ExponentialLRDecay Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.StandardTrainers.dll

Package:

Microsoft.ML v3.0.1

This class implements Exponential Learning rate decay. Implemented from the tensorflow documentation. Source: https://www.tensorflow.org/api_docs/python/tf/compat/v1/train/exponential_decay Default values and implementation of learning rate is from Tensorflow Slim model tests. Source : https://github.com/tensorflow/models/blob/master/research/slim/train_image_classifier.py

public sealed class ExponentialLRDecay : Microsoft.ML.Trainers.LearningRateScheduler

type ExponentialLRDecay = class
    inherit LearningRateScheduler

Public NotInheritable Class ExponentialLRDecay
Inherits LearningRateScheduler

Inheritance

Object

LearningRateScheduler

ExponentialLRDecay

Constructors

ExponentialLRDecay(Single, Single, Single, Boolean)

This contructor initializes intial learning rate, number epochs per decay, decay rate and the staircase option. The defaults are taken from Tensorflow Slim.

Fields

DecayRate	Learning rate decay factor.
DecaySteps	Number of decay steps
GlobalStep	The number of batches seen by the graph so far.
LearningRate	Initial learning rate.
NumEpochsPerDecay	Number of epochs after which learning rate decays.
Staircase	If Staircase is True the learning rate decays at discrete intervals and the decayed learning rate follows a staircase function.