Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 2
The forward two-dimensional stochastic 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 non-negative input data for the forward two-dimensional stochastic pooling layer. This input can be an object of any class derived from Tensor. NoteIf you provide the input data tensor with negative elements, the layer algorithm returns unpredicted results. |
For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the forward two-dimensional stochastic 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. |
|
kernelSizes |
KernelSizes(2, 2) |
Data structure representing sizes m1, m2 of two-dimensional tensor K. |
|
strides |
Strides(2, 2) |
Data structure representing intervals s1, s2 on which the subtensors for stochastic pooling are selected. |
|
paddings |
Paddings(0, 0) |
Data structure representing numbers p1, p2 of data elements to implicitly add to each side of the two-dimensional subtensor along which stochastic pooling is performed. |
|
indices |
Indices(p-2, p-1) |
Indices k1, k2 of the dimensions along which stochastic pooling is performed. |
|
predictionStage |
false |
Flag that specifies whether the layer is used for the prediction stage. |
|
DEPRECATED: seed |
777 |
NoteThis parameter is deprecated and will be removed in a future release.Seed for multinomial random number generator. |
|
engine |
SharePtr< engines:: mt19937:: Batch>() |
Pointer to the random number generator engine that is used internally for multinomial random number generation. |
The forward two-dimensional stochastic 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 tensor Y of size l1 x ... x lp that stores the result of the forward two-dimensional stochastic pooling layer. This input can be an object of any class derived from Tensor. |
|
resultForBackward |
Collection of data needed for the backward two-dimensional stochastic pooling layer. |
|
Element ID |
Element |
|
auxSelectedIndices |
Tensor S of size l1 x ... x lp that stores positions of selected elements. |
|
auxInputDimensions |
NumericTable of size 1 x p that stores the sizes of the dimensions of input data tensor X: n1, n2, …, np. |
C++: stoch_pool2d_layer_dense_batch.cpp
Java*: StochPool2DLayerDenseBatch.java
Python*: stoch_pool2d_layer_dense_batch.py