///<summary>Выполняет прямой проход через кодирующую нейросеть.</summary>
///<param name="input">Входные данные.</param>
public Tensor Encode(Tensor input)
{
var Temp = input;
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_1_Weights, this.Data.Conv1_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_2_Weights, this.Data.Conv1_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_1_Weights, this.Data.Conv2_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_2_Weights, this.Data.Conv2_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
//this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_1_Weights, this.Data.Conv3_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_2_Weights, this.Data.Conv3_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_3_Weights, this.Data.Conv3_3_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_4_Weights, this.Data.Conv3_4_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv4_1_Weights, this.Data.Conv4_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
return(Temp);
}
///<summary>Выполняет прямой проход через кодирующую нейросеть.</summary>
///<param name="input">Входные данные.</param>
public Tensor[] EncodeStyle(Tensor input)
{
var Temp = input;
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_1_Weights, this.Data.Conv1_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
var Conv1 = Temp;
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_2_Weights, this.Data.Conv1_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_1_Weights, this.Data.Conv2_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
var Conv2 = Temp;
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_2_Weights, this.Data.Conv2_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
//this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_1_Weights, this.Data.Conv3_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
var Conv3 = Temp;
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_2_Weights, this.Data.Conv3_2_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_3_Weights, this.Data.Conv3_3_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_4_Weights, this.Data.Conv3_4_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.AvgPool2D(Temp);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv4_1_Weights, this.Data.Conv4_1_Biases);
if (this.Step != null)
{
this.Step(5f);
}
Temp = Layers.ReLU(Temp);
var Conv4 = Temp;
if (this.Step != null)
{
this.Step(5f);
}
return(new Tensor[4] {
Conv1, Conv2, Conv3, Conv4
});
}