109 lines
2.1 KiB
Go
109 lines
2.1 KiB
Go
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package main
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import (
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"git.andr3h3nriqu3s.com/andr3/gotch"
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dbtypes "git.andr3h3nriqu3s.com/andr3/fyp/logic/db_types"
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"git.andr3h3nriqu3s.com/andr3/fyp/logic/models/train/torch"
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my_nn "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/train/torch/nn"
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torch "git.andr3h3nriqu3s.com/andr3/gotch/ts"
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"github.com/charmbracelet/log"
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)
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func main_() {
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log.Info("Hello world")
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m := train.BuildModel([]*dbtypes.Layer{
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&dbtypes.Layer{
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LayerType: dbtypes.LAYER_INPUT,
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Shape: "[ 2, 3, 3 ]",
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},
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&dbtypes.Layer{
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LayerType: dbtypes.LAYER_FLATTEN,
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},
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&dbtypes.Layer{
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LayerType: dbtypes.LAYER_DENSE,
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Shape: "[ 10 ]",
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},
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}, 0, true)
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var err error
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d := gotch.CudaIfAvailable()
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log.Info("device", "d", d)
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m.To(d)
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opt, err := my_nn.DefaultAdamConfig().Build(m.Vs, 0.001)
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if err != nil {
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return
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}
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ones := torch.MustOnes([]int64{1, 2, 3, 3}, gotch.Float, d)
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ones = ones.MustSetRequiresGrad(true, true)
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ones.RetainGrad(false)
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res := m.ForwardT(ones, true)
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res = res.MustSetRequiresGrad(true, true)
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res.RetainGrad(false)
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outs := torch.MustOnes([]int64{1, 10}, gotch.Float, d)
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outs = outs.MustSetRequiresGrad(true, true)
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outs.RetainsGrad(false)
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loss, err := res.BinaryCrossEntropyWithLogits(outs, &torch.Tensor{}, &torch.Tensor{}, 1, false)
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if err != nil {
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return
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}
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loss = loss.MustSetRequiresGrad(true, false)
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opt.ZeroGrad()
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log.Info("loss", "loss", loss.Float64Values())
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loss.MustBackward()
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opt.Step()
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// log.Info(mean.MustGrad(false).Float64Values())
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log.Info(res.MustGrad(false).Float64Values())
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log.Info(ones.MustGrad(false).Float64Values())
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log.Info(outs.MustGrad(false).Float64Values())
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vars := m.Vs.Variables()
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for k, v := range vars {
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log.Info("[grad check]", "k", k)
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var grad *torch.Tensor
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grad, err = v.Grad(false)
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if err != nil {
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log.Error(err)
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return
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}
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grad, err = grad.Abs(false)
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if err != nil {
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log.Error(err)
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return
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}
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grad, err = grad.Max(false)
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if err != nil {
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log.Error(err)
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return
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}
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log.Info("[grad check]", "k", k, "grad", grad.Float64Values())
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}
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}
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