Files
hao-ai-lab-FastVideo/fastvideo/eval/models.py

96 lines
3.3 KiB
Python

"""Model checkpoint resolution and caching for eval metrics.
Single public function — :func:`ensure_checkpoint` — that hands a metric
a local path to its weights, downloading on miss. Three source kinds:
* an existing local path → returned as-is;
* an HTTP(S) URL → downloaded to ``get_cache_dir() / name`` via
``huggingface_hub.http_get`` (resume + retries built in);
* an HF repo id (``"org/repo"``) → :func:`huggingface_hub.hf_hub_download`
if *filename* is given, else :func:`huggingface_hub.snapshot_download`.
*name* is ignored in HF mode — HF manages its own cache key under
``~/.cache/huggingface/hub``.
All download paths are filelock-safe (cooperative across threads,
processes, and SLURM ranks) via :func:`fastvideo.utils.get_lock`.
"""
from __future__ import annotations
import os
from pathlib import Path
from fastvideo import envs
from fastvideo.utils import get_lock
def get_cache_dir() -> Path:
"""Eval cache root.
Layout::
get_cache_dir() / models / ← URL-fetched checkpoints (LAION head,
AMT, GRiT, …)
get_cache_dir() / torch / ← redirected ``TORCH_HOME`` (DINO etc.)
get_cache_dir() / clip / ← passed as ``download_root`` to
``clip.load(...)`` callsites
~/.cache/huggingface/hub / ← left at HF's default; widely shared
with other ML projects
Override priority: ``FASTVIDEO_EVAL_CACHE`` > ``${FASTVIDEO_CACHE_ROOT}/eval``.
Metric authors writing new code: when wrapping a third-party loader
that has its own cache convention (CLIP's ``download_root``, pyiqa's
``cache_dir``, etc.), pass ``str(get_cache_dir() / "<library>")`` so
users get a single ``FASTVIDEO_EVAL_CACHE`` knob to redirect them all.
"""
return Path(envs.FASTVIDEO_EVAL_CACHE.get())
def ensure_checkpoint(
name: str,
source: str,
filename: str | None = None,
) -> str:
"""Resolve a model checkpoint path, downloading on miss.
See module docstring for the full source contract. *name* is used
only as the local cache filename for URL sources; ignored otherwise.
"""
if os.path.exists(source):
return source
if source.startswith(("http://", "https://")):
return _ensure_url(name, source)
if "/" in source:
return _ensure_hf(source, filename)
raise ValueError(f"Cannot resolve checkpoint: source {source!r} is neither a "
"path, URL, nor HF repo id")
def _ensure_url(name: str, url: str) -> str:
local = get_cache_dir() / "models" / name
if local.exists():
return str(local)
local.parent.mkdir(parents=True, exist_ok=True)
with get_lock(url):
if local.exists(): # racing process won; reuse its result
return str(local)
from huggingface_hub.file_download import http_get
tmp = local.with_suffix(local.suffix + ".tmp")
with open(tmp, "wb") as f:
http_get(url, f)
tmp.rename(local)
return str(local)
def _ensure_hf(repo_id: str, filename: str | None) -> str:
from huggingface_hub import hf_hub_download, snapshot_download
with get_lock(f"{repo_id}/{filename or '*'}"):
if filename:
return hf_hub_download(repo_id=repo_id, filename=filename)
return snapshot_download(repo_id=repo_id)