ConvolutionModule

class openff.nagl.nn.ConvolutionModule(n_input_features: int, hidden_feature_sizes: List[int], architecture: str = 'SAGEConv', layer_activation_functions: List[ActivationFunction] | None = None, layer_dropout: List[float] | None = None, layer_aggregator_types: List[str] | None = None)[source]

Bases: Module

Methods

copy

forward

Defines the computation performed at every call.

from_config

Attributes

training

copy(copy_weights: bool = False)[source]
forward(molecule: DGLMolecule | DGLMoleculeBatch)[source]

Defines 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.

classmethod from_config(convolution_config, n_input_features: int)[source]