File size: 2,064 Bytes
b78a213 | 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 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | """
This script provides the functionality to generate metadata.npz files necessary
for load_balancing the DataLoader.
"""
import argparse
import multiprocessing as mp
import os
import warnings
import numpy as np
from tqdm import tqdm
from ocpmodels.datasets import SinglePointLmdbDataset, TrajectoryLmdbDataset
def get_data(index):
data = dataset[index]
natoms = data.natoms
neighbors = None
if hasattr(data, "edge_index"):
neighbors = data.edge_index.shape[1]
return index, natoms, neighbors
def main(args):
path = args.data_path
global dataset
if os.path.isdir(path):
dataset = TrajectoryLmdbDataset({"src": path})
outpath = os.path.join(path, "metadata.npz")
elif os.path.isfile(path):
dataset = SinglePointLmdbDataset({"src": path})
outpath = os.path.join(os.path.dirname(path), "metadata.npz")
indices = range(len(dataset))
pool = mp.Pool(args.num_workers)
outputs = list(tqdm(pool.imap(get_data, indices), total=len(indices)))
indices = []
natoms = []
neighbors = []
for i in outputs:
indices.append(i[0])
natoms.append(i[1])
neighbors.append(i[2])
_sort = np.argsort(indices)
sorted_natoms = np.array(natoms, dtype=np.int32)[_sort]
if None in neighbors:
warnings.warn(
f"edge_index information not found, {outpath} only supports atom-wise load balancing."
)
np.savez(outpath, natoms=sorted_natoms)
else:
sorted_neighbors = np.array(neighbors, dtype=np.int32)[_sort]
np.savez(outpath, natoms=sorted_natoms, neighbors=sorted_neighbors)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--data-path",
required=True,
type=str,
help="Path to S2EF directory or IS2R* .lmdb file",
)
parser.add_argument(
"--num-workers",
default=1,
type=int,
help="Num of workers to parallelize across",
)
args = parser.parse_args()
main(args)
|