Class KernelMatrixTest

src/test/test_kernelmatrix.cpp:69–121

}

class KernelMatrixTest : public ::testing::Test {
    DataSet dataSet;
    unsigned n_rows = 10;
    SyncArray<int> rows;
    DataSet::node2d instances;
    SyncArray<kernel_type> kernel_rows;
protected:
    SvmParam param;

    void SetUp() override {
        param = SvmParam();
        dataSet.load_from_file(DATASET_DIR "test_dataset.txt");
        rows.resize(n_rows);
        kernel_rows.resize(n_rows * dataSet.n_instances());
        for (unsigned i = 0; i < n_rows; ++i) {
            rows.host_data()[i] = i * 3 + 4;
        }
        instances = DataSet::node2d(dataSet.instances().begin(), dataSet.instances().begin() + n_rows);
    }

    void TearDown() override {
        KernelMatrix *kernelMatrix = new KernelMatrix(dataSet.instances(), param);
        kernelMatrix->get_rows(rows, kernel_rows);

        //test diagonal elements
        for (unsigned i = 0; i < kernelMatrix->diag().size(); ++i) {
            float_type cpu_kernel = get_cpu_kernel(dataSet.instances(), i, i, param);
            float_type gpu_kernel = kernelMatrix->diag().host_data()[i];
            EXPECT_NEAR(gpu_kernel, cpu_kernel, 1e-4) << i;
        }

        //test get rows with index
        for (unsigned i = 0; i < rows.size(); ++i) {
            for (unsigned j = 0; j < kernelMatrix->n_instances(); ++j) {
                float_type gpu_kernel = kernel_rows.host_data()[i * kernelMatrix->n_instances() + j];
                float_type cpu_kernel = get_cpu_kernel(dataSet.instances(), rows.host_data()[i], j, param);
                EXPECT_NEAR(gpu_kernel, cpu_kernel, 1e-4) << rows.host_data()[i] << "," << j;
            }
        }

        //test get rows with instances
        kernelMatrix->get_rows(instances, kernel_rows);

        for (unsigned i = 0; i < n_rows; ++i) {
            for (unsigned j = 0; j < kernelMatrix->n_instances(); ++j) {
                float_type gpu_kernel = kernel_rows.host_data()[i * kernelMatrix->n_instances() + j];
                float_type cpu_kernel = get_cpu_kernel(dataSet.instances(), i, j, param);
                EXPECT_NEAR(gpu_kernel, cpu_kernel, 1e-4) << i << "," << j;
            }
        }
        delete kernelMatrix;
    }
};

TEST_F(KernelMatrixTest, test_rbf) {
    param.gamma = 0.5;