Add missing training runs script

run_missing_training_runs.sh

@@ -0,0 +1,130 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# Linux bash 5.2+ training-only script.
+#
+# Based on the existing runs, the objective/time/death-distribution checks are
+# already covered. The remaining gap for the current proof chain is the
+# extra-info ablation under the final candidate model:
+#
+#   all_future + relative time + mixed death/risk head
+#
+# This script only launches those missing training jobs. It intentionally does
+# not call evaluate_*.py and does not add extra random seeds.
+
+cd "$(dirname "${BASH_SOURCE[0]}")"
+
+PYTHON_BIN="${PYTHON_BIN:-python}"
+DEVICE="${DEVICE:-cuda}"
+NUM_WORKERS="${NUM_WORKERS:-4}"
+PROGRESS_INTERVAL="${PROGRESS_INTERVAL:-20}"
+
+TIME_MODE="relative"
+DIST_MODE="mixed"
+SEED="42"
+VALIDATION_QUERY_SEED="42"
+
+COMMON_ARGS=(
+  --data_prefix ukb
+  --labels_file labels.csv
+  --seed "${SEED}"
+  --validation_query_seed "${VALIDATION_QUERY_SEED}"
+  --train_eid_file ukb_train_eid.csv
+  --val_eid_file ukb_val_eid.csv
+  --test_eid_file ukb_test_eid.csv
+  --min_history_events 1
+  --min_future_events 1
+  --n_embd 120
+  --n_head 10
+  --n_hist_layer 12
+  --n_tab_layer 4
+  --n_bins 16
+  --extra_pool_reduce mean
+  --dropout 0.0
+  --batch_size 256
+  --base_lr 0.0003
+  --weight_decay 0.1
+  --betas 0.9 0.99
+  --grad_clip 1.0
+  --max_epochs 200
+  --warmup_epochs 10
+  --patience 15
+  --min_lr_ratio 0.1
+  --num_workers "${NUM_WORKERS}"
+  --device "${DEVICE}"
+  --progress_interval "${PROGRESS_INTERVAL}"
+)
+
+already_trained() {
+  local extra_file="$1"
+  "${PYTHON_BIN}" - "$TIME_MODE" "$DIST_MODE" "$extra_file" "$SEED" "$VALIDATION_QUERY_SEED" <<'PY'
+import json
+import sys
+from pathlib import Path
+
+time_mode, dist_mode, extra_file, seed, validation_query_seed = sys.argv[1:6]
+extra_name = Path(extra_file).name
+
+for config_path in Path("runs").glob("*/train_config.json"):
+    try:
+        cfg = json.loads(config_path.read_text(encoding="utf-8"))
+    except Exception:
+        continue
+
+    observed_query_seed = cfg.get(
+        "all_future_validation_query_seed",
+        cfg.get("validation_query_seed", -1),
+    )
+
+    if (
+        cfg.get("model_target_mode") == "all_future"
+        and cfg.get("time_mode") == time_mode
+        and cfg.get("dist_mode") == dist_mode
+        and Path(str(cfg.get("extra_info_types_file", ""))).name == extra_name
+        and int(cfg.get("seed", -1)) == int(seed)
+        and int(observed_query_seed) == int(validation_query_seed)
+    ):
+        print(config_path.parent)
+        raise SystemExit(0)
+
+raise SystemExit(1)
+PY
+}
+
+train_if_missing() {
+  local label="$1"
+  local extra_file="$2"
+
+  if [[ ! -f "${extra_file}" ]]; then
+    echo "ERROR: missing extra-info type file: ${extra_file}" >&2
+    return 2
+  fi
+
+  echo "==> Checking ${label}: ${TIME_MODE} ${DIST_MODE} all_future with ${extra_file}"
+  if existing_run="$(already_trained "$extra_file")"; then
+    echo "    skip: already trained at ${existing_run}"
+    return 0
+  fi
+
+  echo "    train: ${label}"
+  "${PYTHON_BIN}" train_all_future.py \
+    "${COMMON_ARGS[@]}" \
+    --time_mode "${TIME_MODE}" \
+    --dist_mode "${DIST_MODE}" \
+    --extra_info_types_file "${extra_file}"
+}
+
+# Already present in runs/:
+# - next-token objective checks under SAB, plus older absolute extra ablations
+# - all-future absolute/relative x exponential/weibull/mixed under SAB
+#
+# Still needed:
+# - final all-future relative+mixed extra-info ablations beyond the existing
+#   SAB baseline. These close the disease-only question without expanding seed
+#   count or running downstream evaluation.
+train_if_missing "true_disease_only" "extra_info_types_none.txt"
+train_if_missing "assessment_only_extra" "extra_info_types_assessment_only.txt"
+train_if_missing "exposure_only_extra" "extra_info_types_exposure_only.txt"
+train_if_missing "all_extra_info" "extra_info_types_all.txt"
+
+echo "All requested training-only missing configurations are done."