August 2019
Intermediate to advanced
242 pages
5h 45m
English
Content preview from Hands-On Deep Learning with Go
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Loss function and solver
We will be using the ordinary cross-entropy loss function here, which can be implemented as follows:
losses := gorgonia.Must(gorgonia.HadamardProd(gorgonia.Must(gorgonia.Log(m.out)), y))cost := gorgonia.Must(gorgonia.Sum(losses))cost = gorgonia.Must(gorgonia.Neg(cost))if _, err = gorgonia.Grad(cost, m.learnables()...); err != nil { log.Fatal(err)}
Together with that, we will be using the Gorgonia tape machine and the RMSprop solver, as shown here:
vm := gorgonia.NewTapeMachine(g, gorgonia.WithPrecompiled(prog, locMap), gorgonia.BindDualValues(m.learnables()...))solver := gorgonia.NewRMSPropSolver(gorgonia.WithBatchSize(float64(bs)))
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