From 4f77f2fedaf4cc550e6fb7e28cbe18410bcabf6d Mon Sep 17 00:00:00 2001 From: Omar Shrit Date: Sun, 11 Feb 2024 16:33:32 +0100 Subject: [PATCH] Change from to From in tests and core Signed-off-by: Omar Shrit --- src/mlpack/core/util/conv_to.hpp | 4 +- .../tests/ann/not_adapted/ann_layer_test.cpp | 2 +- src/mlpack/tests/image_load_test.cpp | 2 +- src/mlpack/tests/linear_svm_test.cpp | 40 +++++++++---------- src/mlpack/tests/lmnn_test.cpp | 2 +- .../tests/main_tests/hmm_test_utils.hpp | 2 +- .../tests/main_tests/image_converter_test.cpp | 10 ++--- src/mlpack/tests/softmax_regression_test.cpp | 28 ++++++------- 8 files changed, 45 insertions(+), 45 deletions(-) diff --git a/src/mlpack/core/util/conv_to.hpp b/src/mlpack/core/util/conv_to.hpp index 628ececdf2..eb003f8bf8 100644 --- a/src/mlpack/core/util/conv_to.hpp +++ b/src/mlpack/core/util/conv_to.hpp @@ -35,7 +35,7 @@ class ConvTo * @param input The input that is converted. */ template - inline static OutputType from(const InputType& input, + inline static OutputType From(const InputType& input, const typename std::enable_if_t< coot::is_coot_type::value || coot::is_coot_type::value>* = 0) @@ -51,7 +51,7 @@ class ConvTo * @param input The input that is converted. */ template - inline static OutputType from(const InputType& input, + inline static OutputType From(const InputType& input, const typename std::enable_if_t< arma::is_arma_type::value || arma::is_arma_type::value>* = 0) diff --git a/src/mlpack/tests/ann/not_adapted/ann_layer_test.cpp b/src/mlpack/tests/ann/not_adapted/ann_layer_test.cpp index 729d0dff95..b9c2ddb34f 100644 --- a/src/mlpack/tests/ann/not_adapted/ann_layer_test.cpp +++ b/src/mlpack/tests/ann/not_adapted/ann_layer_test.cpp @@ -1791,7 +1791,7 @@ TEST_CASE("SimpleLookupLayerTest", "[ANNLayerTest]") { // The Lookup module uses index - 1 for the cols. const double outputSum = arma::accu(module.Parameters().cols( - ConvTo::from(input.col(i)) - 1)); + ConvTo::From(input.col(i)) - 1)); REQUIRE(std::fabs(outputSum - arma::accu(output.col(i))) <= 1e-5); } diff --git a/src/mlpack/tests/image_load_test.cpp b/src/mlpack/tests/image_load_test.cpp index f6b9ee940a..48a65dda02 100644 --- a/src/mlpack/tests/image_load_test.cpp +++ b/src/mlpack/tests/image_load_test.cpp @@ -115,7 +115,7 @@ TEST_CASE("SaveImageMatAPITest", "[ImageLoadTest]") arma::Mat im1; size_t dimension = info.Width() * info.Height() * info.Channels(); im1 = arma::randi>(dimension, 1); - arma::mat input = ConvTo::from(im1); + arma::mat input = ConvTo::From(im1); REQUIRE(Save("APITest.bmp", input, info, false) == true); arma::mat output; diff --git a/src/mlpack/tests/linear_svm_test.cpp b/src/mlpack/tests/linear_svm_test.cpp index 58fc54f337..0d89ac77d0 100644 --- a/src/mlpack/tests/linear_svm_test.cpp +++ b/src/mlpack/tests/linear_svm_test.cpp @@ -930,27 +930,27 @@ TEMPLATE_TEST_CASE("LinearSVMLBFGSMultipleClasses", "[LinearSVMTest]", float, { for (size_t i = 0; i < points / 5; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; } @@ -965,27 +965,27 @@ TEMPLATE_TEST_CASE("LinearSVMLBFGSMultipleClasses", "[LinearSVMTest]", float, // Create test dataset. for (size_t i = 0; i < points / 5; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; } @@ -1029,27 +1029,27 @@ TEMPLATE_TEST_CASE("LinearSVMClassifySinglePointTest", "[LinearSVMTest]", float, for (size_t i = 0; i < points / 5; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; } @@ -1059,27 +1059,27 @@ TEMPLATE_TEST_CASE("LinearSVMClassifySinglePointTest", "[LinearSVMTest]", float, // Create test dataset. for (size_t i = 0; i < points / 5; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; } diff --git a/src/mlpack/tests/lmnn_test.cpp b/src/mlpack/tests/lmnn_test.cpp index d4c3621359..44eb0b0d66 100644 --- a/src/mlpack/tests/lmnn_test.cpp +++ b/src/mlpack/tests/lmnn_test.cpp @@ -411,7 +411,7 @@ double KnnAccuracy(const arma::mat& dataset, Map(labels(neighbors(j, i))) += 1 / std::pow(distances(j, i) + 1, 2); - size_t index = ConvTo::from(arma::find(Map + size_t index = ConvTo::From(arma::find(Map == arma::max(Map))); // Increase count if labels match. diff --git a/src/mlpack/tests/main_tests/hmm_test_utils.hpp b/src/mlpack/tests/main_tests/hmm_test_utils.hpp index 1645819d33..52203d0a93 100644 --- a/src/mlpack/tests/main_tests/hmm_test_utils.hpp +++ b/src/mlpack/tests/main_tests/hmm_test_utils.hpp @@ -49,7 +49,7 @@ struct InitHMMModel ++it) { arma::Col maxSeqs = - ConvTo>::from(arma::max(*it, 1)) + 1; + ConvTo>::From(arma::max(*it, 1)) + 1; maxEmissions = arma::max(maxEmissions, maxSeqs); } diff --git a/src/mlpack/tests/main_tests/image_converter_test.cpp b/src/mlpack/tests/main_tests/image_converter_test.cpp index dc935fecf9..3d12986bfa 100644 --- a/src/mlpack/tests/main_tests/image_converter_test.cpp +++ b/src/mlpack/tests/main_tests/image_converter_test.cpp @@ -44,7 +44,7 @@ TEST_CASE_METHOD(ImageConverterTestFixture, "LoadImageTest", TEST_CASE_METHOD(ImageConverterTestFixture, "SaveImageTest", "[ImageConverterMainTest][BindingTests]") { - arma::mat testimage = ConvTo::from( + arma::mat testimage = ConvTo::From( arma::randi>((5 * 5 * 3), 2)); SetInputParam>("input", {"test_image777.png", "test_image999.png"}); @@ -81,7 +81,7 @@ TEST_CASE_METHOD(ImageConverterTestFixture, "SaveImageTest", TEST_CASE_METHOD(ImageConverterTestFixture, "IncompleteTest", "[ImageConverterMainTest][BindingTests]") { - arma::mat testimage = ConvTo::from( + arma::mat testimage = ConvTo::From( arma::randi>((5 * 5 * 3), 2)); SetInputParam>("input", {"test_image777.png", "test_image999.png"}); @@ -99,7 +99,7 @@ TEST_CASE_METHOD(ImageConverterTestFixture, "IncompleteTest", TEST_CASE_METHOD(ImageConverterTestFixture, "InvalidInputTest", "[ImageConverterMainTest][BindingTests]") { - arma::mat testimage = ConvTo::from( + arma::mat testimage = ConvTo::From( arma::randi>((5 * 5 * 3), 2)); SetInputParam>("input", {"test_image777.png", "test_image999.png"}); @@ -119,7 +119,7 @@ TEST_CASE_METHOD(ImageConverterTestFixture, "InvalidInputTest", TEST_CASE_METHOD(ImageConverterTestFixture, "InvalidWidthTest", "[ImageConverterMainTest][BindingTests]") { - arma::mat testimage = ConvTo::from( + arma::mat testimage = ConvTo::From( arma::randi>((5 * 5 * 3), 2)); SetInputParam>("input", {"test_image777.png", "test_image999.png"}); @@ -138,7 +138,7 @@ TEST_CASE_METHOD(ImageConverterTestFixture, "InvalidWidthTest", TEST_CASE_METHOD(ImageConverterTestFixture, "InvalidChannelTest", "[ImageConverterMainTest][BindingTests]") { - arma::mat testimage = ConvTo::from( + arma::mat testimage = ConvTo::From( arma::randi>((5 * 5 * 3), 2)); SetInputParam>("input", {"test_image777.png", "test_image999.png"}); diff --git a/src/mlpack/tests/softmax_regression_test.cpp b/src/mlpack/tests/softmax_regression_test.cpp index 9a6f423751..57c2265b30 100644 --- a/src/mlpack/tests/softmax_regression_test.cpp +++ b/src/mlpack/tests/softmax_regression_test.cpp @@ -232,12 +232,12 @@ TEMPLATE_TEST_CASE("SoftmaxRegressionFitIntercept", "[SoftmaxRegressionTest]", arma::Row responses(1000); for (size_t i = 0; i < 500; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); responses[i] = 0; } for (size_t i = 500; i < 1000; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); responses[i] = 1; } @@ -251,12 +251,12 @@ TEMPLATE_TEST_CASE("SoftmaxRegressionFitIntercept", "[SoftmaxRegressionTest]", // Create a test set. for (size_t i = 0; i < 500; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); responses[i] = 0; } for (size_t i = 500; i < 1000; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); responses[i] = 1; } @@ -289,27 +289,27 @@ TEMPLATE_TEST_CASE("SoftmaxRegressionMultipleClasses", for (size_t i = 0; i < points / 5; ++i) { // TODO: when GaussianDistribution is templatized, remove the conv_to. - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; } @@ -323,27 +323,27 @@ TEMPLATE_TEST_CASE("SoftmaxRegressionMultipleClasses", // Create test dataset. for (size_t i = 0; i < points / 5; ++i) { - data.col(i) = ConvTo::from(g1.Random()); + data.col(i) = ConvTo::From(g1.Random()); labels(i) = 0; } for (size_t i = points / 5; i < (2 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g2.Random()); + data.col(i) = ConvTo::From(g2.Random()); labels(i) = 1; } for (size_t i = (2 * points) / 5; i < (3 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g3.Random()); + data.col(i) = ConvTo::From(g3.Random()); labels(i) = 2; } for (size_t i = (3 * points) / 5; i < (4 * points) / 5; ++i) { - data.col(i) = ConvTo::from(g4.Random()); + data.col(i) = ConvTo::From(g4.Random()); labels(i) = 3; } for (size_t i = (4 * points) / 5; i < points; ++i) { - data.col(i) = ConvTo::from(g5.Random()); + data.col(i) = ConvTo::From(g5.Random()); labels(i) = 4; }