Collab Notebook Added

training/launch_hf_job.py

@@ -0,0 +1,165 @@
+from __future__ import annotations
+
+import argparse
+import os
+import shlex
+import sys
+from textwrap import dedent
+
+from huggingface_hub import run_job
+
+
+DEFAULT_IMAGE = "pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel"
+DEFAULT_REPO = "https://github.com/ADITYAGABA1322/sentinel-env"
+DEFAULT_MODEL = "unsloth/Qwen2.5-0.5B-Instruct"
+
+
+def shell_join(lines: list[str]) -> str:
+    return " && ".join(line.strip() for line in lines if line.strip())
+
+
+def bootstrap_repo(repo_url: str) -> list[str]:
+    return [
+        "set -eux",
+        "command -v git || (apt-get update && apt-get install -y git)",
+        f"git clone {shlex.quote(repo_url)} sentinel-env",
+        "cd sentinel-env",
+        "python -m pip install --upgrade pip",
+        "pip install -r requirements.txt",
+        "pip install -r requirements-train.txt",
+    ]
+
+
+def gpu_test_command() -> str:
+    return "python -c 'import torch; print(torch.cuda.get_device_name())'"
+
+
+def train_command(args: argparse.Namespace) -> str:
+    lines = bootstrap_repo(args.repo_url)
+    lines.append(
+        " ".join(
+            [
+                "python training/train.py",
+                f"--episodes {args.episodes}",
+                f"--task {shlex.quote(args.task)}",
+                f"--seed {args.seed}",
+                f"--model {shlex.quote(args.model)}",
+                f"--epochs {args.epochs}",
+                f"--batch-size {args.batch_size}",
+                f"--learning-rate {args.learning_rate}",
+                f"--lora-rank {args.lora_rank}",
+                f"--max-seq-length {args.max_seq_length}",
+                f"--output-dir {shlex.quote(args.output_dir)}",
+            ]
+        )
+    )
+    if args.mode == "train-full":
+        lines.extend(
+            [
+                "python -c \"from training.replay import record_trained_actions; "
+                f"record_trained_actions(adapter_path='{args.output_dir}', "
+                f"base_model='{args.model}', tasks=['task1','task2','task3'], "
+                "seeds=range(30), out_path='outputs/trained_policy_replay.jsonl')\"",
+                "python training/evaluate.py --episodes 30 --task all "
+                "--policies random,heuristic,oracle_lite,trained "
+                "--replay outputs/trained_policy_replay.jsonl "
+                "--out outputs/eval_post.json --no-plot",
+                "cp outputs/eval_post.json outputs/evaluation_results.json",
+                "python -m training.plots --pre outputs/eval_pre.json "
+                "--post outputs/eval_post.json --out-dir outputs/charts",
+                "python - <<'PY'\n"
+                "import os\n"
+                "from huggingface_hub import HfApi\n"
+                "token = os.environ.get('HF_TOKEN')\n"
+                "api = HfApi(token=token)\n"
+                "model_repo = os.environ.get('SENTINEL_MODEL_REPO', 'XcodeAddy/sentinel-grpo-qwen05')\n"
+                "artifact_repo = os.environ.get('SENTINEL_ARTIFACT_REPO', 'XcodeAddy/sentinel-env-artifacts')\n"
+                "job_id = os.environ.get('JOB_ID', 'manual')\n"
+                "api.create_repo(model_repo, repo_type='model', exist_ok=True)\n"
+                f"api.upload_folder(folder_path='{args.output_dir}', repo_id=model_repo, repo_type='model')\n"
+                "api.create_repo(artifact_repo, repo_type='dataset', exist_ok=True)\n"
+                "api.upload_folder(folder_path='outputs', repo_id=artifact_repo, repo_type='dataset', path_in_repo=f'job-{job_id}/outputs')\n"
+                "print('Uploaded model adapter to', model_repo)\n"
+                "print('Uploaded outputs to', artifact_repo, 'under', f'job-{job_id}/outputs')\n"
+                "PY",
+            ]
+        )
+    return shell_join(lines)
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description="Launch SENTINEL training on Hugging Face Jobs without shell quoting pain."
+    )
+    parser.add_argument("--mode", choices=["gpu-test", "train-smoke", "train-full"], default="gpu-test")
+    parser.add_argument("--namespace", default=os.environ.get("HF_NAMESPACE", "XcodeAddy"))
+    parser.add_argument("--flavor", default="a10g-small")
+    parser.add_argument("--timeout", default="2h")
+    parser.add_argument("--image", default=DEFAULT_IMAGE)
+    parser.add_argument("--repo-url", default=DEFAULT_REPO)
+    parser.add_argument("--model", default=DEFAULT_MODEL)
+    parser.add_argument("--episodes", type=int, default=50)
+    parser.add_argument("--task", choices=["task1", "task2", "task3", "all"], default="all")
+    parser.add_argument("--seed", type=int, default=0)
+    parser.add_argument("--epochs", type=int, default=1)
+    parser.add_argument("--batch-size", type=int, default=2)
+    parser.add_argument("--learning-rate", type=float, default=5e-6)
+    parser.add_argument("--lora-rank", type=int, default=8)
+    parser.add_argument("--max-seq-length", type=int, default=1024)
+    parser.add_argument("--output-dir", default="training/sentinel_qwen05_grpo")
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    token = os.environ.get("HF_TOKEN")
+    if not token:
+        raise SystemExit(
+            dedent(
+                """
+                HF_TOKEN is not set.
+
+                Run:
+                  read -s HF_TOKEN
+                  export HF_TOKEN
+                Then paste your Hugging Face write token.
+                """
+            ).strip()
+        )
+
+    command = gpu_test_command() if args.mode == "gpu-test" else train_command(args)
+    print("Launching HF Job:")
+    print(f"  mode      = {args.mode}")
+    print(f"  namespace = {args.namespace}")
+    print(f"  flavor    = {args.flavor}")
+    print(f"  timeout   = {args.timeout}")
+    print(f"  image     = {args.image}")
+    print("  command   = bash -lc", shlex.quote(command[:260] + ("..." if len(command) > 260 else "")))
+
+    job = run_job(
+        image=args.image,
+        command=["bash", "-lc", command],
+        flavor=args.flavor,
+        timeout=args.timeout,
+        namespace=args.namespace,
+        token=token,
+        secrets={"HF_TOKEN": token},
+        env={
+            "SENTINEL_MODEL_REPO": "XcodeAddy/sentinel-grpo-qwen05",
+            "SENTINEL_ARTIFACT_REPO": "XcodeAddy/sentinel-env-artifacts",
+        },
+        labels={"project": "sentinel", "mode": args.mode},
+    )
+    print("Job launched.")
+    print("URL:", job.url)
+    print("ID:", job.id)
+    print()
+    print("Follow logs with:")
+    print(f"  .venv/bin/hf jobs logs -f {job.id} --namespace {args.namespace} --token \"$HF_TOKEN\"")
+
+
+if __name__ == "__main__":
+    try:
+        main()
+    except KeyboardInterrupt:
+        sys.exit(130)

training/sentinel-env

@@ -0,0 +1 @@
+Subproject commit 5427e15ed4573661c53b1d9cb77a02922c8502fc