More work done on torch

test.go

@@ -0,0 +1,108 @@
+package main
+
+import (
+	"git.andr3h3nriqu3s.com/andr3/gotch"
+
+	dbtypes "git.andr3h3nriqu3s.com/andr3/fyp/logic/db_types"
+	"git.andr3h3nriqu3s.com/andr3/fyp/logic/models/train/torch"
+	my_nn "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/train/torch/nn"
+
+	torch "git.andr3h3nriqu3s.com/andr3/gotch/ts"
+	"github.com/charmbracelet/log"
+)
+
+func main_() {
+
+	log.Info("Hello world")
+
+	m := train.BuildModel([]*dbtypes.Layer{
+		&dbtypes.Layer{
+			LayerType: dbtypes.LAYER_INPUT,
+			Shape:     "[ 2, 3, 3 ]",
+		},
+		&dbtypes.Layer{
+			LayerType: dbtypes.LAYER_FLATTEN,
+		},
+		&dbtypes.Layer{
+			LayerType: dbtypes.LAYER_DENSE,
+			Shape:     "[ 10 ]",
+		},
+	}, 0, true)
+
+    var err error
+
+	d := gotch.CudaIfAvailable()
+
+    log.Info("device", "d", d)
+
+    m.To(d)
+
+
+	opt, err := my_nn.DefaultAdamConfig().Build(m.Vs, 0.001)
+	if err != nil {
+		return
+	}
+
+	ones := torch.MustOnes([]int64{1, 2, 3, 3}, gotch.Float, d)
+	ones = ones.MustSetRequiresGrad(true, true)
+	ones.RetainGrad(false)
+
+	res := m.ForwardT(ones, true)
+	res = res.MustSetRequiresGrad(true, true)
+	res.RetainGrad(false)
+
+    outs := torch.MustOnes([]int64{1, 10}, gotch.Float, d)
+    outs = outs.MustSetRequiresGrad(true, true)
+    outs.RetainsGrad(false)
+
+
+    loss, err := res.BinaryCrossEntropyWithLogits(outs, &torch.Tensor{}, &torch.Tensor{}, 1, false)
+    if err != nil {
+       return
+    }
+    loss = loss.MustSetRequiresGrad(true, false)
+
+    opt.ZeroGrad()
+
+
+	log.Info("loss", "loss", loss.Float64Values())
+
+	loss.MustBackward()
+
+
+    opt.Step()
+
+	// log.Info(mean.MustGrad(false).Float64Values())
+	log.Info(res.MustGrad(false).Float64Values())
+	log.Info(ones.MustGrad(false).Float64Values())
+	log.Info(outs.MustGrad(false).Float64Values())
+
+	vars := m.Vs.Variables()
+
+	for k, v := range vars {
+
+        log.Info("[grad check]", "k", k)
+
+		var grad *torch.Tensor
+		grad, err = v.Grad(false)
+		if err != nil {
+            log.Error(err)
+			return
+		}
+
+		grad, err = grad.Abs(false)
+		if err != nil {
+            log.Error(err)
+			return
+		}
+
+		grad, err = grad.Max(false)
+		if err != nil {
+            log.Error(err)
+			return
+		}
+
+		log.Info("[grad check]", "k", k, "grad", grad.Float64Values())
+	}
+
+}