Merge pull request #2652 from jeffin143/asyn-aug-test

Migrate Augmentated_rnn and Async_Learning Test to catch2

src/mlpack/tests/CMakeLists.txt

@@ -1,7 +1,5 @@
 # mlpack test executable.
 add_executable(mlpack_test
-  async_learning_test.cpp
-  augmented_rnns_tasks_test.cpp
   callback_test.cpp
   cf_test.cpp
   dcgan_test.cpp
@@ -88,6 +86,8 @@ add_executable(mlpack_catch_test
   ann_visitor_test.cpp
   armadillo_svd_test.cpp
   arma_extend_test.cpp
+  async_learning_test.cpp
+  augmented_rnns_tasks_test.cpp
   bayesian_linear_regression_test.cpp
   bias_svd_test.cpp
   binarize_test.cpp
@@ -227,7 +227,6 @@ add_custom_command(TARGET mlpack_test
 
 # The list of long running parallel tests
 set(parallel_tests
-  "AsyncLearningTest;"
   "LocalCoordinateCodingTest;"
   "GMMTest;"
   "CFTest;"

src/mlpack/tests/async_learning_test.cpp

@@ -24,17 +24,15 @@
 
 #include <ensmallen.hpp>
 
-#include <boost/test/unit_test.hpp>
-#include "test_tools.hpp"
+#include "catch.hpp"
 
 using namespace mlpack;
 using namespace mlpack::ann;
 using namespace mlpack::rl;
 
-BOOST_AUTO_TEST_SUITE(AsyncLearningTest);
 
 // Test async one step q-learning in Cart Pole.
-BOOST_AUTO_TEST_CASE(OneStepQLearningTest)
+TEST_CASE("OneStepQLearningTest", "[AsyncLearningTest]")
 {
   /**
    * This is for the Travis CI server, in your own machine you should use more
@@ -106,11 +104,11 @@ BOOST_AUTO_TEST_CASE(OneStepQLearningTest)
     }
   }
 
-  BOOST_REQUIRE_EQUAL(success, true);
+  REQUIRE(success == true);
 }
 
 // Test async one step Sarsa in Cart Pole.
-BOOST_AUTO_TEST_CASE(OneStepSarsaTest)
+TEST_CASE("OneStepSarsaTest", "[AsyncLearningTest]")
 {
   /**
    * This is for the Travis CI server, in your own machine you shuold use more
@@ -184,11 +182,11 @@ BOOST_AUTO_TEST_CASE(OneStepSarsaTest)
     }
   }
 
-  BOOST_REQUIRE_EQUAL(success, true);
+  REQUIRE(success == true);
 }
 
 // Test async n step q-learning in Cart Pole.
-BOOST_AUTO_TEST_CASE(NStepQLearningTest)
+TEST_CASE("NStepQLearningTest", "[AsyncLearningTest]")
 {
   /**
    * This is for the Travis CI server, in your own machine you shuold use more
@@ -233,7 +231,7 @@ BOOST_AUTO_TEST_CASE(NStepQLearningTest)
   {
     size_t maxEpisode = 100000;
     if (testEpisodes > maxEpisode)
-      BOOST_REQUIRE(false);
+      REQUIRE(false);
     testEpisodes++;
     rewards[pos++] = reward;
     pos %= rewards.n_elem;
@@ -249,5 +247,3 @@ BOOST_AUTO_TEST_CASE(NStepQLearningTest)
   agent.Train(measure);
   Log::Debug << "Total test episodes: " << testEpisodes << std::endl;
 }
-
-BOOST_AUTO_TEST_SUITE_END();

src/mlpack/tests/augmented_rnns_tasks_test.cpp

@@ -22,8 +22,7 @@
 #include <mlpack/methods/ann/augmented/tasks/add.hpp>
 #include <mlpack/methods/ann/augmented/tasks/score.hpp>
 
-#include <boost/test/unit_test.hpp>
-#include "test_tools.hpp"
+#include "catch.hpp"
 
 using std::vector;
 using std::pair;
@@ -51,8 +50,10 @@ class HardCodedCopyModel
     size_t zeroCnt = 0, oneCnt = 0;
     for (size_t i = 1; i < input.n_rows; i += 2)
     {
-      size_t& addVar = (input.at(i, 0) == 0) ? zeroCnt : oneCnt;
-      ++addVar;
+      if (input.at(i, 0) == 0)
+        ++zeroCnt;
+      else
+        ++oneCnt;
     }
     assert(oneCnt % zeroCnt == 0);
     nRepeats = oneCnt / zeroCnt;
@@ -158,7 +159,7 @@ class HardCodedAddModel
     predictors = predictors.t();
     predictors.reshape(3, predictors.n_elem / 3);
     assert(predictors.n_rows == 3);
-    int num_A = 0, num_B = 0;
+    size_t num_A = 0, num_B = 0;
     bool num = false; // True iff we have already seen the separating symbol.
     size_t cnt = 0;
     for (size_t i = 0; i < predictors.n_cols; ++i)
@@ -219,12 +220,11 @@ class HardCodedAddModel
   }
 };
 
-BOOST_AUTO_TEST_SUITE(AugmentedRNNsTasks);
 
 // Test of CopyTask instance generator.
 // The data from generator is fed to the dummy hard-coded model above
 // that should be able to solve the task perfectly.
-BOOST_AUTO_TEST_CASE(CopyTaskTest)
+TEST_CASE("CopyTaskTest", "[AugmentedRNNsTasks]")
 {
   // Check the setup on various lengths...
   for (size_t maxLen = 2; maxLen <= 16; ++maxLen)
@@ -242,8 +242,7 @@ BOOST_AUTO_TEST_CASE(CopyTaskTest)
       arma::field<arma::mat> predResponse;
       model.Predict(testPredictor, predResponse);
       // A single failure is a failure.
-      BOOST_REQUIRE_GE(SequencePrecision<arma::mat>(testResponse, predResponse),
-                       0.99);
+      REQUIRE(SequencePrecision<arma::mat>(testResponse, predResponse) >= 0.99);
     }
   }
 }
@@ -251,7 +250,7 @@ BOOST_AUTO_TEST_CASE(CopyTaskTest)
 // Test of SortTask instance generator.
 // The data from generator is fed to the dummy hard-coded model above
 // that should be able to solve the task perfectly.
-BOOST_AUTO_TEST_CASE(SortTaskTest)
+TEST_CASE("SortTaskTest", "[AugmentedRNNsTasks]")
 {
   size_t bitLen = 5;
   for (size_t maxLen = 2; maxLen <= 16; ++maxLen)
@@ -266,15 +265,14 @@ BOOST_AUTO_TEST_CASE(SortTaskTest)
     arma::field<arma::mat> predResponse;
     model.Predict(testPredictor, predResponse);
     // A single failure is a failure.
-    BOOST_REQUIRE_GE(SequencePrecision<arma::mat>(testResponse, predResponse),
-                     0.99);
+    REQUIRE(SequencePrecision<arma::mat>(testResponse, predResponse) >= 0.99);
   }
 }
 
 // Test of AddTask instance generator.
 // The data from generator is fed to the dummy hard-coded model above
 // that should be able to solve the task perfectly.
-BOOST_AUTO_TEST_CASE(AddTaskTest)
+TEST_CASE("AddTaskTest", "[AugmentedRNNsTasks]")
 {
   for (size_t bitLen = 2; bitLen <= 16; ++bitLen)
   {
@@ -288,9 +286,6 @@ BOOST_AUTO_TEST_CASE(AddTaskTest)
     arma::field<arma::mat> predResponse;
     model.Predict(testPredictor, predResponse);
     // A single failure is a failure.
-    BOOST_REQUIRE_GE(SequencePrecision<arma::mat>(testResponse, predResponse),
-                     0.99);
+    REQUIRE(SequencePrecision<arma::mat>(testResponse, predResponse) >= 0.99);
   }
 }
-
-BOOST_AUTO_TEST_SUITE_END();