Datasets:
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cc7d399 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | """Runtime cache configuration for local and cloud runs."""
from __future__ import annotations
import os
from pathlib import Path
def _choose_cache_root(project_root: Path) -> Path:
explicit = os.environ.get("SFR_CACHE_ROOT")
if explicit:
return Path(explicit).expanduser()
workspace = Path("/workspace")
if workspace.exists() and os.access(workspace, os.W_OK):
return workspace / ".cache"
return project_root / ".cache"
def configure_runtime_cache(project_root: Path) -> Path:
"""Route Hugging Face, evaluate, and temp files to a writable cache root."""
cache_root = _choose_cache_root(project_root)
hf_root = cache_root / "huggingface"
tmp_root = cache_root / "tmp"
defaults = {
"HF_HOME": hf_root,
"HF_DATASETS_CACHE": hf_root / "datasets",
"HUGGINGFACE_HUB_CACHE": hf_root / "hub",
"TRANSFORMERS_CACHE": hf_root / "hub",
"HF_EVALUATE_CACHE": hf_root / "evaluate",
"HF_METRICS_CACHE": hf_root / "metrics",
"HF_MODULES_CACHE": hf_root / "modules",
"HF_DATASETS_DOWNLOADED_EVALUATE_PATH": hf_root / "evaluate" / "downloads",
"HF_DATASETS_EXTRACTED_EVALUATE_PATH": hf_root / "evaluate" / "extracted",
"MPLCONFIGDIR": cache_root / "matplotlib",
"NUMBA_CACHE_DIR": cache_root / "numba",
"TMPDIR": tmp_root,
}
for var, path in defaults.items():
os.environ.setdefault(var, str(path))
for var in defaults:
Path(os.environ[var]).mkdir(parents=True, exist_ok=True)
return cache_root
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