A MoleculeDataset contains a list of molecules and their associated features and targets.

A StandardScaler normalizes a dataset. When fit on a dataset, the StandardScaler learns the mean and standard deviation across the 0th axis.

Light ontology projection tailored to OWL2Vec PARAMETERS: 0. urionto: URI of the ontology to project 1. reasoner Reasoner.STRUC

Project random walks or subtrees in graphs into embeddings, suited for classification. Parameters ---------- vector_size: int (defaul

Identity PyTorch module.

A MoleculeDatapoint contains a single molecule and its associated features and targets.

A MoleculeModel is a model which contains a message passing network following by feed-forward layers.

classdocs

This class manages the most common ontology annotations

A BatchMolGraph represents the graph structure and featurization of a batch of molecules. A BatchMolGraph contains the attributes of a MolGr

An :class:`MPN` is a wrapper around :class:`MPNEncoder` which featurizes input as needed.

An :class:`MPNEncoder` is a message passing neural network for encoding a molecule.

A MolGraph represents the graph structure and featurization of a single molecule. A MolGraph computes the following attributes: - smiles

Noam learning rate scheduler with piecewise linear increase and exponential decay. The learning rate increases linearly from init_lr to max_

Calculates the precision and recall. - `update` must receive output of the form `(y_pred, y)`. - `y_pred` must be in the following shape

Calculates the categorical accuracy. - `update` must receive output of the form `(y_pred, y)`. - `y_pred` must be in the following shape

Abstract Base class (ABC) for all Metrics. Taken from https://github.com/pytorch/ignite/metrics/metric.py and modify a bit. Often

Define a vocabulary object that will be used to numericalize a field. Attributes: token2id: A collections.defaultdict instance mappin