Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 5
For a given dimension k ∈ {1, ..., p} of size n k , the forward local response normalization layer normalizes the input tensor X ∈ R n 1 x n 2 x ... x n p . For more details and notations, see Forward Local Response Normalization Layer.
For a dimension k ∈ {1, ..., p} of size n k , the backward local response normalization layer computes the value:
where:
g i 1...i p is the input gradient computed on the preceding layer
α, β, κ ∈ R
n is a positive integer number
Given p-dimensional tensors:
X ∈ R n 1 x n 2 x ... x n p of size n 1 x n 2 x ... x n p
G ∈ R n 1 x n 2 x ... x n p - the gradient computed on the preceding layer
The problem is to compute the p-dimensional tensor Z = (z i 1...i p ) ∈ R n 1 x n 2 x ... x n p .