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from __future__ import annotations
from pathlib import Path
import yaml
import requests
from orb_models.forcefield import pretrained
from orb_models.forcefield.calculator import ORBCalculator
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 ORB(ORBCalculator):
def __init__(
self,
checkpoint=REGISTRY["ORB"]["checkpoint"],
device=None,
**kwargs,
):
device = device or get_freer_device()
cache_dir = Path.home() / ".cache" / "orb"
cache_dir.mkdir(parents=True, exist_ok=True)
ckpt_path = cache_dir / checkpoint
url = f"https://storage.googleapis.com/orbitalmaterials-public-models/forcefields/{checkpoint}"
if not ckpt_path.exists():
print(f"Downloading ORB model from {url} to {ckpt_path}...")
try:
response = requests.get(url, stream=True, timeout=120)
response.raise_for_status()
with open(ckpt_path, "wb") as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
print("Download completed.")
except requests.exceptions.RequestException as e:
raise RuntimeError("Failed to download ORB model.") from e
orbff = pretrained.orb_v1(weights_path=ckpt_path, device=device)
super().__init__(orbff, device=device, **kwargs)
class ORBv2(ORBCalculator):
def __init__(
self,
checkpoint=REGISTRY["ORBv2"]["checkpoint"],
device=None,
**kwargs,
):
device = device or get_freer_device()
cache_dir = Path.home() / ".cache" / "orb"
cache_dir.mkdir(parents=True, exist_ok=True)
ckpt_path = cache_dir / checkpoint
url = f"https://storage.googleapis.com/orbitalmaterials-public-models/forcefields/{checkpoint}"
if not ckpt_path.exists():
print(f"Downloading ORB model from {url} to {ckpt_path}...")
try:
response = requests.get(url, stream=True, timeout=120)
response.raise_for_status()
with open(ckpt_path, "wb") as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
print("Download completed.")
except requests.exceptions.RequestException as e:
raise RuntimeError("Failed to download ORB model.") from e
orbff = pretrained.orb_v2(weights_path=ckpt_path, device=device)
super().__init__(orbff, device=device, **kwargs)
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