Anyang Peng
Feat: add DeepMD pretrain model (#12)
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from __future__ import annotations
from pathlib import Path
import yaml
import requests
from deepmd.calculator import DP as DPCalculator
from mlip_arena.models.utils import get_freer_device
with open(Path(__file__).parents[1] / "registry.yaml", encoding="utf-8") as f:
REGISTRY = yaml.safe_load(f)
class DeepMD(DPCalculator):
def __init__(
self,
checkpoint=REGISTRY["DeepMD"]["checkpoint"],
device=None,
**kwargs,
):
device = device or get_freer_device()
cache_dir = Path.home() / ".cache" / "deepmd"
cache_dir.mkdir(parents=True, exist_ok=True)
model_path = cache_dir / checkpoint
url = "https://bohrium-api.dp.tech/ds-dl/mlip-arena-tfpk-v1.zip"
if not model_path.exists():
import zipfile
print(f"Downloading DeepMD model from {url} to {model_path}...")
try:
response = requests.get(url, stream=True, timeout=120)
response.raise_for_status()
with open(cache_dir/"temp.zip", "wb") as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
print("Download completed.")
with zipfile.ZipFile(cache_dir/"temp.zip", "r") as zip_ref:
zip_ref.extractall(cache_dir)
print("Unzip completed.")
except requests.exceptions.RequestException as e:
raise RuntimeError("Failed to download DeepMD model.") from e
super().__init__(model_path, device=device, **kwargs)