55 lines
1.5 KiB
Go
55 lines
1.5 KiB
Go
package main
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import (
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"fmt"
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"github.com/sugarme/gotch"
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ts "github.com/sugarme/gotch/tensor"
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"github.com/sugarme/gotch/vision"
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)
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const (
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ImageDim int64 = 784
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Label int64 = 10
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MnistDir string = "../../data/mnist"
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epochs = 200
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)
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func runLinear() {
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var ds *vision.Dataset
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ds = vision.LoadMNISTDir(MnistDir)
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device := gotch.CPU
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dtype := gotch.Float
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ws := ts.MustZeros([]int64{ImageDim, Label}, dtype, device).MustSetRequiresGrad(true, false)
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bs := ts.MustZeros([]int64{Label}, dtype, device).MustSetRequiresGrad(true, false)
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for epoch := 0; epoch < epochs; epoch++ {
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weight := ts.NewTensor()
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reduction := int64(1) // Mean of loss
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ignoreIndex := int64(-100)
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logits := ds.TrainImages.MustMm(ws, false).MustAdd(bs, true)
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loss := logits.MustLogSoftmax(-1, dtype, true).MustNllLoss(ds.TrainLabels, weight, reduction, ignoreIndex, true)
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ws.ZeroGrad()
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bs.ZeroGrad()
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loss.MustBackward()
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ts.NoGrad(func() {
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ws.Add_(ws.MustGrad(false).MustMul1(ts.FloatScalar(-1.0), true))
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bs.Add_(bs.MustGrad(false).MustMul1(ts.FloatScalar(-1.0), true))
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})
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testLogits := ds.TestImages.MustMm(ws, false).MustAdd(bs, true)
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testAccuracy := testLogits.MustArgmax([]int64{-1}, false, true).MustEq1(ds.TestLabels, true).MustTotype(gotch.Float, true).MustMean(gotch.Float, true).MustView([]int64{-1}, true).MustFloat64Value([]int64{0})
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fmt.Printf("Epoch: %v - Loss: %.3f - Test accuracy: %.2f%%\n", epoch, loss.Float64Values()[0], testAccuracy*100)
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loss.MustDrop()
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}
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}
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