public static extern CudnnStatus cudnnSetTensor4dDescriptor(CudnnTensorDescriptorHandle tensorDesc,
CudnnTensorFormat format,
CudnnType dataType, // image data type
int n, // number of inputs (batch size)
int c, // number of input feature maps
int h, // height of input section
int w); // width of input section
public CudnnTensorDescriptorParameters(CudnnType type, CudnnTensorFormat format, int n, int c, int h, int w)
{
if (n < 1 || c < 1 || h < 1 || w < 1)
{
throw new ArgumentException("At least one of the parameters n, c, h, w was negative.");
}
this.Type = type;
this.Num = n;
this.Channels = c;
this.Height = h;
this.Width = w;
this.NumStride = h * w * c;
if (format == CudnnTensorFormat.MajorRow)
{
this.ChannelsStride = h * w;
this.HeightStride = w;
this.WidthStride = 1;
}
else
{
this.ChannelsStride = 1;
this.HeightStride = w * c;
this.WidthStride = c;
}
}
public static extern CudnnStatus cudnnSetTensor4dDescriptor(CudnnTensorDescriptorHandle tensorDesc,
CudnnTensorFormat format,
CudnnType dataType, // image data type
int n, // number of inputs (batch size)
int c, // number of input feature maps
int h, // height of input section
int w);
public CudnnTensorDescriptorParameters(CudnnType type, CudnnTensorFormat format, int n, int c, int h, int w)
{
if (n < 1 || c < 1 || h < 1 || w < 1)
throw new ArgumentException("At least one of the parameters n, c, h, w was negative.");
this.Type = type;
this.Num = n;
this.Channels = c;
this.Height = h;
this.Width = w;
this.NumStride = h * w * c;
if ( format == CudnnTensorFormat.MajorRow )
{
this.ChannelsStride = h * w;
this.HeightStride = w;
this.WidthStride = 1;
}
else
{
this.ChannelsStride = 1;
this.HeightStride = w * c;
this.WidthStride = c;
}
}
