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Optimized Tests

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This commit is contained in:
manish7294
2018-01-31 22:07:41 +05:30
parent c34144853e
commit 4562f1c6b2
1 changed files with 94 additions and 132 deletions
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src/mlpack/tests/main_tests/sparse_coding_test.cpp
+94 -132
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@@ -48,40 +48,38 @@ BOOST_FIXTURE_TEST_SUITE(SparseCodingMainTest, SparseCodingTestFixture);
*/
BOOST_AUTO_TEST_CASE(SparseCodingOutputDimensionTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Generate test dataset.
mat testData;
testData = inputData.cols(450, 499);
// Generate train dataset.
inputData.shed_cols(450, 499);
mat initialDictionary = inputData.cols(0, 1);
// Input data.
SetInputParam("training", std::move(inputData));
SetInputParam("atoms", (int) 30);
SetInputParam("max_iterations", (int) 500);
SetInputParam("normalize", (bool) true);
SetInputParam("atoms", (int) 2);
SetInputParam("max_iterations", (int) 100);
SetInputParam("test", std::move(testData));
mlpackMain();
// Check that number of output dictionary points are equals number of atoms.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_cols, 30);
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_cols, 2);
// Check that number of output dictionary rows equal number of input rows
// which equal 784 for each data point.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_rows, 784);
// which equal 4 for each data point.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_rows, 4);
// Check that number of output points are equal to number of test points.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_cols, 50);
// Test file contains 63 data points.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_cols, 63);
// Check that number of output codes rows equal number of atoms.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_rows, 30);
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_rows, 2);
}
/**
@@ -90,35 +88,22 @@ BOOST_AUTO_TEST_CASE(SparseCodingOutputDimensionTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingNormalizationTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Generate test dataset.
mat testData;
testData = inputData.cols(450, 499);
// Generate train dataset.
inputData.shed_cols(450, 499);
// Generate initial dictionary.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("max_iterations", (int) 10);
SetInputParam("normalize", (bool) true);
mlpackMain();
mat initialDictionary =
std::move(CLI::GetParam<arma::mat>("dictionary"));
mat initialDictionary = inputData.cols(0, 1);
// Train for normalization set to true.
// Input data.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("atoms", (int) 2);
SetInputParam("initial_dictionary", initialDictionary);
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
@@ -147,7 +132,7 @@ BOOST_AUTO_TEST_CASE(SparseCodingNormalizationTest)
// Input data.
SetInputParam("training", std::move(inputData));
SetInputParam("atoms", (int) 30);
SetInputParam("atoms", (int) 2);
SetInputParam("initial_dictionary", std::move(initialDictionary));
SetInputParam("max_iterations", (int) 100);
SetInputParam("test", std::move(testData));
@@ -167,8 +152,9 @@ BOOST_AUTO_TEST_CASE(SparseCodingNormalizationTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingBoundsTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Test for L1 value.
@@ -241,8 +227,9 @@ BOOST_AUTO_TEST_CASE(SparseCodingBoundsTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingReqAtomsTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Input training data.
SetInputParam("training", std::move(inputData));
@@ -258,22 +245,16 @@ BOOST_AUTO_TEST_CASE(SparseCodingReqAtomsTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingModelVerTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Input data.
SetInputParam("training", std::move(inputData));
SetInputParam("atoms", (int) 30);
SetInputParam("max_iterations", (int) 10);
SetInputParam("normalize", (bool) true);
mlpackMain();
mat initialDictionary =
std::move(CLI::GetParam<arma::mat>("dictionary"));
mat initialDictionary = inputData.cols(0, 1);
// Input trained model and initial_dictionary.
SetInputParam("input_model",
@@ -291,29 +272,22 @@ BOOST_AUTO_TEST_CASE(SparseCodingModelVerTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingAtomsVerTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Input data.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("max_iterations", (int) 10);
SetInputParam("normalize", (bool) true);
mlpackMain();
mat initialDictionary =
std::move(CLI::GetParam<arma::mat>("dictionary"));
mat initialDictionary = inputData.cols(0, 1); // 2 points.
// Input data and initial_dictionary.
SetInputParam("training", std::move(inputData));
SetInputParam("atoms", (int) 40); // Invalid.
SetInputParam("initial_dictionary", std::move(initialDictionary));
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
Log::Fatal.ignoreInput = true;
BOOST_REQUIRE_THROW(mlpackMain(), std::runtime_error);
@@ -326,29 +300,23 @@ BOOST_AUTO_TEST_CASE(SparseCodingAtomsVerTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingRowsVerTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Input data.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
mlpackMain();
mat initialDictionary =
std::move(CLI::GetParam<arma::mat>("dictionary"));
mat initialDictionary = inputData.cols(0, 1);
// Trim inputData.
inputData.shed_rows(100, 400);
inputData.shed_rows(1, 2);
// Input data and initial_dictionary.
SetInputParam("training", std::move(inputData)); // Invalid Data.
SetInputParam("atoms", (int) 30);
SetInputParam("atoms", (int) 2);
SetInputParam("initial_dictionary", std::move(initialDictionary));
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
@@ -364,27 +332,24 @@ BOOST_AUTO_TEST_CASE(SparseCodingRowsVerTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingDataDimensionalityTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Generate test dataset.
mat testData;
testData = inputData.cols(450, 499);
mat initialDictionary = inputData.cols(0, 1);
// Trim testData.
testData.shed_rows(100, 400);
// Generate train dataset.
inputData.shed_cols(450, 499);
testData.shed_rows(1, 2);
// Input data.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("atoms", (int) 2);
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
SetInputParam("test", std::move(testData));
Log::Fatal.ignoreInput = true;
@@ -397,22 +362,18 @@ BOOST_AUTO_TEST_CASE(SparseCodingDataDimensionalityTest)
*/
BOOST_AUTO_TEST_CASE(SparseCodingModelReuseTest)
{
mat inputData;
inputData.load("mnist_first250_training_4s_and_9s.arm");
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Shuffle input dataset.
inputData = shuffle(inputData);
// Generate test dataset.
mat testData;
testData = inputData.cols(450, 499);
// Generate train dataset.
inputData.shed_cols(450, 499);
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
// Input data.
SetInputParam("training", inputData);
SetInputParam("atoms", (int) 30);
SetInputParam("atoms", (int) 2);
SetInputParam("max_iterations", (int) 100);
SetInputParam("normalize", (bool) true);
SetInputParam("test", testData);
@@ -440,17 +401,18 @@ BOOST_AUTO_TEST_CASE(SparseCodingModelReuseTest)
mlpackMain();
// Check that number of output dictionary points are equals number of atoms.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_cols, 30);
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_cols, 2);
// Check that number of output dictionary rows equal number of input rows
// which equal 784 for each data point.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_rows, 784);
// which equal 4 for each data point.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("dictionary").n_rows, 4);
// Check that number of output points are equal to number of test points.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_cols, 50);
// Test file contains 63 data points.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_cols, 63);
// Check that number of output codes rows equal number of atoms.
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_rows, 30);
BOOST_REQUIRE_EQUAL(CLI::GetParam<arma::mat>("codes").n_rows, 2);
// Check that initial outputs and final outputs
// using two models model are same.
@@ -466,12 +428,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffMaxItrTest)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);
@@ -522,12 +484,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffObjToleranceTest)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);
@@ -575,12 +537,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffNewtonToleranceTest)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);
@@ -628,12 +590,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffL1Test)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);
@@ -681,12 +643,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffL2Test)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);
@@ -734,12 +696,12 @@ BOOST_AUTO_TEST_CASE(SparseCodingDiffL1L2Test)
{
arma::mat inputData;
if (!data::Load("iris_train.csv", inputData))
BOOST_FAIL("Cannot load train dataset trainSet.csv!");
BOOST_FAIL("Cannot load train dataset iris_train.csv!");
// Load test dataset.
arma::mat testData;
if (!data::Load("iris_test.csv", testData))
BOOST_FAIL("Cannot load test dataset testSet.csv!");
BOOST_FAIL("Cannot load test dataset iris_test.csv!");
mat initialDictionary = inputData.cols(0, 1);