i-PI¶

Official website	How is metatensor supported?
https://ipi-code.org/	In the official version

Supported model outputs¶

Only the energy output is supported, and used to run path integral simulations, incorporating quantum nuclear effects in the statistical sampling.

How to install the code¶

The metatensor interface is part of i-PI since version 3.0. Please refer to i-PI documentation about how to install it.

How to use the code¶

Note

Here we assume you already have an exported model that you want to use in your simulations. Please see this tutorial to learn how to manually create and export a model; or use a tool like metatrain to create a model based on existing architectures and your own dataset.

The metatensor interface in i-PI provides a custom i-PI client that can be used in combination with an i-PI server to run simulations. This client is managed with the i-pi-driver-py command.

# minimal version
i-pi-driver-py -m metatensor -o template.xyz,model.pt

# all possible options
i-pi-driver-py -m metatensor -o template.xyz,model.pt,device=cpu,extensions=path/to/extensions,check_consistency=False

The minimal options to give to the metatensor client are the path to a template structure for the simulated system (template.xyz in the example above) and the path to the metatensor model (model.pt above). The template structure must be a file that ASE can read. The code only uses it to get the atomic types (assumed to be the atomic numbers) matching all particles in the system.

The following options can also be specified using key=value syntax:

extensions: the path to a folder containing TorchScript extensions. We will try to load any extension the model requires from there first;
device: torch device to use to execute the model. Typical values would be cpu, cuda, cuda:2, etc. By default, the code will find the best device for the model that is available on the current computer;
check_consistency: whether to run some additional internal checks. Set this to True if you are seeing a strange behavior for a given model or when developing a new model.