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- /*
- * MIT License
- *
- * Copyright (c) 2019 Alexey Edelev <semlanik@gmail.com>
- *
- * 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
- }
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