dopt.online

This package contains implementations of common online optimisation algorithms, with a particular bias towards those commonly used in large scale machine learning/deep learning.

Modules

adam module dopt.online.adam: Contains an implementation of ADAM that relies on automatic differentiation
amsgrad module dopt.online.amsgrad: Contains an implementation of AMSGrad that relies on automatic differentiation
sgd module dopt.online.sgd: Contains an implementation of stochastic gradient descent that relies on automatic differentiation

Public Imports

dopt.online.adam public import dopt.online.adam;

dopt.online.amsgrad public import dopt.online.amsgrad;

dopt.online.sgd public import dopt.online.sgd;

Members

Aliases

Projection alias Projection = Operation delegate(Operation): Used for performing projected gradient descent.
Updater alias Updater = DeviceBuffer[] delegate(DeviceBuffer[Operation] args): A delegate that can be used to perform the update step for an online optimisation algorithm.

Meta

Source

See Source File

Authors

Henry Gouk

dopt modules