48 lines
1011 B
Go
48 lines
1011 B
Go
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// Copyright (c) 2026 Petr Balvín <opensource@petrbalvin.org> (https://petrbalvin.org)
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// SPDX-License-Identifier: MIT
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package grad
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import (
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"math"
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"sourcedock.dev/petrbalvin/tensor/internal/core"
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)
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// numericGrad estimates the gradient of a scalar function at a by
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// central differences, the reference the analytic backward is checked
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// against.
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func numericGrad(f func(a *core.Array) float64, a *core.Array) []float64 {
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n := a.Len()
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out := make([]float64, n)
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for i := range n {
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hi := 1e-6
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up := cloneFlat(a)
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down := cloneFlat(a)
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up[i] += hi
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down[i] -= hi
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au, _ := core.FromFloats(up, a.Shape()...)
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ad, _ := core.FromFloats(down, a.Shape()...)
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out[i] = (f(au) - f(ad)) / (2 * hi)
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}
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return out
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}
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func cloneFlat(a *core.Array) []float64 {
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out := make([]float64, a.Len())
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for i := range a.Len() {
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out[i] = a.FloatAt(i)
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}
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return out
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}
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func maxAbsDiff(a, b []float64) float64 {
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m := 0.0
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for i := range a {
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if d := math.Abs(a[i] - b[i]); d > m {
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m = d
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}
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}
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return m
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}
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