|
private cudnnLRNCrossChannelForward ( |
||
| handle | ||
| normDesc | ||
| lrnMode | cudnnLRNMode | |
| alpha | double | |
| srcDesc | ||
| srcData | ManagedCuda.BasicTypes.CUdeviceptr | |
| beta | double | |
| destDesc | ||
| destData | ManagedCuda.BasicTypes.CUdeviceptr | |
| return | cudnnStatus | |
public void cudnnLRNCrossChannelForward(
cudnnLRNMode lrnMode,
double alpha,
cudnnTensorDescriptor srcDesc,
CUdeviceptr srcData,
double beta,
cudnnTensorDescriptor destDesc,
CUdeviceptr destData)
{
res = CudaDNNNativeMethods.cudnnLRNCrossChannelForward(_handle, _desc, lrnMode, ref alpha, srcDesc, srcData, ref beta, destDesc, destData);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnLRNCrossChannelForward", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
}
/// <summary>
/// This function performs the forward LRN layer computation.
/// </summary>
/// <param name="lrnMode">LRN layer mode of operation. Currently only
/// CUDNN_LRN_CROSS_CHANNEL_DIM1 is implemented. Normalization is
/// performed along the tensor's dimA[1].</param>
/// <param name="alpha">Pointer to scaling factors (in host memory) used to blend the layer output
/// value with prior value in the destination tensor as follows: dstValue =
/// alpha[0]*resultValue + beta[0]*priorDstValue. Please refer to this section
/// for additional details.</param>
/// <param name="xDesc">Tensor descriptor objects for the input and output tensors.</param>
/// <param name="x">Input tensor data pointer in device memory.</param>
/// <param name="beta">Pointer to scaling factors (in host memory) used to blend the layer output
/// value with prior value in the destination tensor as follows: dstValue =
/// alpha[0]*resultValue + beta[0]*priorDstValue. Please refer to this section
/// for additional details.</param>
/// <param name="yDesc">Tensor descriptor objects for the input and output tensors.</param>
/// <param name="y">Output tensor data pointer in device memory.</param>
public void cudnnLRNCrossChannelForward(
cudnnLRNMode lrnMode,
float alpha,
cudnnTensorDescriptor xDesc,
CUdeviceptr x,
float beta,
cudnnTensorDescriptor yDesc,
CUdeviceptr y)
{
res = CudaDNNNativeMethods.cudnnLRNCrossChannelForward(_handle, _desc, lrnMode, ref alpha, xDesc, x, ref beta, yDesc, y);
Debug.Write(""); //Line(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnLRNCrossChannelForward", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
}