5-th DL fix
This commit is contained in:
@@ -65,6 +65,7 @@ def _run_node(cfg: dict) -> None:
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vram_mb_override=cfg.get("vram_mb_override"),
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max_loaded_shards=int(cfg.get("max_loaded_shards", 1)),
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debug=bool(cfg.get("debug", False)),
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tracker_source_disabled=bool(cfg.get("tracker_source_disabled", False)),
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)
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except Exception as exc:
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print(f"\nERROR: {exc}", file=sys.stderr, flush=True)
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@@ -148,6 +149,8 @@ def _cmd_default(args) -> int:
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overrides["max_loaded_shards"] = args.max_shards
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if args.debug:
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overrides["debug"] = True
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if getattr(args, "tracker_source_disabled", False):
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overrides["tracker_source_disabled"] = True
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if overrides:
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cfg = merge_cli_overrides(cfg, **overrides)
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@@ -245,6 +248,7 @@ def _cmd_start(args) -> int:
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vram_mb_override=getattr(args, "memory", None),
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max_loaded_shards=getattr(args, "max_shards", 1),
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debug=getattr(args, "debug", False),
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tracker_source_disabled=getattr(args, "tracker_source_disabled", False),
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)
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except Exception as exc:
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print(f"ERROR: {exc}", file=sys.stderr, flush=True)
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@@ -281,6 +285,8 @@ def main() -> None:
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help="Quantization level")
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parser.add_argument("--download-dir", metavar="PATH", help="Model download directory")
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parser.add_argument("--tracker", metavar="URL", help="Tracker URL")
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parser.add_argument("--tracker-source-disabled", action="store_true",
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help="Skip tracker/peer model-file sources and download from HuggingFace directly")
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parser.add_argument("--wallet", metavar="PATH", help="Wallet file path")
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parser.add_argument("--shard-start", type=int, metavar="N", help="Pin shard start layer")
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parser.add_argument("--shard-end", type=int, metavar="N", help="Pin shard end layer")
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@@ -329,6 +335,8 @@ def main() -> None:
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start_cmd.add_argument("--max-shards", type=int, default=1, metavar="N",
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help="Maximum shard slots this node advertises to the tracker (default 1)")
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start_cmd.add_argument("--debug", action="store_true", help="Enable verbose node debug logging")
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start_cmd.add_argument("--tracker-source-disabled", action="store_true",
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help="Skip tracker/peer model-file sources and download from HuggingFace directly")
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args = parser.parse_args()
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@@ -13,7 +13,6 @@ import tarfile
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import tempfile
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import urllib.parse
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import urllib.request
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from pathlib import Path
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from typing import Any
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@@ -147,11 +146,13 @@ def _download_model_source(
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if progress:
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print(f" {label}: transfer complete ({received / 1e9:.2f} GB), extracting ...", flush=True)
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_safe_extract_shard(archive_path, extract_dir)
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if shard_dir.exists():
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shutil.rmtree(shard_dir)
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shutil.move(str(extract_dir), str(shard_dir))
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return shard_dir
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except Exception as exc:
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if progress:
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print(f" {label}: download failed: {exc!r}", flush=True)
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print(f" {label}: download failed ({url}): {exc!r}", flush=True)
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return None
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@@ -177,55 +178,6 @@ def _download_huggingface_subset(
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return Path(snapshot_download(**kwargs))
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def _download_from_fastest_source(
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*,
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model_sources: list[dict],
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hf_repo: str,
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cache_dir: Path,
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shard_dir: Path,
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progress: bool,
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timeout: float,
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) -> tuple[str, Path] | None:
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shard_dir.parent.mkdir(parents=True, exist_ok=True)
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with tempfile.TemporaryDirectory(prefix="meshnet-race-", dir=shard_dir.parent) as tmp:
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tmp_root = Path(tmp)
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jobs: dict[Any, tuple[str, Path]] = {}
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pool = ThreadPoolExecutor(max_workers=min(4, len(model_sources) + 1))
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try:
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for index, source in enumerate(model_sources):
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label = str(source.get("type") or "model-source")
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candidate = tmp_root / f"source-{index}"
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jobs[pool.submit(
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_download_model_source, source, candidate, timeout, progress, label,
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)] = (label, candidate)
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allow_patterns = _allow_patterns_from_sources(model_sources)
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hf_candidate = tmp_root / "huggingface"
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jobs[pool.submit(_download_huggingface_subset, hf_repo, cache_dir, hf_candidate, allow_patterns)] = (
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"HuggingFace",
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hf_candidate,
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)
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for future in as_completed(jobs):
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label, candidate = jobs[future]
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try:
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result = future.result()
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except Exception as exc:
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if progress:
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print(f" {label}: download failed: {exc!r}", flush=True)
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continue
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if result is None:
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continue
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if shard_dir.exists():
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shutil.rmtree(shard_dir)
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shutil.move(str(candidate), str(shard_dir))
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if progress:
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print(f" download source: {label}", flush=True)
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pool.shutdown(wait=False, cancel_futures=True)
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return label, shard_dir
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finally:
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pool.shutdown(wait=False, cancel_futures=True)
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return None
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def _allow_patterns_from_sources(model_sources: list[dict]) -> list[str] | None:
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patterns: set[str] = set()
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for source in model_sources:
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@@ -336,21 +288,31 @@ def download_shard(
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f" Downloading layers {shard_start}-{shard_end} from {hf_repo} ...",
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flush=True,
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)
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if model_sources:
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# Tracker (or peer) model sources are preferred outright — usually LAN-fast.
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# HuggingFace is only the fallback when every advertised source fails.
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for source in model_sources or []:
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label = str(source.get("type") or "model-source")
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if progress:
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print(" Racing tracker model source against HuggingFace ...", flush=True)
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raced = _download_from_fastest_source(
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model_sources=model_sources,
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hf_repo=hf_repo,
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cache_dir=cache_dir,
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shard_dir=shard_dir,
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progress=progress,
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print(f" Downloading from {label} model source (HuggingFace is the fallback) ...", flush=True)
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fetched = _download_model_source(
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source,
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shard_dir,
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timeout=max(peer_timeout, _MODEL_SOURCE_TIMEOUT_SECONDS),
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progress=progress,
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label=label,
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)
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if raced is not None:
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return raced[1]
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if fetched is not None:
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if progress:
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print(f" download source: {label}", flush=True)
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return fetched
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if model_sources and progress:
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print(" All model sources failed — falling back to HuggingFace ...", flush=True)
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allow_patterns = _allow_patterns_from_remote_index(hf_repo, cache_dir, shard_start, shard_end)
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allow_patterns = None
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if model_sources:
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allow_patterns = _allow_patterns_from_sources(model_sources)
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if allow_patterns is None:
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allow_patterns = _allow_patterns_from_remote_index(hf_repo, cache_dir, shard_start, shard_end)
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if progress:
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if allow_patterns:
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print(" download source: HuggingFace (layer-filtered)", flush=True)
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@@ -332,6 +332,7 @@ def run_startup(
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vram_mb_override: int | None = None,
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max_loaded_shards: int = 1,
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debug: bool = False,
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tracker_source_disabled: bool = False,
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) -> StubNodeServer | TorchNodeServer:
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"""Execute the full startup sequence and return a running node server.
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@@ -458,7 +459,10 @@ def run_startup(
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if net_asgn.get("hf_repo") == model_id and net_asgn.get("gap_found"):
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shard_start = net_asgn["shard_start"]
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shard_end = net_asgn["shard_end"]
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full_sources = _full_model_sources(net_asgn.get("model_sources", []))
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full_sources = (
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[] if tracker_source_disabled
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else _full_model_sources(net_asgn.get("model_sources", []))
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)
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if full_sources:
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cache_dir = download_shard(
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model_id.split("/")[-1],
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@@ -588,7 +592,7 @@ def run_startup(
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f"(of {assigned_num_layers})",
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flush=True,
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)
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full_sources = _full_model_sources(assigned_model_sources)
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full_sources = [] if tracker_source_disabled else _full_model_sources(assigned_model_sources)
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if full_sources:
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print("Downloading assigned model snapshot...", flush=True)
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cache_dir = download_shard(
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@@ -676,7 +680,10 @@ def run_startup(
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assign_qs = urllib.parse.urlencode({
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"model": model,
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"device": device,
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"vram_mb": vram_mb,
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# CPU-mode nodes must be sized by RAM: a detected-but-unusable GPU's
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# VRAM would otherwise cap the shard (e.g. 8 GB VRAM → 3 layers on a
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# 79 GB box whose Torch has no CUDA).
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"vram_mb": assignment_vram_mb,
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"ram_mb": ram_mb,
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})
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try:
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@@ -690,7 +697,7 @@ def run_startup(
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assigned_model: str = assignment.get("model", model)
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hf_repo: str | None = assignment.get("hf_repo")
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peers: list[dict] = assignment.get("peers", [])
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model_sources: list[dict] = assignment.get("model_sources", [])
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model_sources: list[dict] = [] if tracker_source_disabled else assignment.get("model_sources", [])
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print(f" Shard: layers {shard_start}-{shard_end} of {assigned_model}", flush=True)
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# 4. Download shard
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