mlcolvar.core.transform.tools.SwitchingFunctions

class mlcolvar.core.transform.tools.SwitchingFunctions(in_features: int, name: str, cutoff: float, dmax: float = None, options: dict = None)

Bases: Transform

Common switching functions

__init__(in_features: int, name: str, cutoff: float, dmax: float = None, options: dict = None)

Transform class options.

Parameters:

• in_features (int) – Number of inputs of the transform

• out_features (int) – Number of outputs of the transform

Methods

Fermi_switch(x, cutoff[, q, prefactor_cutoff])
Rational_switch(x, cutoff[, n, m, eps, ...])
__init__(in_features, name, cutoff[, dmax, ...])	Transform class options.
forward(x)	Define the computation performed at every call.

forward(x: Tensor)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

setup_from_datamodule(datamodule)

Initialize parameters based on pytorch lighting datamodule.

Attributes

SWITCH_FUNCS
T_destination
call_super_init
dump_patches
training