwxr-xr-xexperiments/rain_ep_dillavou_s0b.sh105
1 files changed, 105 insertions, 0 deletions
diff --git a/experiments/rain_ep_dillavou_s0b.sh b/experiments/rain_ep_dillavou_s0b.sh
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+#!/usr/bin/env bash
+set -euo pipefail
+
+ROOT=/home/yurenh2/sdil
+AUTHOR=/scratch/yurenh2/energy-based-learning
+PYTHON=/scratch/yurenh2/venvs/burstccn/bin/python
+OUT="$ROOT/results/ep_bias/dillavou_s0b"
+mkdir -p "$OUT"
+cd "$AUTHOR"
+
+run_cell() {
+ local gpu=$1
+ local tag=$2
+ local beta_policy=$3
+ local beta_value=$4
+ local mode=$5
+ local bias_ratio=$6
+ CUDA_VISIBLE_DEVICES="$gpu" "$PYTHON" \
+ "$ROOT/experiments/rain_ep_bias_train.py" \
+ --author-root "$AUTHOR" --device cuda \
+ --adapter dillavou --network-protocol comparative32 \
+ --beta-policy "$beta_policy" --beta-value "$beta_value" \
+ --mode "$mode" --bias-ratio "$bias_ratio" \
+ --dillavou-drift-ratio 0 --predictor-rate 1 \
+ --dillavou-calibration-steps 1 --neutral-cadence 0 \
+ --epochs 1 --schedule-epochs 100 \
+ --train-limit 10000 --test-limit 2000 --batch-size 100 \
+ --training-iterations 15 --inference-iterations 60 \
+ --evaluation-split train_holdout --data-seed 6200 \
+ --seed 1988 --beta-seed 7100 --deterministic \
+ --output "$OUT/$tag.json" > "$OUT/$tag.log" 2>&1
+}
+
+# Wave 1: select the smallest fixed offset causing at least ten accuracy points
+# of damage relative to clean positive EP. This is development-only selection.
+run_cell 0 pep_clean fixed_positive 0.25 clean 0 &
+run_cell 1 pep_raw_03 fixed_positive 0.25 raw 0.3 &
+run_cell 2 pep_raw_1 fixed_positive 0.25 raw 1 &
+run_cell 3 pep_raw_3 fixed_positive 0.25 raw 3 &
+run_cell 4 pep_raw_10 fixed_positive 0.25 raw 10 &
+run_cell 5 random_clean random_sign 0.25 clean 0 &
+run_cell 6 centered_clean centered 0.25 clean 0 &
+run_cell 7 pep_sdil_3 fixed_positive 0.25 innovation 3 &
+wait
+
+selected=$("$PYTHON" - "$OUT" <<'PY'
+import json
+from pathlib import Path
+import sys
+
+root = Path(sys.argv[1])
+clean = json.loads((root / "pep_clean.json").read_text())["final"]["test_accuracy"]
+candidates = [(0.3, "03"), (1.0, "1"), (3.0, "3"), (10.0, "10")]
+rows = []
+selected = candidates[-1][0]
+for ratio, tag in candidates:
+ final = json.loads((root / f"pep_raw_{tag}.json").read_text())["final"]
+ rows.append({"ratio": ratio, "accuracy": final["test_accuracy"],
+ "finite": final["finite"]})
+ if final["finite"] and final["test_accuracy"] <= clean - 0.10:
+ selected = ratio
+ break
+(root / "selector.json").write_text(json.dumps({
+ "rule": "smallest ratio with >=0.10 accuracy damage and finite parameters",
+ "clean_accuracy": clean,
+ "candidates": rows,
+ "selected_ratio": selected,
+}, indent=2) + "\n")
+print(selected)
+PY
+)
+
+# Wave 2: test beta centering, the two local calibrators, an oracle, and larger
+# beta values at the selected hardware-offset magnitude.
+run_cell 0 pep_constant_selected fixed_positive 0.25 constant "$selected" &
+run_cell 1 pep_sdil_selected fixed_positive 0.25 innovation "$selected" &
+run_cell 2 pep_oracle_selected fixed_positive 0.25 oracle "$selected" &
+run_cell 3 random_raw_selected random_sign 0.25 raw "$selected" &
+run_cell 4 centered_raw_selected centered 0.25 raw "$selected" &
+run_cell 5 pep_raw_beta05 fixed_positive 0.5 raw "$selected" &
+run_cell 6 pep_raw_beta1 fixed_positive 1.0 raw "$selected" &
+run_cell 7 pep_raw_beta2 fixed_positive 2.0 raw "$selected" &
+wait
+
+"$PYTHON" - "$OUT" <<'PY'
+import json
+from pathlib import Path
+import sys
+
+root = Path(sys.argv[1])
+summary = {}
+for path in sorted(root.glob("*.json")):
+ if path.name in {"selector.json", "summary.json"}:
+ continue
+ report = json.loads(path.read_text())
+ summary[path.stem] = {
+ "test_accuracy": report["final"]["test_accuracy"],
+ "test_cost": report["final"]["test_cost"],
+ "finite": report["final"]["finite"],
+ "wall_seconds": report["final"]["wall_seconds"],
+ "corrector": report["final"]["corrector"],
+ }
+(root / "summary.json").write_text(json.dumps(summary, indent=2) + "\n")
+print(json.dumps(summary, indent=2))
+PY