Developer Guide for Intel® Data Analytics Acceleration Library 2018
The forward 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 |
|
---|---|---|
data |
Tensor of size n1 x ... x np that stores the input data for the forward split layer. 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 forward split layer has the following parameters:
Parameter |
Default Value |
Description |
|
---|---|---|---|
nOutputs |
1 |
Number of output tensors. |
The forward 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 |
|
---|---|---|
valueCollection |
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. |
The value result stores a null pointer while valueCollection stores actual computation results.
C++: split_layer_dense_batch.cpp
Java*: SplitLayerDenseBatch.java
Python*: split_layer_dense_batch.py