Library/ManagedCuda/CudaDNN/CudaDNNNativeMethods.cs
// LRN uses a window [center-lookBehind, center+lookAhead], where
// lookBehind = floor( (lrnN-1)/2 ), lookAhead = lrnN-lookBehind-1.
// So for n=10, the window is [k-4...k...k+5] with a total of 10 samples.
// Values of double parameters will be cast down to tensor data type.
/// <summary>
/// This function initializes a previously created LRN descriptor object.
/// </summary>
/// <param name="normDesc">Handle to a previously created LRN descriptor.</param>
/// <param name="lrnN">Normalization window width in elements. LRN layer uses a window
/// [center-lookBehind, center+lookAhead], where lookBehind =
/// floor( (lrnN-1)/2 ), lookAhead = lrnN-lookBehind-1. So for n=10,
/// the window is [k-4...k...k+5] with a total of 10 samples. For
/// DivisiveNormalization layer the window has the same extents as above in
/// all 'spatial' dimensions (dimA[2], dimA[3], dimA[4]). By default lrnN is set
/// to 5 in cudnnCreateLRNDescriptor.</param>
/// <param name="lrnAlpha">Value of the alpha variance scaling parameter in the normalization
/// formula. Inside the library code this value is divided by the
/// window width for LRN and by (window width)^#spatialDimensions
/// for DivisiveNormalization. By default this value is set to 1e-4 in
/// cudnnCreateLRNDescriptor.</param>
/// <param name="lrnBeta">Value of the beta power parameter in the normalization formula. By
/// default this value is set to 0.75 in cudnnCreateLRNDescriptor.</param>
/// <param name="lrnK">Value of the k parameter in normalization formula. By default this value is set to 2.0.</param>
This function initializes a previously created LRN descriptor object.
This function initializes a previously created LRN descriptor object .
[DllImport(CUDNN_API_DLL_NAME)]
		public static extern cudnnStatus cudnnSetLRNDescriptor(
									  cudnnLRNDescriptor   normDesc,
									  uint               lrnN,
									  double                 lrnAlpha,
									  double                 lrnBeta,
									  double                 lrnK);
[ DllImport ( CUDNN_API_DLL_NAME ) ] public static extern cudnnStatus cudnnSetLRNDescriptor ( cudnnLRNDescriptor normDesc , uint lrnN , double lrnAlpha , double lrnBeta , double lrnK ) ;
This function initializes a previously created LRN descriptor object.
This function initializes a previously created LRN descriptor object .
normDesc
cudnnLRNDescriptor
Handle to a previously created LRN descriptor.
Handle to a previously created LRN descriptor .
lrnN
uint
Normalization window width in elements. LRN layer uses a window
[center-lookBehind, center+lookAhead], where lookBehind
floor( (lrnN-1)/2 ), lookAhead = lrnN-lookBehind-1. So for n=10,
the window is [k-4...k...k+5] with a total of 10 samples. For
DivisiveNormalization layer the window has the same extents as above in
all 'spatial' dimensions (dimA[2], dimA[3], dimA[4]). By default lrnN is set
to 5 in cudnnCreateLRNDescriptor.
Normalization window width in elements . LRN layer uses a window [ center - lookBehind center + lookAhead ] where lookBehind floor ( ( lrnN - 1 ) / 2 ) lookAhead = lrnN - lookBehind - 1 . So for n = 10 the window is [ k - 4 ... k ... k + 5 ] with a total of 10 samples . For DivisiveNormalization layer the window has the same extents as above in all ' spatial ' dimensions ( dimA [ 2 ] dimA [ 3 ] dimA [ 4 ] ) . By default lrnN is set to 5 in cudnnCreateLRNDescriptor .
lrnAlpha
double
Value of the alpha variance scaling parameter in the normalization
formula. Inside the library code this value is divided by the
window width for LRN and by (window width)^#spatialDimensions
for DivisiveNormalization. By default this value is set to 1e-4 in
cudnnCreateLRNDescriptor.
Value of the alpha variance scaling parameter in the normalization formula . Inside the library code this value is divided by the window width for LRN and by ( window width ) ^#spatialDimensions for DivisiveNormalization . By default this value is set to 1e - 4 in cudnnCreateLRNDescriptor .
lrnBeta
double
Value of the beta power parameter in the normalization formula. By
default this value is set to 0.75 in cudnnCreateLRNDescriptor.
Value of the beta power parameter in the normalization formula . By default this value is set to 0 . 75 in cudnnCreateLRNDescriptor .
lrnK
double
Value of the k parameter in normalization formula. By default this value is set to 2.0.
Value of the k parameter in normalization formula . By default this value is set to 2 . 0 .