Added Perceptron Tests

2018-01-15 20:49:11 +05:30
parent 737d6f531f
commit 61d6eeb7e9
2 changed files with 201 additions and 0 deletions
@@ -129,6 +129,7 @@ add_executable(mlpack_test
  main_tests/linear_regression_test.cpp
  main_tests/nbc_test.cpp
  main_tests/pca_test.cpp
+  main_tests/perceptron_test.cpp
  main_tests/preprocess_binarize_test.cpp
  main_tests/preprocess_imputer_test.cpp
  main_tests/preprocess_split_test.cpp
@@ -0,0 +1,200 @@
+/**
+ * @file perceptron_test.cpp
+ * @author Manish Kumar
+ *
+ * Test mlpackMain() of perceptron_main.cpp.
+ *
+ * mlpack is free software; you may redistribute it and/or modify it under the
+ * terms of the 3-clause BSD license.  You should have received a copy of the
+ * 3-clause BSD license along with mlpack.  If not, see
+ * http://www.opensource.org/licenses/BSD-3-Clause for more information.
+ */
+#define BINDING_TYPE BINDING_TYPE_TEST
+
+#include <mlpack/core.hpp>
+static const std::string testName = "Perceptron";
+
+#include <mlpack/core/util/mlpack_main.hpp>
+#include <mlpack/methods/perceptron/perceptron_main.cpp>
+#include "test_helper.hpp"
+
+#include <boost/test/unit_test.hpp>
+#include "../test_tools.hpp"
+
+using namespace mlpack;
+
+struct PerceptronTestFixture
+{
+ public:
+  PerceptronTestFixture()
+  {
+    // Cache in the options for this program.
+    CLI::RestoreSettings(testName);
+  }
+
+  ~PerceptronTestFixture()
+  {
+    // Clear the settings.
+    CLI::ClearSettings();
+  }
+};
+
+BOOST_FIXTURE_TEST_SUITE(PerceptronMainTest,
+                         PerceptronTestFixture);
+
+/**
+ * Ensure that we get desired dimensions when both training
+ * data and labels are passed.
+ */
+BOOST_AUTO_TEST_CASE(PerceptronOutputDimensionTest)
+{
+  arma::mat inputData;
+  if (!data::Load("trainSet.csv", inputData))
+    BOOST_FAIL("Cannot load train dataset trainSet.csv!");
+
+  // Get the labels out.
+  arma::Row<size_t> labels(inputData.n_cols);
+  for (size_t i = 0; i < inputData.n_cols; ++i)
+    labels[i] = inputData(inputData.n_rows - 1, i);
+
+  // Delete the last row containing labels from input dataset.
+  inputData.shed_row(inputData.n_rows - 1);
+
+  arma::mat testData;
+  if (!data::Load("testSet.csv", testData))
+    BOOST_FAIL("Cannot load test dataset testSet.csv!");
+
+  // Delete the last row containing labels from test dataset.
+  testData.shed_row(testData.n_rows - 1);
+
+  size_t testSize = testData.n_cols;
+
+  // Input training data.
+  SetInputParam("training", std::move(inputData));
+  SetInputParam("labels", std::move(labels));
+
+  // Input test data.
+  SetInputParam("test", std::move(testData));
+
+  mlpackMain();
+
+  // Check that number of output points are equal to number of input points.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_cols,
+                      testSize);
+
+  // Check output have only single row.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_rows, 1);
+}
+
+/**
+ * Check that last row of input file is used as labels
+ * when labels are not passed specifically.
+ */
+BOOST_AUTO_TEST_CASE(PerceptronLabelsLessDimensionTest)
+{
+  arma::mat inputData;
+  if (!data::Load("trainSet.csv", inputData))
+    BOOST_FAIL("Cannot load train dataset trainSet.csv!");
+
+  arma::mat testData;
+  if (!data::Load("testSet.csv", testData))
+    BOOST_FAIL("Cannot load test dataset testSet.csv!");
+
+  // Delete the last row containing labels from test dataset.
+  testData.shed_row(testData.n_rows - 1);
+
+  size_t testSize = testData.n_cols;
+
+  // Input training data.
+  SetInputParam("training", std::move(inputData));
+
+  // Input test data.
+  SetInputParam("test", std::move(testData));
+
+  mlpackMain();
+
+  // Check that number of output points are equal to number of input points.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_cols,
+                      testSize);
+
+  // Check output have only single row.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_rows, 1);
+}
+
+/**
+ * Ensure that saved model can be used again.
+ */
+BOOST_AUTO_TEST_CASE(PerceptronModelReuseTest)
+{
+  arma::mat inputData;
+  if (!data::Load("trainSet.csv", inputData))
+    BOOST_FAIL("Cannot load train dataset trainSet.csv!");
+
+  arma::mat testData;
+  if (!data::Load("testSet.csv", testData))
+    BOOST_FAIL("Cannot load test dataset testSet.csv!");
+
+  // Delete the last row containing labels from test dataset.
+  testData.shed_row(testData.n_rows - 1);
+
+  size_t testSize = testData.n_cols;
+
+  // Input training data.
+  SetInputParam("training", std::move(inputData));
+
+  // Input test data.
+  SetInputParam("test", std::move(testData));
+
+  mlpackMain();
+
+  arma::Row<size_t> output;
+  output = std::move(CLI::GetParam<arma::Row<size_t>>("output"));
+
+  // Reset passed parameters.
+  CLI::GetSingleton().Parameters()["training"].wasPassed = false;
+  CLI::GetSingleton().Parameters()["test"].wasPassed = false;
+
+  if (!data::Load("testSet.csv", testData))
+    BOOST_FAIL("Cannot load test dataset testSet.csv!");
+
+  // Delete the last row containing labels from test dataset.
+  testData.shed_row(testData.n_rows - 1);
+
+  // Input trained model.
+  SetInputParam("test", std::move(testData));
+  SetInputParam("input_model",
+                std::move(CLI::GetParam<PerceptronModel>("output_model")));
+
+  mlpackMain();
+
+  // Check that number of output points are equal to number of input points.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_cols,
+                      testSize);
+
+  // Check output have only single row.
+  BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::Row<size_t>>("output").n_rows, 1);
+
+  // Check that initial output and final output matrix
+  // using saved model are same.
+  CheckMatrices(output, CLI::GetParam<arma::Row<size_t>>("output"));
+}
+
+/**
+ * Ensure that max_iterations is always non-negative.
+ */
+BOOST_AUTO_TEST_CASE(PerceptronMaxItrTest)
+{
+  arma::mat inputData;
+  if (!data::Load("trainSet.csv", inputData))
+    BOOST_FAIL("Cannot load train dataset trainSet.csv!");
+
+  // Input training data.
+  SetInputParam("training", std::move(inputData));
+  SetInputParam("max_iterations", (int) -1);
+
+  Log::Fatal.ignoreInput = true;
+  BOOST_REQUIRE_THROW(mlpackMain(), std::runtime_error);
+  Log::Fatal.ignoreInput = false;
+}
+
+BOOST_AUTO_TEST_SUITE_END();