76 lines
1.7 KiB
Go
76 lines
1.7 KiB
Go
package main
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import (
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"fmt"
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"log"
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"runtime"
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"git.andr3h3nriqu3s.com/andr3/gotch"
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"git.andr3h3nriqu3s.com/andr3/gotch/nn"
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"git.andr3h3nriqu3s.com/andr3/gotch/ts"
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"git.andr3h3nriqu3s.com/andr3/gotch/vision"
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)
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const (
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ImageDimNN int64 = 784
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HiddenNodesNN int64 = 128
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LabelNN int64 = 10
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epochsNN = 200
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LrNN = 1e-3
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)
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var MnistDirNN string = fmt.Sprintf("%s/%s", gotch.CachedDir, "mnist")
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var l nn.Linear
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func netInit(vs *nn.Path) ts.Module {
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n := nn.Seq()
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n.Add(nn.NewLinear(vs, ImageDimNN, HiddenNodesNN, nn.DefaultLinearConfig()))
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n.AddFn(nn.NewFunc(func(xs *ts.Tensor) *ts.Tensor {
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return xs.MustRelu(false)
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}))
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n.Add(nn.NewLinear(vs, HiddenNodesNN, LabelNN, nn.DefaultLinearConfig()))
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return n
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}
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func train(trainX, trainY, testX, testY *ts.Tensor, m ts.Module, opt *nn.Optimizer, epoch int) {
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logits := m.Forward(trainX)
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loss := logits.CrossEntropyForLogits(trainY)
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opt.BackwardStep(loss)
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testLogits := m.Forward(testX)
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testAccuracy := testLogits.AccuracyForLogits(testY)
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accuracy := testAccuracy.Float64Values()[0] * 100
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lossVal := loss.Float64Values()[0]
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fmt.Printf("Epoch: %v \t Loss: %.3f \t Test accuracy: %.2f%%\n", epoch, lossVal, accuracy)
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runtime.GC()
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}
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func runNN() {
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var ds *vision.Dataset
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ds = vision.LoadMNISTDir(MnistDirNN)
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vs := nn.NewVarStore(device)
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net := netInit(vs.Root())
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opt, err := nn.DefaultAdamConfig().Build(vs, LrNN)
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if err != nil {
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log.Fatal(err)
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}
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trainImages := ds.TrainImages.MustTo(device, true)
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trainLabels := ds.TrainLabels.MustTo(device, true)
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testImages := ds.TestImages.MustTo(device, true)
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testLabels := ds.TestLabels.MustTo(device, true)
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for epoch := 0; epoch < epochsNN; epoch++ {
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train(trainImages, trainLabels, testImages, testLabels, net, opt, epoch)
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}
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}
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