Add 7B variant of HF Job for stronger cold-start.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

scripts/run_hf_job_7b.sh

@@ -0,0 +1,206 @@
+#!/usr/bin/env bash
+# Runs INSIDE the HF Job container. Self-contained: clones the repo, installs
+# deps, and walks Phases 0..6. On any failure, the trap pushes whatever
+# artifacts already landed in /tmp/results/ to the dataset repo under partial/.
+#
+# Required env vars (set via `hf jobs run --secret`):
+#   HF_TOKEN
+#   WANDB_API_KEY
+
+set -euo pipefail
+
+MODEL_REPO="jester1177/mutant-hunter-qwen-coder-7b-lora"
+DATASET_REPO="jester1177/mutant-hunter-results"
+RESULTS_DIR="/tmp/results"
+
+push_partial() {
+    rc=$?
+    echo ""
+    echo "[trap] caught exit code ${rc}; uploading whatever is in ${RESULTS_DIR}/ as partial/"
+    if [ -d "${RESULTS_DIR}" ]; then
+        python - <<'PY' || echo "[trap] partial upload itself failed; giving up"
+import os
+from huggingface_hub import HfApi
+api = HfApi()
+api.upload_folder(
+    folder_path="/tmp/results",
+    repo_id="jester1177/mutant-hunter-results",
+    repo_type="dataset",
+    path_in_repo="partial",
+)
+print("[trap] partial artifacts pushed to dataset repo under partial/")
+PY
+    else
+        echo "[trap] no ${RESULTS_DIR}/ directory exists; nothing to push"
+    fi
+    exit "${rc}"
+}
+trap push_partial ERR
+
+echo "=== Phase 0: setup ==="
+cd /tmp
+if [ ! -d MetaOpenEnv_MutantHunter ]; then
+    git clone https://github.com/melohub-xbit/MetaOpenEnv_MutantHunter.git
+fi
+cd MetaOpenEnv_MutantHunter
+mkdir -p "${RESULTS_DIR}" "${RESULTS_DIR}/training" "${RESULTS_DIR}/plots"
+
+python -c "import torch; assert torch.cuda.is_available(), 'No CUDA available in base image'; print(f'Using pre-installed torch {torch.__version__}, CUDA {torch.version.cuda}')"
+pip install --no-cache-dir -e ".[training]"
+pip install --no-cache-dir bitsandbytes wandb
+
+python -c "from huggingface_hub import login; login(token='${HF_TOKEN}')"
+python -c "import os; os.environ['HOME']='/tmp'; import wandb; wandb.login(key='${WANDB_API_KEY}')"
+
+python - <<'PY'
+from huggingface_hub import HfApi
+api = HfApi()
+api.create_repo("jester1177/mutant-hunter-qwen-coder-7b-lora", repo_type="model", exist_ok=True)
+api.create_repo("jester1177/mutant-hunter-results", repo_type="dataset", exist_ok=True)
+print("repos ready")
+PY
+
+echo "=== Phase 1: heuristic baseline (~5 min) ==="
+python training/baseline_eval.py \
+    --episodes 15 \
+    --policy mutation_aware \
+    --seed-start 0 \
+    --out "${RESULTS_DIR}/baseline_heuristic.json"
+
+python - <<'PY'
+from huggingface_hub import upload_file
+upload_file(
+    path_or_fileobj="/tmp/results/baseline_heuristic.json",
+    path_in_repo="baseline_heuristic.json",
+    repo_id="jester1177/mutant-hunter-results",
+    repo_type="dataset",
+)
+print("baseline_heuristic.json pushed")
+PY
+
+echo "=== Phase 2: zero-shot LLM baseline (~30 min) ==="
+python evaluation/zero_shot_distribution.py \
+    --episodes 15 \
+    --model Qwen/Qwen2.5-Coder-7B-Instruct \
+    --max-new-tokens 1024 \
+    --seed-start 0 \
+    --device auto
+
+cp evaluation/_results/zero_shot_distribution.json "${RESULTS_DIR}/baseline_zeroshot.json"
+
+python - <<'PY'
+from huggingface_hub import upload_file
+upload_file(
+    path_or_fileobj="/tmp/results/baseline_zeroshot.json",
+    path_in_repo="baseline_zeroshot.json",
+    repo_id="jester1177/mutant-hunter-results",
+    repo_type="dataset",
+)
+print("baseline_zeroshot.json pushed")
+PY
+
+echo "=== Phase 3: 200-step GRPO training (~4h) ==="
+python training/train_grpo.py \
+    --steps 80 \
+    --rollouts-per-step 3 \
+    --base-model Qwen/Qwen2.5-Coder-7B-Instruct \
+    --max-new-tokens 1024 \
+    --learning-rate 5e-6 \
+    --seed 42 \
+    --output-dir "${RESULTS_DIR}/training" \
+    --wandb-project mutant-hunter-final
+
+if [ ! -d "${RESULTS_DIR}/training/final" ]; then
+    echo "ERROR: ${RESULTS_DIR}/training/final/ not found after training" >&2
+    exit 1
+fi
+
+python - <<'PY'
+from huggingface_hub import HfApi
+HfApi().upload_folder(
+    folder_path="/tmp/results/training/final",
+    repo_id="jester1177/mutant-hunter-qwen-coder-7b-lora",
+    repo_type="model",
+)
+print("LoRA adapter pushed to model repo")
+PY
+
+if [ -f "${RESULTS_DIR}/training/training_log.jsonl" ]; then
+    python - <<'PY'
+from huggingface_hub import upload_file
+upload_file(
+    path_or_fileobj="/tmp/results/training/training_log.jsonl",
+    path_in_repo="training_log.jsonl",
+    repo_id="jester1177/mutant-hunter-qwen-coder-7b-lora",
+    repo_type="model",
+)
+print("training_log.jsonl pushed")
+PY
+else
+    echo "[warn] training_log.jsonl not found; skipping upload"
+fi
+
+echo "=== Phase 4: trained eval (~30 min) ==="
+# Stash Phase 2 output so the next run does not clobber it.
+cp "${RESULTS_DIR}/baseline_zeroshot.json" "${RESULTS_DIR}/baseline_zeroshot.keep.json"
+
+python evaluation/zero_shot_distribution.py \
+    --episodes 15 \
+    --model Qwen/Qwen2.5-Coder-7B-Instruct \
+    --lora-path "${RESULTS_DIR}/training/final" \
+    --max-new-tokens 1024 \
+    --seed-start 0 \
+    --device auto
+
+cp evaluation/_results/zero_shot_distribution.json "${RESULTS_DIR}/trained_eval.json"
+
+python - <<'PY'
+from huggingface_hub import upload_file
+upload_file(
+    path_or_fileobj="/tmp/results/trained_eval.json",
+    path_in_repo="trained_eval.json",
+    repo_id="jester1177/mutant-hunter-results",
+    repo_type="dataset",
+)
+print("trained_eval.json pushed")
+PY
+
+echo "=== Phase 5: plots ==="
+python evaluation/make_plots.py \
+    --baseline-heuristic-json "${RESULTS_DIR}/baseline_heuristic.json" \
+    --baseline-zeroshot-json "${RESULTS_DIR}/baseline_zeroshot.json" \
+    --trained-eval-json "${RESULTS_DIR}/trained_eval.json" \
+    --training-log-json "${RESULTS_DIR}/training/training_log.jsonl" \
+    --out-dir "${RESULTS_DIR}/plots/"
+
+python - <<'PY'
+from huggingface_hub import HfApi
+HfApi().upload_folder(
+    folder_path="/tmp/results/plots",
+    repo_id="jester1177/mutant-hunter-qwen-coder-7b-lora",
+    repo_type="model",
+    path_in_repo="plots",
+)
+print("plots/ pushed to model repo")
+PY
+
+echo "=== Phase 6: summary ==="
+echo "Model:   https://huggingface.co/${MODEL_REPO}"
+echo "Dataset: https://huggingface.co/datasets/${DATASET_REPO}"
+
+python - <<'PY' || echo "[warn] could not read W&B run URL"
+import os
+os.environ.setdefault("HOME", "/tmp")
+try:
+    import wandb
+    api = wandb.Api()
+    runs = api.runs("mutant-hunter-final", order="-created_at", per_page=1)
+    for r in runs:
+        print(f"W&B run: {r.url}")
+        break
+except Exception as e:
+    print(f"[warn] wandb URL lookup failed: {e}")
+PY
+
+echo ""
+echo "=== Done ==="