Developer Guide for Intel® Data Analytics Acceleration Library 2019 Update 2
The forward fully-connected 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 the tensor of size n1 x ... x nk x ... x np that stores the input data for the forward fully-connected layer. This input can be an object of any class derived from Tensor. |
|
weights |
Pointer to the tensor of size n1 x ... x nk - 1 x m x nk + 1 x ... x np that stores a set of weights. This input can be an object of any class derived from Tensor. |
|
biases |
Pointer to the tensor of size m that stores a set of biases. This input can be an object of any class derived from Tensor. |
|
mask |
Pointer to the tensor of size n1 x ... x nk - 1 x m x nk + 1 x ... x np that holds 1 for the corresponding weights used in computations and 0 for the weights not used in computations. If no mask is provided, the library uses all the weights. |
For common parameters of neural network layers, see Common Parameters.
In addition to the common parameters, the forward fully-connected 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. |
|
nOutputs |
Not applicable |
Number of layer outputs m. Required to initialize the algorithm. |
The forward fully-connected 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 nk x m that stores the result of the forward fully-connected layer. This input can be an object of any class derived from Tensor. |
|
resultForBackward |
Collection of data needed for the backward fully-connected layer. |
|
Element ID |
Element |
|
auxData |
Pointer to the tensor of size n1 x ... x nk x ... x np that stores the input data for the forward fully-connected layer. This input can be an object of any class derived from Tensor. |
|
auxWeights |
Pointer to the tensor of size n1 x ... x nk - 1 x m x nk + 1 x ... x np that stores a set of weights. This input can be an object of any class derived from Tensor. |
|
auxBiases |
Pointer to the tensor of size m that stores a set of biases. This input can be an object of any class derived from Tensor. |
|
auxMask |
Pointer to the tensor of size n1 x ... x nk - 1 x m x nk + 1 x ... x np that holds 1 for the corresponding weights used in computations and 0 for the weights not used in computations. If no mask is provided, the library uses all the weights. |
C++: fullycon_layer_dense_batch.cpp
Java*: FullyconLayerDenseBatch.java
Python*: fullycon_layer_dense_batch.py