public Conv2Layer(IAllocator allocator, SeedSource seedSource, DType elementType, int batchSize, int inputWidth, int inputHeight, int nInputPlane, int nOutputPlane, ConvolutionDesc2d cd)
{
this.cd = cd;
this.weight = new NDArray(allocator, elementType, nOutputPlane, nInputPlane * cd.kW * cd.kH);
this.bias = new NDArray(allocator, elementType, nOutputPlane, 1);
this.gradWeight = new NDArray(allocator, elementType, this.weight.Shape);
this.gradBias = new NDArray(allocator, elementType, this.bias.Shape);
inputSizes = new long[] { batchSize, nInputPlane, inputHeight, inputWidth };
this.gradInput = new NDArray(allocator, elementType, inputSizes);
outputSizes = SpatialConvolutionMM.OutputSize(inputSizes, weight.Shape, cd);
this.activation = new NDArray(allocator, elementType, outputSizes);
this.OutputSizes = outputSizes;
var stdv = 1.0f / (float)Math.Sqrt(cd.kW * cd.kH * nInputPlane);
Ops.RandomUniform(weight, seedSource, -stdv, stdv);
Ops.RandomUniform(bias, seedSource, -stdv, stdv);
}
public Conv2Cpu(IAllocator allocator, SeedSource seedSource, DType elementType, int batchSize, int inputWidth, int inputHeight, int nInputPlane, int nOutputPlane, ConvolutionDesc2d cd)
: base(allocator, seedSource, elementType, batchSize, inputWidth, inputHeight, nInputPlane, nOutputPlane, cd)
{
var finputSizes = SpatialConvolutionMM.FInputSize(inputSizes, outputSizes, cd);
this.finput = new NDArray(allocator, elementType, finputSizes);
this.fgradInput = new NDArray(allocator, elementType, finputSizes);
}
public override NDArray Backward(NDArray input, NDArray gradOutput, ModelMode mode)
{
SpatialConvolutionMM.Conv2BackwardInput(input, gradOutput, gradInput, weight, finput, fgradInput, cd);
SpatialConvolutionMM.Conv2BackwardFilter(input, gradOutput, gradWeight, gradBias, finput, fgradInput, cd);
return(gradInput);
}
public override NDArray Forward(NDArray input, ModelMode mode)
{
SpatialConvolutionMM.Conv2Forward(input, activation, weight, bias, finput, cd);
return(activation);
}
public override Tensor Backward(Tensor input, Tensor gradOutput, ModelMode mode)
{
SpatialConvolutionMM.Conv2BackwardInput(input, gradOutput, gradInput, weight, finput, fgradInput, cd);
SpatialConvolutionMM.Conv2BackwardFilter(input, gradOutput, gradWeight, gradBias, finput, fgradInput, cd);
return(gradInput);
}
