PLSSVM - Parallel Least Squares Support Vector Machine  2.0.0
A Least Squares Support Vector Machine implementation using different backends.
Public Types | Public Member Functions | List of all members
plssvm::sycl::detail::device_kernel_predict_polynomial< T > Class Template Reference

Predicts the labels for data points using the polynomial kernel function. More...

#include <predict_kernel.hpp>

Public Types

using real_type = T
 The type of the data.
 

Public Member Functions

 device_kernel_predict_polynomial (real_type *out_d, const real_type *data_d, const real_type *data_last_d, const real_type *alpha_d, const kernel_index_type num_data_points, const real_type *points, const kernel_index_type num_predict_points, const kernel_index_type num_features, const int degree, const real_type gamma, const real_type coef0)
 Construct a new device kernel to predict the labels for data points using the polynomial kernel function. More...
 
void operator() (::sycl::nd_item< 2 > idx) const
 Function call operator overload performing the actual calculation. More...
 

Detailed Description

template<typename T>
class plssvm::sycl::detail::device_kernel_predict_polynomial< T >

Predicts the labels for data points using the polynomial kernel function.

Currently only single GPU execution is supported.

Template Parameters
Tthe type of the data points

Constructor & Destructor Documentation

◆ device_kernel_predict_polynomial()

template<typename T >
plssvm::sycl::detail::device_kernel_predict_polynomial< T >::device_kernel_predict_polynomial ( real_type out_d,
const real_type data_d,
const real_type data_last_d,
const real_type alpha_d,
const kernel_index_type  num_data_points,
const real_type points,
const kernel_index_type  num_predict_points,
const kernel_index_type  num_features,
const int  degree,
const real_type  gamma,
const real_type  coef0 
)
inline

Construct a new device kernel to predict the labels for data points using the polynomial kernel function.

Currently only single GPU execution is supported.

Parameters
[in]out_dthe calculated predictions
[in]data_dthe one-dimension support vector matrix
[in]data_last_dthe last row of the support vector matrix
[in]alpha_dthe previously calculated weight for each data point
[in]num_data_pointsthe total number of support vectors
[in]pointsthe data points to predict
[in]num_predict_pointsthe total number of data points to predict
[in]num_featuresthe number of features per support vector and point to predict
[in]degreethe degree parameter used in the polynomial kernel function
[in]gammathe gamma parameter used in the polynomial kernel function
[in]coef0the coef0 parameter used in the polynomial kernel function

Member Function Documentation

◆ operator()()

template<typename T >
void plssvm::sycl::detail::device_kernel_predict_polynomial< T >::operator() ( ::sycl::nd_item< 2 >  idx) const
inline

Function call operator overload performing the actual calculation.

Parameters
[in]idxthe sycl::nd_item identifying an instance of the functor executing at each point in a sycl::range

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