Garden's Almanac of Matter Models

ANI

June 2020

Checkpoint Params Polaris Sophia Perlmutter Delta Frontier Della
ani-2x
ani-1ccx
ani-1x
verified, last 30 days installed, not recently verified not installed

No cluster has installed any checkpoint of this model yet.


Running this model
1# from a job or interactive session on a supported cluster:
2from rootstock import RootstockCalculator
3
4with RootstockCalculator(
5 cluster=YOUR_CLUSTER_ID, # eg, "sophia", "perlmutter"
6 checkpoint="ani-2x",
7 device="cuda",
8) as calc:
9 # model is now running in subprocess on compute node
10 atoms.calc = calc
11 atoms.get_potential_energy()

Environments

Rootstock runs each model family inside an isolated Python environment defined by a single file. This environment file includes the specific dependencies needed, plus a setup() function that loads the model and returns an ASE calculator. These files are usually almost identical for a given model family, but because of cluster-specific quirks (eg, an old CUDA driver) the dependencies and setup code can vary a bit.

ani_env.py
1# /// script
2# requires-python = ">=3.10"
3# dependencies = [
4# "torchani>=2.2",
5# "ase>=3.22",
6# "torch>=2.0",
7# ]
8# ///
9"""
10ANI-2x environment for Rootstock.
11
12ANI-2x is a neural network potential for organic molecules containing
13H, C, N, O, F, S, Cl. It is not a universal potential — do not use it
14for inorganic or periodic systems.
15
16Models:
17 - "ANI2x": ANI-2x ensemble (default, 8 networks)
18 - "ANI1ccx": ANI-1ccx, trained on CCSD(T)/CBS data (H, C, N, O only)
19 - "ANI1x": ANI-1x (H, C, N, O only)
20"""
21
22CHECKPOINTS = {
23 "ani-2x": "ANI2x",
24 "ani-1ccx": "ANI1ccx",
25 "ani-1x": "ANI1x",
26}
27
28
29def setup(checkpoint: str, device: str = "cuda"):
30 """
31 Load an ANI calculator.
32
33 Args:
34 checkpoint: Canonical checkpoint id, must be a key of CHECKPOINTS.
35 device: PyTorch device string (e.g., "cuda", "cpu").
36
37 Returns:
38 ASE-compatible calculator.
39 """
40 import torchani
41
42 model_map = {
43 "ANI2x": torchani.models.ANI2x,
44 "ANI1ccx": torchani.models.ANI1ccx,
45 "ANI1x": torchani.models.ANI1x,
46 }
47 model = CHECKPOINTS[checkpoint]
48
49 return model_map[model](periodic_table_index=True).to(device).ase()
50

Built on Polaris: 2026-05-12

Couldn't load the current environments from Rootstock.


References
  1. Devereux, Christian, Smith, Justin S., Huddleston, Kate K., Barros, Kipton, Zubatyuk, Roman, Isayev, Olexandr, Roitberg, Adrian E., Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens, Journal of Chemical Theory and Computation, 2020.