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convolve< Backend::EIGEN3, Matrix > Struct Template Reference

Detailed Description

template<class Matrix>
struct shogun::linalg::implementation::convolve< Backend::EIGEN3, Matrix >

Partial specialization of convolve for the Eigen3 backend

Definition at line 88 of file Convolve.h.

Public Types

typedef Matrix::Scalar T
typedef Eigen::Matrix< T,
Eigen::Dynamic, Eigen::Dynamic > 
typedef Eigen::Matrix< T,
Eigen::Dynamic, 1 > 

Static Public Member Functions

static void compute (SGMatrix< T > X, SGMatrix< T > W, SGMatrix< T > Y, bool flip, bool overwrite, int32_t stride_x, int32_t stride_y)

Member Typedef Documentation

typedef Eigen::Matrix<T,Eigen::Dynamic,Eigen::Dynamic> MatrixXt

Eigen3 matrix type

Definition at line 94 of file Convolve.h.

typedef Matrix::Scalar T

The scalar type

Definition at line 91 of file Convolve.h.

typedef Eigen::Matrix<T,Eigen::Dynamic,1> VectorXt

Eigen3 vector type

Definition at line 97 of file Convolve.h.

Member Function Documentation

static void compute ( SGMatrix< T X,
SGMatrix< T W,
SGMatrix< T Y,
bool  flip,
bool  overwrite,
int32_t  stride_x,
int32_t  stride_y 

Computes the 2D convolution of X with W

XInput image
WFilter coefficients. The dimensions of the matrix must be odd-numbered.
YOutput image of the same size as the input image, as the borders of the input image are implicitly padded with zeros during the computation
flipIf true the filter coefficients are flipped, performing cross-correlation instead of convolution
overwriteIf true, the values in Y are overwritten with result of the computation. Otherwise, the result is added to the existing values in Y.
stride_xStride in the x (column) direction
stride_yStride in the y (row) direction

Definition at line 112 of file Convolve.h.

The documentation for this struct was generated from the following file:

SHOGUN Machine Learning Toolbox - Documentation