torchani#

The TorchANI neural network potential library main namespace

Most of the functions and classes of the library are accessible from their specific modules. For convenience, some useful classes are accessible also from here. These are:

Functions

single_point

Calculate properties for a batch of molecules

Modules

`neighbors`	Modular neighborlists to improve scaling for large systems
`aev`	Atomic Environment Vectors (AEVs) are TorchANI's name for local atomic features, calculated from the local chemical environment of each atom.
`nn`	Classes that represent atomic (and groups of element-specific) neural networks
`grad`	Wrapper functions that make use of `torch.autograd`
`models`	Provides access to all published ANI models.
`potentials`	Callable objects that can be attached to TorchANI models.
`cutoffs`	Collection of Cutoff functions
`datasets`	Functions and classes for creating batched and map-like datasets.
`transforms`	Composable functions that modify to properties when training or batching a dataset.
`io`	Convenience functions for reading and writing molecules in ".xyz" format
`electro`	Utilities for working with charged systems
`arch`	Construction of ANI-style models and definition of their architecture
`constants`	Atomic constants, and Density Functional constants
`utils`	Misc utilities used throughout the code
`units`	Unit conversion factors used in TorchANI
`sae`	Simple module that calculates a "1-body atomic potential"
`sae_estimation`	Functions to calculate self atomic energies (SAEs) via linear regression.
`cli`	Contains the TorchANI CLI entrypoints.
`paths`	Locations used by TorchANI to cache various resources
`ase`	Calculator subclass, used for interfacing with the ASE library
`annotations`	Type aliases; common type annotations used throughout the code
`neurochem`	This module is part of the Legacy API of TorchANI 2 and should not be used in new code.
`legacy_data`	This module is part of the Legacy API of TorchANI 2 and should not be used in new code.