Library/ManagedCuda/CudaDNN/LRNDescriptor.cs
/// <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>
This function performs the forward LRN layer computation.
This function performs the forward LRN layer computation .
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.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnLRNCrossChannelForward", res));
			if (res != cudnnStatus.Success) throw new CudaDNNException(res);
		}
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 . WriteLine ( String . Format ( " " , DateTime . Now , " " , res ) ) ; if ( res != cudnnStatus . Success ) throw new CudaDNNException ( res ) ; }
This function performs the forward LRN layer computation.
This function performs the forward LRN layer computation .
lrnMode
cudnnLRNMode
LRN layer mode of operation. Currently only
CUDNN_LRN_CROSS_CHANNEL_DIM1 is implemented. Normalization is
performed along the tensor's dimA[1].
LRN layer mode of operation . Currently only CUDNN_LRN_CROSS_CHANNEL_DIM1 is implemented . Normalization is performed along the tensor ' s dimA [ 1 ] .
alpha
float
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.
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 .
xDesc
cudnnTensorDescriptor
Tensor descriptor objects for the input and output tensors.
Tensor descriptor objects for the input and output tensors .
x
CUdeviceptr
Input tensor data pointer in device memory.
Input tensor data pointer in device memory .
beta
float
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.
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 .
yDesc
cudnnTensorDescriptor
Tensor descriptor objects for the input and output tensors.
Tensor descriptor objects for the input and output tensors .
y
CUdeviceptr
Output tensor data pointer in device memory.
Output tensor data pointer in device memory .