Getting Started Guide

Contents

Batch Processing

Layer Input

The backward two-dimensional average 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
inputGradient
Pointer to the tensor of size
m
1
x
m
2
x ... x
m
p
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 data needed for the backward two-dimensional average pooling layer.
Element ID
Element
auxInputDimensions
Collection that contains the size of the dimensions of the input data tensor in the forward computation step:
n
1
,
n
2
, ...,
n
p
.

Layer Parameters

For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the backward two-dimensional average 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 the size of the two-dimensional subtensor from which the average element is computed.
strides
Strides(2, 2)
Data structure representing the intervals on which the subtensors for pooling are selected.
paddings
Paddings(0, 0)
Data structure representing the number of data elements to implicitly add to each size of the two-dimensional subtensor on which pooling is performed.
indices
HomogenNumericTable(p-2, p-1)
Indices of the two dimensions on which pooling is performed, stored in
HomogenNumericTable
.

Layer Output

The backward two-dimensional average 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
gradient
Pointer to the tensor of size
n
1
x
n
2
x ... x
n
p
that stores the result of the backward two-dimensional average pooling layer. This input can be an object of any class derived from
Tensor
.

Product and Performance Information

1

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Notice revision #20110804