Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 2
The forward one-dimensional max pooling 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 |
Pointer to tensor X of size n1 x ... x np that stores the input data for the forward one-dimensional max pooling 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 one-dimensional max pooling 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 |
Performance-oriented computation method, the only method supported by the layer. |
|
kernelSize |
KernelSize(2) |
Data structure representing the size of the one-dimensional subtensor from which the maximum element is selected. |
|
stride |
Stride(2) |
Data structure representing the interval on which the subtensors for max pooling are selected. |
|
padding |
Padding(0) |
Data structure representing the number of data elements to implicitly add to each side of the one-dimensional subtensor along which max pooling is performed. |
|
index |
Index(p-1) |
Index k of the dimension along which max pooling is performed. |
The forward one-dimensional max pooling 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 |
|
---|---|---|
value |
Pointer to the tensor of size l1 x ... x lp that stores the result of the forward one-dimensional max pooling layer. This input can be an object of any class derived from Tensor. |
|
resultForBackward |
Collection of data needed for the backward one-dimensional max pooling layer. |
|
Element ID |
Element |
|
auxSelectedIndices |
Tensor T of size l1 x ... x lp that stores indices of maximum elements. |
|
auxInputDimensions |
NumericTable of size 1 x p that stores the sizes of the dimensions of input data tensor X: n1, n2, …, np. |
C++: max_pool1d_layer_dense_batch.cpp
Java*: MaxPool1DLayerDenseBatch.java
Python*: maxi_pool1d_layer_dense_batch.py