FullyConnectedLayer class. More...
#include <SimdNeural.hpp>
Inheritance diagram for FullyConnectedLayer:
Public Member Functions | |
| FullyConnectedLayer (Function::Type f, size_t srcSize, size_t dstSize, bool bias=true) | |
| Creates new FullyConnectedLayer class. More... | |
 Public Member Functions inherited from Layer | |
| virtual | ~Layer () |
Additional Inherited Members | |
| Public Types inherited from Layer | |
| enum | Type { Input , Convolutional , MaxPooling , AveragePooling , FullyConnected , Dropout } |
| enum | Method { Fast , Check , Train } |
Detailed Description
FullyConnectedLayer class.
Fully connected layer in neural network.
Constructor & Destructor Documentation
◆ FullyConnectedLayer()
| FullyConnectedLayer | ( | Function::Type | f, |
| size_t | srcSize, | ||
| size_t | dstSize, | ||
| bool | bias = true |
||
| ) |
Creates new FullyConnectedLayer class.
- Parameters
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[in] f - a type of activation function used in this layer. [in] srcSize - a size of input vector. [in] dstSize - a size of output vector. [in] bias - a boolean flag (enabling of bias). By default it is True.