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from pathlib import Path
import yaml
from huggingface_hub import HfApi, HfFileSystem, hf_hub_download
# from mlip_arena.models import MLIP
# from mlip_arena.models import REGISTRY as MODEL_REGISTRY
try:
from .elasticity import run as ELASTICITY
from .eos import run as EOS
from .md import run as MD
from .neb import run as NEB
from .neb import run_from_endpoints as NEB_FROM_ENDPOINTS
from .optimize import run as OPT
from .phonon import run as PHONON
__all__ = ["OPT", "EOS", "MD", "NEB", "NEB_FROM_ENDPOINTS", "ELASTICITY", "PHONON"]
except ImportError:
pass
with open(Path(__file__).parent / "registry.yaml", encoding="utf-8") as f:
REGISTRY = yaml.safe_load(f)
# class Task:
# def __init__(self):
# self.name: str = self.__class__.__name__ # display name on the leaderboard
# def run_local(self, model: MLIP):
# """Run the task using the given model and return the results."""
# raise NotImplementedError
# def run_hf(self, model: MLIP):
# """Run the task using the given model and return the results."""
# raise NotImplementedError
# # Calcualte evaluation metrics and postprocessed data
# api = HfApi()
# api.upload_file(
# path_or_fileobj="results.json",
# path_in_repo=f"{self.__class__.__name__}/{model.__class__.__name__}/results.json", # Upload to a specific folder
# repo_id="atomind/mlip-arena",
# repo_type="dataset",
# )
# def run_nersc(self, model: MLIP):
# """Run the task using the given model and return the results."""
# raise NotImplementedError
# def get_results(self):
# """Get the results from the task."""
# # fs = HfFileSystem()
# # files = fs.glob(f"datasets/atomind/mlip-arena/{self.__class__.__name__}/*/*.json")
# for model, metadata in MODEL_REGISTRY.items():
# results = hf_hub_download(
# repo_id="atomind/mlip-arena",
# filename="results.json",
# subfolder=f"{self.__class__.__name__}/{model}",
# repo_type="dataset",
# revision=None,
# )
# return results
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