MaxPoolingLayer class. More...
#include <SimdNeural.hpp>
Inheritance diagram for MaxPoolingLayer:
Public Member Functions | |
| MaxPoolingLayer (Function::Type f, const Size &srcSize, size_t srcDepth, const Size &poolingSize, const Size &poolingStride, const Size &poolingPad=Size()) | |
| Creates new MaxPoolingLayer 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
MaxPoolingLayer class.
Max pooling layer in neural network.
Constructor & Destructor Documentation
◆ MaxPoolingLayer()
| MaxPoolingLayer | ( | Function::Type | f, |
| const Size & | srcSize, | ||
| size_t | srcDepth, | ||
| const Size & | poolingSize, | ||
| const Size & | poolingStride, | ||
| const Size & | poolingPad = Size() |
||
| ) |
Creates new MaxPoolingLayer class.
- Parameters
-
[in] f - a type of activation function used in this layer. [in] srcSize - a size (width and height) of input image. [in] srcDepth - a number of input channels (images). [in] poolingSize - a pooling size. [in] poolingStride - a pooling stride. [in] poolingPad - a pooling pad. By default it is equal to (0, 0).