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Fix variant assign error with missmatching types.
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@breyerml
breyerml authored Apr 26, 2024
1 parent ef063f1 commit 9691f18
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Showing 2 changed files with 28 additions and 28 deletions.
54 changes: 27 additions & 27 deletions tests/backends/generic_csvm_tests.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -492,7 +492,7 @@ TYPED_TEST_P(GenericCSVMKernelFunction, blas_level_3_assembly_implicit_without_C
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 2.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}
if constexpr (kernel == plssvm::kernel_function_type::polynomial) {
params.degree = 1;
Expand Down Expand Up @@ -549,7 +549,7 @@ TYPED_TEST_P(GenericCSVMKernelFunction, blas_level_3_assembly_implicit) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 2.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}
if constexpr (kernel == plssvm::kernel_function_type::polynomial) {
params.degree = 1;
Expand Down Expand Up @@ -601,7 +601,7 @@ TYPED_TEST_P(GenericCSVMKernelFunction, predict_values) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 2.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}
if constexpr (kernel == plssvm::kernel_function_type::polynomial) {
params.degree = 1;
Expand Down Expand Up @@ -664,7 +664,7 @@ TYPED_TEST_P(GenericCSVMKernelFunction, predict_values_provided_w) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 2.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create the data that should be used
Expand Down Expand Up @@ -716,7 +716,7 @@ TYPED_TEST_P(GenericCSVMKernelFunction, perform_dimensional_reduction) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

const auto data = util::generate_specific_matrix<plssvm::soa_matrix<plssvm::real_type>>(plssvm::shape{ 6, 4 }, plssvm::shape{ plssvm::PADDING_SIZE, plssvm::PADDING_SIZE });
Expand Down Expand Up @@ -760,7 +760,7 @@ TYPED_TEST_P(GenericCSVMSolver, solve_lssvm_system_of_linear_equations_trivial)
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 2.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create the data that should be used
Expand Down Expand Up @@ -802,7 +802,7 @@ TYPED_TEST_P(GenericCSVMSolver, solve_lssvm_system_of_linear_equations) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 1.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create the data that should be used
Expand Down Expand Up @@ -855,7 +855,7 @@ TYPED_TEST_P(GenericCSVMSolverKernelFunction, assemble_kernel_matrix_minimal) {

plssvm::parameter params{ plssvm::kernel_type = kernel, plssvm::cost = 1.0 };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}
if constexpr (kernel == plssvm::kernel_function_type::polynomial) {
params.degree = 1;
Expand Down Expand Up @@ -1091,7 +1091,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionClassification, predict) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create data set that is always classifiable
Expand Down Expand Up @@ -1126,7 +1126,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionClassification, score_model) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create data set that is always classifiable
Expand Down Expand Up @@ -1161,7 +1161,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionClassification, score) {
// create parameter struct
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create data set that is always classifiable
Expand Down Expand Up @@ -1557,7 +1557,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, solve_lssvm_system_of_linear_eq
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1578,7 +1578,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, solve_lssvm_system_of_linear_eq
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1599,7 +1599,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, solve_lssvm_system_of_linear_eq
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1621,7 +1621,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, solve_lssvm_system_of_linear_eq
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1642,7 +1642,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, solve_lssvm_system_of_linear_eq
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1663,7 +1663,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, perform_dimensional_reduction_e
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1683,7 +1683,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, assemble_kernel_matrix_automati
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand All @@ -1709,7 +1709,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_empty_matrices)
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1745,7 +1745,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_missing_padding)
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1787,7 +1787,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_sv_alpha_size_mi
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1815,7 +1815,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_rho_alpha_size_m
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1843,7 +1843,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_w_size_mismatch)
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1874,7 +1874,7 @@ TYPED_TEST_P(GenericCSVMKernelFunctionDeathTest, predict_values_num_features_mis
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1926,7 +1926,7 @@ TYPED_TEST_P(GenericCSVMSolverKernelFunctionDeathTest, assemble_kernel_matrix_em
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1962,7 +1962,7 @@ TYPED_TEST_P(GenericCSVMSolverKernelFunctionDeathTest, assemble_kernel_matrix_A_
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down Expand Up @@ -1993,7 +1993,7 @@ TYPED_TEST_P(GenericCSVMSolverKernelFunctionDeathTest, assemble_kernel_matrix_si
// create parameter
plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

// create C-SVM: must be done using the mock class since the member function to test is private or protected
Expand Down
2 changes: 1 addition & 1 deletion tests/backends/generic_gpu_csvm_tests.hpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -407,7 +407,7 @@ TYPED_TEST_P(GenericGPUCSVMKernelFunction, run_predict_kernel) {

plssvm::parameter params{ plssvm::kernel_type = kernel };
if constexpr (kernel != plssvm::kernel_function_type::linear) {
params.gamma = 1.0;
params.gamma = real_type{ 1.0 };
}

const plssvm::data_set data{ PLSSVM_TEST_FILE };
Expand Down

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