71 lines
1.4 KiB
Go
71 lines
1.4 KiB
Go
package main
|
|
|
|
import (
|
|
"fmt"
|
|
"log"
|
|
|
|
"github.com/sugarme/gotch"
|
|
"github.com/sugarme/gotch/nn"
|
|
ts "github.com/sugarme/gotch/tensor"
|
|
"github.com/sugarme/gotch/vision"
|
|
)
|
|
|
|
const (
|
|
ImageDimNN int64 = 784
|
|
HiddenNodesNN int64 = 128
|
|
LabelNN int64 = 10
|
|
MnistDirNN string = "../../data/mnist"
|
|
|
|
epochsNN = 50
|
|
batchSizeNN = 256
|
|
|
|
LrNN = 1e-3
|
|
)
|
|
|
|
var l nn.Linear
|
|
|
|
func netInit(vs nn.Path) ts.Module {
|
|
n := nn.Seq()
|
|
|
|
l = nn.NewLinear(vs.Sub("layer1"), ImageDimNN, HiddenNodesNN, nn.DefaultLinearConfig())
|
|
|
|
n.Add(l)
|
|
|
|
n.AddFn(nn.ForwardWith(func(xs ts.Tensor) ts.Tensor {
|
|
return xs.MustRelu()
|
|
}))
|
|
|
|
n.Add(nn.NewLinear(vs, HiddenNodesNN, LabelNN, nn.DefaultLinearConfig()))
|
|
|
|
return n
|
|
}
|
|
|
|
func train(trainX, trainY, testX, testY ts.Tensor, m ts.Module, opt nn.Optimizer, epoch int) {
|
|
loss := m.Forward(trainX).CrossEntropyForLogits(trainY)
|
|
|
|
opt.BackwardStep(loss)
|
|
|
|
testAccuracy := m.Forward(testX).AccuracyForLogits(testY).Values()[0]
|
|
fmt.Printf("Epoch: %v \t Loss: %.3f \t Test accuracy: %.2f%%\n", epoch, loss.Values()[0], testAccuracy*100)
|
|
|
|
}
|
|
|
|
func runNN() {
|
|
|
|
var ds vision.Dataset
|
|
ds = vision.LoadMNISTDir(MnistDirNN)
|
|
vs := nn.NewVarStore(gotch.CPU)
|
|
net := netInit(vs.Root())
|
|
opt, err := nn.DefaultAdamConfig().Build(vs, LrNN)
|
|
if err != nil {
|
|
log.Fatal(err)
|
|
}
|
|
|
|
for epoch := 0; epoch < epochsNN; epoch++ {
|
|
|
|
train(ds.TrainImages, ds.TrainLabels, ds.TestImages, ds.TestLabels, net, opt, epoch)
|
|
|
|
}
|
|
|
|
}
|