Getting Started Guide

Contents

Batch Processing

Layer Input

The backward pReLU 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
n
1
x
n
2
x ... x
n
p
that stores the input gradient 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 pReLU layer. This collection can contain objects of any class derived from
Tensor
.
Element ID
Element
auxData
Pointer to the tensor of size
n
1
x
n
2
x ... x
n
p
that stores the input data for the forward pReLU layer. This input can be an object of any class derived from
Tensor
.
auxWeights
Pointer to the tensor of size
n
k
x
n
k
+ 1
x ... x
n
k
+
q
- 1
that stores weights for the forward pReLU layer. This input can be an object of any class derived from
Tensor
.

Layer Parameters

For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the backward pReLU 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.
dataDimension
0
Starting index of data dimension of type
size_t
to apply a weight.
weightsDimension
1
Number of weight dimensions of type
size_t
.
propagateGradient
false
Flag that specifies whether the backward layer propagates the gradient.

Layer Output

The backward pReLU 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 pReLU layer. This input can be an object of any class derived from
Tensor
.
weightDerivatives
Pointer to the tensor of size
n
k
x
n
k
+ 1
x ... x
n
k
+
q
- 1
that stores result
Ε
/ ∂
w
i
k
...
i
k
+
q
- 1
of the backward pReLU layer. This input can be an object of any class derived from
Tensor
.
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Product and Performance Information

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Notice revision #20110804