fyp/logic/models/train/torch/utils.go

package train

import (
	"unsafe"

	my_nn "git.andr3h3nriqu3s.com/andr3/fyp/logic/models/train/torch/nn"

	"github.com/charmbracelet/log"

	"git.andr3h3nriqu3s.com/andr3/gotch/nn"
	torch "git.andr3h3nriqu3s.com/andr3/gotch/ts"
)

func or_panic(err error) {
	if err != nil {
		log.Fatal(err)
	}
}

type SimpleBlock struct {
	C1, C2 *nn.Conv2D
	BN1    *nn.BatchNorm
}

// BasicBlock returns a BasicBlockModule instance
func NewSimpleBlock(_vs *my_nn.Path, inplanes int64) *SimpleBlock {
    vs := (*nn.Path)(unsafe.Pointer(_vs))

	conf1 := nn.DefaultConv2DConfig()
	conf1.Stride = []int64{2, 2}

	conf2 := nn.DefaultConv2DConfig()
	conf2.Padding = []int64{2, 2}

	b := &SimpleBlock{
		C1:  nn.NewConv2D(vs, inplanes, 128, 3, conf1),
		C2:  nn.NewConv2D(vs, 128, 128, 3, conf2),
		BN1: nn.NewBatchNorm(vs, 2, 128, nn.DefaultBatchNormConfig()),
	}
	return b
}

// Forward method
func (b *SimpleBlock) Forward(x *torch.Tensor) *torch.Tensor {
	identity := x

	out := b.C1.Forward(x)
	out = out.MustRelu(false)

	out = b.C2.Forward(out)
	out = out.MustRelu(false)

	shape, err := out.Size()
	or_panic(err)

	out, err = out.AdaptiveAvgPool2d(shape, false)
	or_panic(err)

	out = b.BN1.Forward(out)
	out, err = out.LeakyRelu(false)
	or_panic(err)

	out = out.MustAdd(identity, false)
	out = out.MustRelu(false)

	return out
}

func (b *SimpleBlock) ForwardT(x *torch.Tensor, train bool) *torch.Tensor {
	identity := x

	out := b.C1.ForwardT(x, train)
	out = out.MustRelu(false)

	out = b.C2.ForwardT(out, train)
	out = out.MustRelu(false)

	shape, err := out.Size()
	or_panic(err)

	out, err = out.AdaptiveAvgPool2d(shape, false)
	or_panic(err)

	out = b.BN1.ForwardT(out, train)
	out, err = out.LeakyRelu(false)
	or_panic(err)

	out = out.MustAdd(identity, false)
	out = out.MustRelu(false)

	return out
}


// BasicBlock returns a BasicBlockModule instance
func NewLinear(vs *my_nn.Path, in, out int64) *my_nn.Linear {
	config := my_nn.DefaultLinearConfig()
	return my_nn.NewLinear(vs, in, out, config)
}

type Flatten struct{}

// BasicBlock returns a BasicBlockModule instance
func NewFlatten() *Flatten {
	return &Flatten{}
}

// The flatten layer does not to move anything to the device
func (b *Flatten) ExtractFromVarstore(vs *my_nn.VarStore) {}
func (b *Flatten) Debug() {}

// Forward method
func (b *Flatten) Forward(x *torch.Tensor) *torch.Tensor {

	out, err := x.Flatten(1, -1, false)
	or_panic(err)

	return out
}

func (b *Flatten) ForwardT(x *torch.Tensor, train bool) *torch.Tensor {

	out, err := x.Flatten(1, -1, false)
	or_panic(err)

	return out
}

type Sigmoid struct{}

func NewSigmoid() *Sigmoid {
	return &Sigmoid{}
}

// The sigmoid layer does not need to move anything to another device
func (b *Sigmoid) ExtractFromVarstore(vs *my_nn.VarStore) {}
func (b *Sigmoid) Debug() {}

func (b *Sigmoid) Forward(x *torch.Tensor) *torch.Tensor {
	out, err := x.Sigmoid(false)
	or_panic(err)

	return out
}

func (b *Sigmoid) ForwardT(x *torch.Tensor, train bool) *torch.Tensor {
    out, err := x.Sigmoid(false)
    or_panic(err)

    return out
}