///<summary>Выполняет прямой проход через сеть-трансформер.</summary>
///<param name="input">Входные данные.</param>
public Tensor Stylize(Tensor input)
{
var Temp = Layers.Conv2D(input, this.Data.Conv1_Weights, 1);
if (Step != null)
{
Step(10);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.Conv1_Shift, this.Data.Conv1_Scale);
Temp = Layers.ReLU(Temp);
Temp = Layers.Conv2D(Temp, this.Data.Conv2_Weights, 2);
if (Step != null)
{
Step(10);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.Conv2_Shift, this.Data.Conv2_Scale);
Temp = Layers.ReLU(Temp);
Temp = Layers.Conv2D(Temp, this.Data.Conv3_Weights, 2);
if (Step != null)
{
Step(10);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.Conv3_Shift, this.Data.Conv3_Scale);
Temp = Layers.ReLU(Temp);
Temp = Layers.ResBlock(Temp, this.Data.ResBlock1);
if (Step != null)
{
Step(10);
}
Temp = Layers.ResBlock(Temp, this.Data.ResBlock2);
if (Step != null)
{
Step(10);
}
Temp = Layers.ResBlock(Temp, this.Data.ResBlock3);
if (Step != null)
{
Step(10);
}
Temp = Layers.ResBlock(Temp, this.Data.ResBlock4);
if (Step != null)
{
Step(10);
}
Temp = Layers.ResBlock(Temp, this.Data.ResBlock5);
if (Step != null)
{
Step(10);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv1_Weights, 2);
if (Step != null)
{
Step(10);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv1_Shift, this.Data.TConv1_Scale);
Temp = Layers.ReLU(Temp);
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv2_Weights, 2);
if (Step != null)
{
Step(10);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv2_Shift, this.Data.TConv2_Scale);
Temp = Layers.ReLU(Temp);
Temp = Layers.Conv2D(Temp, this.Data.TConv3_Weights, 1);
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv3_Shift, this.Data.TConv3_Scale);
Temp = Layers.Tanh(Temp);
return(Temp);
}
///<summary>Выполняет прямой проход через декодирующую нейросеть.</summary>
///<param name="input">Входные данные.</param>
public Tensor Decode(Tensor Content, Tensor Style)
{
var Temp = Layers.StyleSwap(Content, Style);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv3_1_Weights, this.Data.TConv3_1_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv3_1_Shift, this.Data.TConv3_1_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv2_4_Weights, this.Data.TConv2_4_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv2_4_Shift, this.Data.TConv2_4_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.Upsample2D(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv2_3_Weights, this.Data.TConv2_3_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv2_3_Shift, this.Data.TConv2_3_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv2_2_Weights, this.Data.TConv2_2_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv2_2_Shift, this.Data.TConv2_2_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv2_1_Weights, this.Data.TConv2_1_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv2_1_Shift, this.Data.TConv2_1_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv1_4_Weights, this.Data.TConv1_4_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv1_4_Shift, this.Data.TConv1_4_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.Upsample2D(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv1_3_Weights, this.Data.TConv1_3_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv1_3_Shift, this.Data.TConv1_3_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv1_2_Weights, this.Data.TConv1_2_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.InstanceNorm2D(Temp, this.Data.TConv1_2_Shift, this.Data.TConv1_2_Scale);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.ConvTranspose2D(Temp, this.Data.TConv1_1_Weights, this.Data.TConv1_1_Biases, 1);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
Temp = Layers.Sigmoid(Temp);
if (this.Step != null)
{
this.Step(1f / 29f * 100f);
}
return(Temp);
}