Developer Guide for Intel® Data Analytics Acceleration Library 2018 Update 2
The backward reshape 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 tensor of size m1 x ... x mq that stores the input gradient G 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 reshape layer. |
|
Element ID |
Element |
|
auxInputDimensions |
Collection of integers that stores the dimension sizes of the input tensors in the forward computation step: n1, ... , np. |
The backward reshape 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 tensor of size n1 × n2 × ... × np that stores the result of the backward reshape layer. This input can be an object of any class derived from Tensor. |
C++: reshape_layer_dense_batch.cpp
Java*: ReshapeLayerDenseBatch.java
Python*: reshape_layer_dense_batch.py