Module model

This module provides the scaffolding for creating models and layers in a neural network.

Modules

config

layout

model_params

trainer

Structs

ModelFeatures

The ModelFeatures provides a common way of defining the layout of a model. This is used to define the number of input features, the number of hidden layers, the number of hidden features, and the number of output features.

ModelParamsBase

This object is an abstraction over the parameters of a deep neural network model. This is done to isolate the necessary parameters from the specific logic within a model allowing us to easily create additional stores for tracking velocities, gradients, and other metrics we may need.

StandardModelConfig

Trainer

Traits

DeepNeuralNetwork

The DeepNeuralNetwork trait is a specialization of the Model trait that provides additional functionality for deep neural networks. This trait is

Model

The base interface for all models; each model provides access to a configuration object defined as the associated type Config. The configuration object is used to provide hyperparameters and other control related parameters. In addition, the model’s layout is defined by the features method which aptly returns a copy of its ModelFeatures object.

ModelExt

ModelLayout

ModelTrainer

Type Aliases

ModelParams