migrate ann_* and related test from boost to catch2

src/mlpack/tests/CMakeLists.txt

@@ -1,10 +1,5 @@
 # mlpack test executable.
 add_executable(mlpack_test
-  ann_dist_test.cpp
-  ann_layer_test.cpp
-  ann_regularizer_test.cpp
-  ann_test_tools.hpp
-  ann_visitor_test.cpp
   arma_extend_test.cpp
   async_learning_test.cpp
   augmented_rnns_tasks_test.cpp
@@ -147,6 +142,11 @@ add_executable(mlpack_catch_test
   adaboost_test.cpp
   akfn_test.cpp
   aknn_test.cpp
+  ann_dist_test.cpp
+  ann_layer_test.cpp
+  ann_regularizer_test.cpp
+  ann_test_tools.hpp
+  ann_visitor_test.cpp
   armadillo_svd_test.cpp
   bias_svd_test.cpp
   block_krylov_svd_test.cpp
@@ -223,7 +223,6 @@ add_custom_command(TARGET mlpack_test
 
 # The list of long running parallel tests
 set(parallel_tests
-  "ANNLayerTest;"
   "AsyncLearningTest;"
   "LocalCoordinateCodingTest;"
   "FeedForwardNetworkTest;"

src/mlpack/tests/ann_dist_test.cpp

@@ -16,20 +16,18 @@
 #include <mlpack/methods/ann/dists/normal_distribution.hpp>
 #include <mlpack/methods/ann/init_rules/random_init.hpp>
 
-#include <boost/test/unit_test.hpp>
-#include "test_tools.hpp"
+#include "catch.hpp"
+#include "test_catch_tools.hpp"
 
 #include <mlpack/methods/ann/activation_functions/logistic_function.hpp>
 
 using namespace mlpack;
 using namespace mlpack::ann;
 
-BOOST_AUTO_TEST_SUITE(ANNDistTest);
-
 /**
  * Simple bernoulli distribution module test.
  */
-BOOST_AUTO_TEST_CASE(SimpleBernoulliDistributionTest)
+TEST_CASE("SimpleBernoulliDistributionTest", "[ANNDistTest]")
 {
   arma::mat param = arma::mat("1 1 0");
   BernoulliDistribution<> module(param, false);
@@ -43,7 +41,7 @@ BOOST_AUTO_TEST_CASE(SimpleBernoulliDistributionTest)
 /**
  * Jacobian bernoulli distribution module test when we don't apply logistic.
  */
-BOOST_AUTO_TEST_CASE(JacobianBernoulliDistributionTest)
+TEST_CASE("JacobianBernoulliDistributionTest", "[ANNDistTest]")
 {
   for (size_t i = 0; i < 5; ++i)
   {
@@ -78,15 +76,14 @@ BOOST_AUTO_TEST_CASE(JacobianBernoulliDistributionTest)
     }
 
     module.LogProbBackward(target, jacobianB);
-    BOOST_REQUIRE_LE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))),
-        1e-5);
+    REQUIRE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))) <= 1e-5);
   }
 }
 
 /**
  * Jacobian bernoulli distribution module test when we apply logistic.
  */
-BOOST_AUTO_TEST_CASE(JacobianBernoulliDistributionLogisticTest)
+TEST_CASE("JacobianBernoulliDistributionLogisticTest", "[ANNDistTest]")
 {
   for (size_t i = 0; i < 5; ++i)
   {
@@ -124,15 +121,14 @@ BOOST_AUTO_TEST_CASE(JacobianBernoulliDistributionLogisticTest)
     }
 
     module.LogProbBackward(target, jacobianB);
-    BOOST_REQUIRE_LE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))),
-        3e-5);
+    REQUIRE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))) <= 3e-5);
   }
 }
 
 /**
  * Normal Distribution module test.
  */
-BOOST_AUTO_TEST_CASE(NormalDistributionTest)
+TEST_CASE("NormalDistributionTest", "[ANNDistTest]")
 {
   arma::vec mu = {1.1, 1.2, 1.5, 1.7};
   arma::vec sigma = {0.1, 0.11, 0.5, 0.23};
@@ -145,29 +141,29 @@ BOOST_AUTO_TEST_CASE(NormalDistributionTest)
   normalDist.LogProbability(x, prob);
 
   // Testing output of log probability for some random mu, sigma and x.
-  BOOST_REQUIRE_CLOSE(prob[0], 1.2586464, 1e-3);
-  BOOST_REQUIRE_CLOSE(prob[1], 0.8751131, 1e-3);
-  BOOST_REQUIRE_CLOSE(prob[2], -0.30579138, 1e-3);
-  BOOST_REQUIRE_CLOSE(prob[3], -5.498411, 1e-3);
+  REQUIRE(prob[0] == Approx( 1.2586464).epsilon(1e-5));
+  REQUIRE(prob[1] == Approx( 0.8751131).epsilon(1e-5));
+  REQUIRE(prob[2] == Approx( -0.30579138).epsilon(1e-5));
+  REQUIRE(prob[3] == Approx( -5.498411).epsilon(1e-5));
 
   arma::vec dmu, dsigma;
   normalDist.ProbBackward(x, dmu, dsigma);
 
   // Testing output of dmu and dsigma for some random mu, sigma and x.
-  BOOST_REQUIRE_CLOSE(dmu[0], -17.603287, 1e-3);
-  BOOST_REQUIRE_CLOSE(dsigma[0], -26.40487, 1e-3);
-  BOOST_REQUIRE_CLOSE(dmu[1], -19.827663, 1e-3);
-  BOOST_REQUIRE_CLOSE(dsigma[1], -3.7852707, 1e-3);
-  BOOST_REQUIRE_CLOSE(dmu[2], 0.5892323, 1e-3);
-  BOOST_REQUIRE_CLOSE(dsigma[2], -1.2373875, 1e-3);
-  BOOST_REQUIRE_CLOSE(dmu[3], 0.061901994, 1e-3);
-  BOOST_REQUIRE_CLOSE(dsigma[3], 0.19751444, 1e-3);
+  REQUIRE(dmu[0] == Approx( -17.603287).epsilon(1e-5));
+  REQUIRE(dsigma[0] == Approx( -26.40487).epsilon(1e-5));
+  REQUIRE(dmu[1] == Approx( -19.827663).epsilon(1e-5));
+  REQUIRE(dsigma[1] == Approx( -3.7852707).epsilon(1e-5));
+  REQUIRE(dmu[2] == Approx( 0.5892323).epsilon(1e-5));
+  REQUIRE(dsigma[2] == Approx( -1.2373875).epsilon(1e-5));
+  REQUIRE(dmu[3] == Approx( 0.061901994).epsilon(1e-5));
+  REQUIRE(dsigma[3] == Approx( 0.19751444).epsilon(1e-5));
 }
 
 /**
  * Jacobian Normal Distribution module test for mean.
  */
-BOOST_AUTO_TEST_CASE(JacobianNormalDistributionMeanTest)
+TEST_CASE("JacobianNormalDistributionMeanTest", "[ANNDistTest]")
 {
   for (size_t i = 0; i < 5; i++)
   {
@@ -226,15 +222,14 @@ BOOST_AUTO_TEST_CASE(JacobianNormalDistributionMeanTest)
       jacobianB.col(k) = deltaMu % deriv;
     }
 
-    BOOST_REQUIRE_LE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))),
-        5e-3);
+    REQUIRE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))) <= 5e-3);
   }
 }
 
 /**
  * Jacobian Normal Distribution module test for standard deviation.
  */
-BOOST_AUTO_TEST_CASE(JacobianNormalDistributionStandardDeviationTest)
+TEST_CASE("JacobianNormalDistributionStandardDeviationTest", "[ANNDistTest]")
 {
   for (size_t i = 0; i < 5; i++)
   {
@@ -293,10 +288,6 @@ BOOST_AUTO_TEST_CASE(JacobianNormalDistributionStandardDeviationTest)
       jacobianB.col(k) = deltaSigma % deriv;
     }
 
-    BOOST_REQUIRE_LE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))),
-        5e-3);
+    REQUIRE(arma::max(arma::max(arma::abs(jacobianA - jacobianB))) <= 5e-3);
   }
 }
-
-
-BOOST_AUTO_TEST_SUITE_END();

src/mlpack/tests/ann_regularizer_test.cpp

@@ -16,16 +16,14 @@
 #include <mlpack/methods/ann/init_rules/random_init.hpp>
 #include <mlpack/methods/ann/regularizer/regularizer.hpp>
 
-#include <boost/test/unit_test.hpp>
+#include "catch.hpp"
 #include "ann_test_tools.hpp"
-#include "serialization.hpp"
+#include "serialization_catch.hpp"
 
 using namespace mlpack;
 using namespace mlpack::ann;
 
-BOOST_AUTO_TEST_SUITE(ANNRegularizerTest);
-
-BOOST_AUTO_TEST_CASE(GradientL1RegularizerTest)
+TEST_CASE("GradientL1RegularizerTest", "[ANNRegularizerTest]")
 {
   // Add function gradient instantiation.
   struct GradientFunction
@@ -51,10 +49,10 @@ BOOST_AUTO_TEST_CASE(GradientL1RegularizerTest)
     L1Regularizer reg;
   } function;
 
-  BOOST_REQUIRE_LE(CheckRegularizerGradient(function), 1e-4);
+  REQUIRE(CheckRegularizerGradient(function) <= 1e-4);
 }
 
-BOOST_AUTO_TEST_CASE(GradientL2RegularizerTest)
+TEST_CASE("GradientL2RegularizerTest", "[ANNRegularizerTest]")
 {
   // Add function gradient instantiation.
   struct GradientFunction
@@ -80,10 +78,10 @@ BOOST_AUTO_TEST_CASE(GradientL2RegularizerTest)
     L2Regularizer reg;
   } function;
 
-  BOOST_REQUIRE_LE(CheckRegularizerGradient(function), 1e-4);
+  REQUIRE(CheckRegularizerGradient(function) <= 1e-4);
 }
 
-BOOST_AUTO_TEST_CASE(GradientOrthogonalRegularizerTest)
+TEST_CASE("GradientOrthogonalRegularizerTest", "[ANNRegularizerTest]")
 {
   // Add function gradient instantiation.
   struct GradientFunction
@@ -111,7 +109,5 @@ BOOST_AUTO_TEST_CASE(GradientOrthogonalRegularizerTest)
     OrthogonalRegularizer reg;
   } function;
 
-  BOOST_REQUIRE_LE(CheckRegularizerGradient(function), 1e-4);
+  REQUIRE(CheckRegularizerGradient(function) <= 1e-4);
 }
-
-BOOST_AUTO_TEST_SUITE_END();

src/mlpack/tests/ann_visitor_test.cpp

@@ -15,18 +15,16 @@
 #include <mlpack/methods/ann/visitor/weight_set_visitor.hpp>
 #include <mlpack/methods/ann/visitor/reset_visitor.hpp>
 
-#include <boost/test/unit_test.hpp>
-#include "test_tools.hpp"
+#include "catch.hpp"
+#include "test_catch_tools.hpp"
 
 using namespace mlpack;
 using namespace mlpack::ann;
 
-BOOST_AUTO_TEST_SUITE(ANNVisitorTest);
-
 /**
  * Test that the BiasSetVisitor works properly.
  */
-BOOST_AUTO_TEST_CASE(BiasSetVisitorTest)
+TEST_CASE("BiasSetVisitorTest", "[ANNVisitorTest]")
 {
   LayerTypes<> linear = new Linear<>(10, 10);
 
@@ -43,16 +41,14 @@ BOOST_AUTO_TEST_CASE(BiasSetVisitorTest)
 
   size_t biasSize = boost::apply_visitor(BiasSetVisitor(weight, 0), linear);
 
-  BOOST_REQUIRE_EQUAL(biasSize, 10);
+  REQUIRE(biasSize == 10);
 
   arma::mat input(10, 1), output;
   input.randu();
 
   boost::apply_visitor(ForwardVisitor(input, output), linear);
 
-  BOOST_REQUIRE_EQUAL(arma::accu(output), 55);
+  REQUIRE(arma::accu(output) == 55);
 
   boost::apply_visitor(DeleteVisitor(), linear);
 }
-
-BOOST_AUTO_TEST_SUITE_END();

src/mlpack/tests/test_catch_tools.hpp

@@ -33,7 +33,7 @@ inline void CheckMatrices(const arma::mat& a,
   for (size_t i = 0; i < a.n_elem; ++i)
   {
     if (std::abs(a[i]) < tolerance / 2)
-      REQUIRE(b[i] == Approx(0.0).margin(tolerance / 200));
+      REQUIRE(b[i] == Approx(0.0).margin(tolerance / 2));
     else
       REQUIRE(a[i] == Approx(b[i]).epsilon(tolerance / 100));
   }
@@ -62,7 +62,7 @@ inline void CheckMatrices(const arma::cube& a,
   for (size_t i = 0; i < a.n_elem; ++i)
   {
     if (std::abs(a[i]) < tolerance / 2)
-      REQUIRE(b[i] == Approx(0.0).margin(tolerance / 200));
+      REQUIRE(b[i] == Approx(0.0).margin(tolerance / 2));
     else
       REQUIRE(a[i] == Approx(b[i]).epsilon(tolerance / 100));
   }