Library/ManagedCuda/CudaDNN/CudaDNNNativeMethods.cs
/// <summary>
/// This function performs the forward LRN layer computation.
/// </summary>
/// <param name="handle">Handle to a previously created cuDNN library descriptor.</param>
/// <param name="normDesc">Handle to a previously intialized LRN parameter descriptor.</param>
/// <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 .
[DllImport(CUDNN_API_DLL_NAME)]
		public static extern cudnnStatus cudnnLRNCrossChannelForward(
									  cudnnHandle                    handle,
									  cudnnLRNDescriptor             normDesc,
									  cudnnLRNMode                   lrnMode,
									  ref double alpha,
									  cudnnTensorDescriptor    xDesc,
									  CUdeviceptr x,
									  ref double beta,
									  cudnnTensorDescriptor    yDesc,
									  CUdeviceptr y);
[ DllImport ( CUDNN_API_DLL_NAME ) ] public static extern cudnnStatus cudnnLRNCrossChannelForward ( cudnnHandle handle , cudnnLRNDescriptor normDesc , cudnnLRNMode lrnMode , ref double alpha , cudnnTensorDescriptor xDesc , CUdeviceptr x , ref double beta , cudnnTensorDescriptor yDesc , CUdeviceptr y ) ;
This function performs the forward LRN layer computation.
This function performs the forward LRN layer computation .
handle
cudnnHandle
Handle to a previously created cuDNN library descriptor.
Handle to a previously created cuDNN library descriptor .
normDesc
cudnnLRNDescriptor
Handle to a previously intialized LRN parameter descriptor.
Handle to a previously intialized LRN parameter descriptor .
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 ] .
double
ref
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 .
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 .
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.
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 .
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.
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 .