feat: add --check-env preflight flag for OOM risk detection before quantization

onecomp/cli.py

@@ -63,6 +63,14 @@ def main():
         default="auto",
         help='save directory (default: auto-generated, "none" to skip)',
     )
+    parser.add_argument(
+        "--check-env",
+        action="store_true",
+        help=(
+            "Print an environment and memory report before quantization. "
+            "Exits with code 1 if OOM risk is 'danger'."
+        ),
+    )
     parser.add_argument(
         "--version",
         action="version",
@@ -76,6 +84,23 @@ def main():
     # Lazy import to keep --help fast
     from .runner import Runner  # pylint: disable=import-outside-toplevel
 
+    if args.check_env:
+        import sys  # pylint: disable=import-outside-toplevel
+        from .utils.vram_estimator import (  # pylint: disable=import-outside-toplevel
+            check_environment,
+            print_env_report,
+        )
+
+        env_result = check_environment(
+            args.model_id,
+            total_vram_gb=args.total_vram_gb,
+            group_size=args.groupsize,
+            save_dir=save_dir if isinstance(save_dir, str) and save_dir != "auto" else None,
+        )
+        print_env_report(env_result, total_vram_gb_override=args.total_vram_gb)
+        if env_result.risk == "danger":
+            sys.exit(1)
+
     Runner.auto_run(
         model_id=args.model_id,
         wbits=args.wbits,

onecomp/runner.py

@@ -417,6 +417,7 @@ def auto_run(
         evaluate: bool = True,
         eval_original_model: bool = False,
         save_dir: str = "auto",
+        check_env: bool = False,
         **kwargs,
     ):
         """One-liner quantization with sensible defaults.
@@ -487,6 +488,24 @@ def auto_run(
         setup_logger()
         logger = getLogger(__name__)
 
+        if check_env:
+            from .utils.vram_estimator import (  # pylint: disable=import-outside-toplevel
+                check_environment,
+                print_env_report,
+            )
+
+            env_result = check_environment(
+                model_id,
+                total_vram_gb=total_vram_gb,
+                group_size=groupsize,
+                save_dir=save_dir if isinstance(save_dir, str) and save_dir != "auto" else None,
+            )
+            print_env_report(env_result, total_vram_gb_override=total_vram_gb)
+            if env_result.risk == "danger":
+                raise RuntimeError(
+                    f"Environment check failed (OOM risk=danger): {env_result.risk_detail}"
+                )
+
         candidate_bits = (2, 3, 4, 8)
 
         if wbits is None:

onecomp/utils/__init__.py

@@ -25,6 +25,11 @@
     effective_bits_for_quantizer,
     weight_memory_gb,
     VRAMBitwidthEstimation,
+    EnvironmentSnapshot,
+    ModelMemoryProfile,
+    EnvCheckResult,
+    check_environment,
+    print_env_report,
 )
 
 from .model_inputs import add_model_specific_inputs

onecomp/utils/vram_estimator.py

@@ -153,6 +153,42 @@ class VRAMBitwidthEstimation:
     meta_bits_per_param: float
 
 
+@dataclass
+class EnvironmentSnapshot:
+    """Physical hardware readings at check-env time."""
+
+    gpu_count: int
+    gpu_name: str | None
+    gpu_total_vram_gb: float | None
+    gpu_free_vram_gb: float | None
+    ram_total_gb: float | None
+    ram_available_gb: float | None
+    disk_available_gb: float | None
+    disk_path: str
+
+
+@dataclass
+class ModelMemoryProfile:
+    """Derived memory footprint for the target model."""
+
+    total_params: int
+    fp16_gb: float
+    quantized_gb: dict
+    calibration_overhead_gb: float
+
+
+@dataclass
+class EnvCheckResult:
+    """Composite result returned by check_environment()."""
+
+    model_id: str
+    env: EnvironmentSnapshot
+    model: ModelMemoryProfile
+    estimation: VRAMBitwidthEstimation | None
+    risk: str
+    risk_detail: str
+
+
 def estimate_target_bitwidth(
     model: torch.nn.Module,
     vram_ratio: float = 0.70,
@@ -322,3 +358,241 @@ def estimate_wbits_from_vram(
         wbits=wbits,
         logger=logger,
     )
+
+
+def check_environment(
+    model_id: str,
+    *,
+    total_vram_gb: float | None = None,
+    group_size: int = 128,
+    save_dir: str | None = None,
+    vram_ratio: float = 0.80,
+    calibration_overhead_ratio: float = 0.15,
+) -> EnvCheckResult:
+    """Collect hardware info and estimate OOM risk before quantization.
+
+    Loads the model architecture on a ``meta`` device (no GPU/CPU memory)
+    to count parameters, then compares available VRAM against estimated
+    memory requirements at 2/4/8-bit quantization.
+
+    Args:
+        model_id: Hugging Face model ID or local path.
+        total_vram_gb: Override GPU VRAM in GB for estimation math only.
+            Physical GPU readings are always from the real device.
+        group_size: GPTQ group size for metadata calculation.
+        save_dir: Path used for disk-space check. Defaults to cwd.
+        vram_ratio: Fraction of VRAM allocated for the estimation budget.
+        calibration_overhead_ratio: Calibration activation buffer as a
+            fraction of the FP16 model footprint (default 15 %).
+
+    Returns:
+        :class:`EnvCheckResult` with hardware snapshot, memory profile,
+        VRAM estimation, and risk level (``"safe"``, ``"warning"``,
+        ``"danger"``, or ``"unknown"``).
+    """
+    import os
+    import pathlib
+    import shutil
+
+    from transformers import AutoConfig, AutoModelForCausalLM
+
+    # --- GPU snapshot --------------------------------------------------------
+    gpu_count = torch.cuda.device_count()
+    if gpu_count > 0:
+        dev = torch.cuda.current_device()
+        props = torch.cuda.get_device_properties(dev)
+        gpu_name = props.name
+        gpu_total_vram_gb = props.total_memory / _BYTES_PER_GB
+        try:
+            free_bytes, _ = torch.cuda.mem_get_info(dev)
+            gpu_free_vram_gb = free_bytes / _BYTES_PER_GB
+        except Exception:
+            gpu_free_vram_gb = None
+    else:
+        gpu_name = None
+        gpu_total_vram_gb = None
+        gpu_free_vram_gb = None
+
+    # --- CPU RAM (psutil optional) -------------------------------------------
+    try:
+        import psutil
+
+        vm = psutil.virtual_memory()
+        ram_total_gb = vm.total / _BYTES_PER_GB
+        ram_available_gb = vm.available / _BYTES_PER_GB
+    except ImportError:
+        ram_total_gb = None
+        ram_available_gb = None
+
+    # --- Disk space (stdlib) -------------------------------------------------
+    check_path = save_dir if save_dir else os.getcwd()
+    p = pathlib.Path(check_path)
+    while not p.exists():
+        p = p.parent
+    disk_available_gb = shutil.disk_usage(p).free / _BYTES_PER_GB
+
+    # --- Model memory profile ------------------------------------------------
+    config = AutoConfig.from_pretrained(model_id)
+    with torch.device("meta"):
+        model = AutoModelForCausalLM.from_config(config, torch_dtype=torch.float16)
+
+    total_params = sum(p.numel() for p in model.parameters())
+    fp16_gb = (total_params * 2) / _BYTES_PER_GB
+    quantized_gb = {b: weight_memory_gb(total_params, b, group_size) for b in (2, 4, 8)}
+    calibration_overhead_gb = fp16_gb * calibration_overhead_ratio
+
+    # --- VRAM bitwidth estimation (reuse existing) ---------------------------
+    try:
+        estimation = estimate_target_bitwidth(
+            model,
+            vram_ratio=vram_ratio,
+            total_vram_gb=total_vram_gb,
+            group_size=group_size,
+        )
+    except (RuntimeError, ValueError):
+        estimation = None
+
+    # --- OOM risk assessment -------------------------------------------------
+    # Use free VRAM (runtime reality) when available; fall back to override.
+    effective_vram = gpu_free_vram_gb if gpu_free_vram_gb is not None else total_vram_gb
+
+    if effective_vram is None:
+        risk = "unknown"
+        risk_detail = "No GPU detected and no --total-vram-gb provided."
+    else:
+        need_4bit = quantized_gb[4] + calibration_overhead_gb
+        if effective_vram >= fp16_gb * 1.2:
+            risk = "safe"
+            risk_detail = (
+                f"Free VRAM ({effective_vram:.1f} GB) comfortably fits "
+                f"even FP16 weights ({fp16_gb:.1f} GB × 1.2)."
+            )
+        elif effective_vram >= need_4bit:
+            risk = "warning"
+            risk_detail = (
+                f"Free VRAM ({effective_vram:.1f} GB) fits 4-bit quantized "
+                f"weights but is tight (calibration overhead included)."
+            )
+        else:
+            risk = "danger"
+            risk_detail = (
+                f"Free VRAM ({effective_vram:.1f} GB) is insufficient for "
+                f"4-bit + calibration ({need_4bit:.1f} GB needed)."
+            )
+
+    return EnvCheckResult(
+        model_id=model_id,
+        env=EnvironmentSnapshot(
+            gpu_count=gpu_count,
+            gpu_name=gpu_name,
+            gpu_total_vram_gb=gpu_total_vram_gb,
+            gpu_free_vram_gb=gpu_free_vram_gb,
+            ram_total_gb=ram_total_gb,
+            ram_available_gb=ram_available_gb,
+            disk_available_gb=disk_available_gb,
+            disk_path=str(p),
+        ),
+        model=ModelMemoryProfile(
+            total_params=total_params,
+            fp16_gb=fp16_gb,
+            quantized_gb=quantized_gb,
+            calibration_overhead_gb=calibration_overhead_gb,
+        ),
+        estimation=estimation,
+        risk=risk,
+        risk_detail=risk_detail,
+    )
+
+
+def print_env_report(result: EnvCheckResult, *, total_vram_gb_override: float | None = None) -> None:
+    """Print a human-readable environment and OOM risk report to stdout.
+
+    Args:
+        result: The :class:`EnvCheckResult` from :func:`check_environment`.
+        total_vram_gb_override: When not ``None``, annotates the VRAM budget
+            line with ``[--total-vram-gb override]``.
+    """
+    _W = 60
+    _SEP = "=" * _W
+    _COL = 22
+
+    def _row(label: str, value: str) -> str:
+        return f"  {label:<{_COL}}: {value}"
+
+    risk_labels = {
+        "safe": "SAFE",
+        "warning": "WARNING",
+        "danger": "DANGER !!",
+        "unknown": "UNKNOWN",
+    }
+    risk_label = risk_labels.get(result.risk, result.risk.upper())
+
+    e = result.env
+    m = result.model
+
+    print(_SEP)
+    print("  OneComp Environment Check")
+    print(_SEP)
+    print()
+
+    # Hardware
+    print("Hardware")
+    print(_row("GPU count", str(e.gpu_count)))
+    if e.gpu_name is not None:
+        print(_row("GPU name", e.gpu_name))
+    if e.gpu_total_vram_gb is not None:
+        label = "GPU VRAM (total)"
+        value = f"{e.gpu_total_vram_gb:.1f} GB"
+        if total_vram_gb_override is not None:
+            value += "  [physical]"
+        print(_row(label, value))
+    if total_vram_gb_override is not None:
+        print(_row("VRAM budget used", f"{total_vram_gb_override:.1f} GB  [--total-vram-gb override]"))
+    if e.gpu_free_vram_gb is not None:
+        print(_row("GPU VRAM (free)", f"{e.gpu_free_vram_gb:.1f} GB"))
+    if e.ram_total_gb is not None:
+        print(_row("CPU RAM (total)", f"{e.ram_total_gb:.1f} GB"))
+        print(_row("CPU RAM (avail)", f"{e.ram_available_gb:.1f} GB"))
+    else:
+        print(_row("CPU RAM", "n/a (install psutil for RAM info)"))
+    print(_row("Disk (avail)", f"{e.disk_available_gb:.1f} GB  [{e.disk_path}]"))
+    print()
+
+    # Model
+    print(f"Model: {result.model_id}")
+    print(_row("Parameters", f"{m.total_params:,}"))
+    print(_row("FP16 footprint", f"{m.fp16_gb:.2f} GB"))
+    print()
+
+    # Memory estimates
+    gs = "(group_size varies)"
+    print(f"Memory Estimates")
+    for bits in (2, 4, 8):
+        print(_row(f"{bits}-bit quantized", f"{m.quantized_gb[bits]:.2f} GB"))
+    print(_row("Calib. overhead", f"{m.calibration_overhead_gb:.2f} GB  (15% of FP16)"))
+    print(_row("4-bit + overhead", f"{m.quantized_gb[4] + m.calibration_overhead_gb:.2f} GB"))
+    print()
+
+    # OOM risk
+    print("OOM Risk Assessment")
+    print(_row("Risk level", risk_label))
+    detail_words = result.risk_detail.split()
+    detail_line = ""
+    detail_lines = []
+    for word in detail_words:
+        if len(detail_line) + len(word) + 1 > 34:
+            detail_lines.append(detail_line)
+            detail_line = word
+        else:
+            detail_line = (detail_line + " " + word).lstrip()
+    if detail_line:
+        detail_lines.append(detail_line)
+    for i, dl in enumerate(detail_lines):
+        if i == 0:
+            print(_row("Detail", dl))
+        else:
+            print(f"  {'':<{_COL}}  {dl}")
+    print()
+    if result.estimation is not None:
+        print(_row("Recommended wbits", f"{result.estimation.target_bitwidth:.2f}  (VRAM-estimated)"))
+    print(_SEP)

pyproject.toml

@@ -53,10 +53,12 @@ cu124 = ["torch", "torchvision"]
 cu126 = ["torch", "torchvision"]
 cu128 = ["torch", "torchvision"]
 cu130 = ["torch", "torchvision"]
+check-env = ["psutil>=5.9"]
 dev = [
     "black",
     "hydra-core",
     "pylint",
+    "psutil>=5.9",
     "pytest",
 ]
 visualize = [