Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 5
The backward split 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 |
|
---|---|---|
inputGradientCollection |
Collection of k tensors of size n1 x ... x np that stores the result of the forward split layer. This collection can contain objects of any class derived from Tensor. |
inputGradient stores a null pointer while inputGradientCollection stores all input tensors.
For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the backward split layer has the following parameters:
Parameter |
Default Value |
Description |
|
---|---|---|---|
nInputs |
1 |
Number of input tensors. |
The backward split 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 |
Tensor of size n1 x ... x np that stores result z of the backward split layer. This result can be an object of any class derived from Tensor. |
C++: split_layer_dense_batch.cpp
Java*: SplitLayerDenseBatch.java
Python*: split_layer_dense_batch.py