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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 gradients
- import (
- "math"
- )
- func sign(v float64) float64 {
- if v == 0 {
- return 0
- }
- // fmt.Printf("%v / math.Abs(%v) = %v\n", v, math.Abs(v), v/math.Abs(v))
- return v / math.Abs(v)
- }
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