/* * MIT License * * Copyright (c) 2019 Alexey Edelev * * This file is part of NeuralNetwork project https://git.semlanik.org/semlanik/NeuralNetwork * * Permission is hereby granted, free of charge, to any person obtaining a copy of this * software and associated documentation files (the "Software"), to deal in the Software * without restriction, including without limitation the rights to use, copy, modify, * merge, publish, distribute, sublicense, and/or sell copies of the Software, and * to permit persons to whom the Software is furnished to do so, subject to the following * conditions: * * The above copyright notice and this permission notice shall be included in all copies * or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, * INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR * PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE * FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR * OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER * DEALINGS IN THE SOFTWARE. */ package neuralnetwork import ( mat "gonum.org/v1/gonum/mat" ) const ( BiasGradient = iota WeightGradient = iota ) // Interface factory function type that specifies producer interface for gradient descent objects type GradientDescentInitializer func(nn *NeuralNetwork, layer, gradientType int) interface{} // Online gradient descent interface. Is used by online training mechanism type OnlineGradientDescent interface { ApplyDelta(m mat.Matrix, gradient mat.Matrix) *mat.Dense } // Batch gradient descent interface. Is used by batch training mechanism type BatchGradientDescent interface { ApplyDelta(m mat.Matrix) *mat.Dense AccumGradients(gradient mat.Matrix) Gradients() *mat.Dense }