Glossary

Terms commonly used in FastAI.jl.

Type abbreviations

In many docstrings, generic types are abbreviated with the following symbols. Many of these refer to a learning method; the context should make clear which method is meant.

• DC{T}: A data container of type T, meaning a type that implements the data container interface getobs and nobs where getobs : (DC{T}, Int) -> Int, that is, each observation is of type T.
• I: Type of the unprocessed input in the context of a method.
• T: Type of the target variable.
• X: Type of the processed input. This is fed into a model, though it may be batched beforehand. Xs represents a batch of processed inputs.
• Y: Type of the model output. Ys represents a batch of model outputs.
• model/M: A learnable mapping M : (X,) -> Y or M : (Xs,) -> Ys. It predicts an encoded target from an encoded input. The learnable part of a learning method.

Some examples of these in use:

• LearningTask represents the task of learning to predict T from I.
• LearningMethod is a concrete approach to learning to predict T from I by using the encoded representations X and Y.
• encodeinput : (method, context, I) -> X encodes an input so that a prediction can be made by a model.
• A task dataset is a DC{(I, T)}, i.e. a data container where each observation is a 2-tuple of an input and a target.

Definitions

Data container

A data structure that is used to load a number of data observations separately and lazily. It defines how many observations it holds with nobs and how to load a single observation with getobs.

Learning method

An instance of DLPipelines.LearningMethod. A concrete approach to solving a learning task. Encapsulates the logic and configuration for processing data to train a model and make predictions.

See the DLPipelines.jl documentation for more information.

Learning task

An abstract subtype of DLPipelines.LearningTask that represents the problem of learning a mapping from some input type I to a target type T. For example, ImageClassificationTask represents the task of learning to map an image to a class. See learning method

Task data container / dataset

DC{(I, T)}. A data container containing pairs of inputs and targets. Used in methoddataset, methoddataloaders and evaluate.