Developer Guide for Intel® Data Analytics Acceleration Library 2018 Update 2
The backward local response normalization layer accepts the input described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms.
Input ID |
Input |
|
---|---|---|
inputGradient |
Pointer to the tensor of size n1 x n2 x ... x np that stores the input gradient computed on the preceding layer. This input can be an object of any class derived from Tensor. |
|
inputFromForward |
Collection of input data needed for the backward local response normalization layer. This collection can contain objects of any class derived from Tensor. |
|
Element ID |
Element |
|
auxData |
Pointer to the tensor of size n1 x n2 x ... x np that stores the input data for the forward local response normalization layer. This input can be an object of any class derived from Tensor. |
|
auxSmBeta |
Pointer to the tensor of size n1 x n2 x ... x np that stores the value of (sk * (ik))-β . This input can be an object of any class derived from Tensor. |
For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the backward local response normalization layer has the following parameters:
Parameter |
Default Value |
Description |
|
---|---|---|---|
algorithmFPType |
float |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
|
method |
defaultDense |
Computation method used by the algorithm. The only method supported by the layer so far is acrossDimension. |
|
dimension |
1 |
Numeric table of size 1 x 1 with the dimension index of type size_t to calculate local response normalization backpropagation. |
|
kappa |
2 |
Value of layer hyper-parameter κ. |
|
alpha |
1.0e-04 |
Value of layer hyper-parameter α. |
|
beta |
0.75 |
Value of layer hyper-parameter β. |
|
nAdjust |
5 |
Value of layer hyper-parameter n. |
The backward local response normalization layer calculates the result described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.
Result ID |
Result |
|
---|---|---|
gradient |
Pointer to the tensor of size n1 x n2 x ... x np that stores the result of the backward local response normalization layer. This input can be an object of any class derived from Tensor. |
C++: lrn_layer_dense_batch.cpp
Java*: LRNLayerDenseBatch.java
Python*: lrn_layer_dense_batch.py