[mlpack-git] master: Build the AdaDelta test. (322ff1c)

[gitdub at mlpack.org]

Repository : https://github.com/mlpack/mlpack
On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/80943dd398d652aa5ccb8461726a710d04fae925...322ff1c0622c7574800014f21d8a537c68101b5f

>---------------------------------------------------------------

commit 322ff1c0622c7574800014f21d8a537c68101b5f
Author: marcus <marcus.edel at fu-berlin.de>
Date:   Fri Mar 18 13:23:19 2016 +0100

    Build the AdaDelta test.


>---------------------------------------------------------------

322ff1c0622c7574800014f21d8a537c68101b5f
 src/mlpack/tests/CMakeLists.txt     |  1 +
 src/mlpack/tests/ada_delta_test.cpp | 61 ++-----------------------------------
 2 files changed, 4 insertions(+), 58 deletions(-)

diff --git a/src/mlpack/tests/CMakeLists.txt b/src/mlpack/tests/CMakeLists.txt
index 6539f2a..4a33625 100644
--- a/src/mlpack/tests/CMakeLists.txt
+++ b/src/mlpack/tests/CMakeLists.txt
@@ -4,6 +4,7 @@ add_executable(mlpack_test
   activation_functions_test.cpp
   adaboost_test.cpp
   adam_test.cpp
+  ada_delta_test.cpp
   allkfn_test.cpp
   allknn_test.cpp
   allkrann_search_test.cpp
diff --git a/src/mlpack/tests/ada_delta_test.cpp b/src/mlpack/tests/ada_delta_test.cpp
index 01fdd63..8ff716e 100644
--- a/src/mlpack/tests/ada_delta_test.cpp
+++ b/src/mlpack/tests/ada_delta_test.cpp
@@ -1,6 +1,7 @@
 /**
  * @file ada_delta_test.cpp
  * @author Marcus Edel
+ * @author Vasanth Kalingeri
  *
  * Tests the AdaDelta optimizer
  */
@@ -8,38 +9,25 @@
 
 #include <mlpack/core/optimizers/adadelta/ada_delta.hpp>
 #include <mlpack/core/optimizers/sgd/test_function.hpp>
-
 #include <mlpack/methods/logistic_regression/logistic_regression.hpp>
 
-#include <mlpack/methods/ann/ffn.hpp>
-#include <mlpack/methods/ann/init_rules/random_init.hpp>
-#include <mlpack/methods/ann/performance_functions/mse_function.hpp>
-#include <mlpack/methods/ann/layer/binary_classification_layer.hpp>
-#include <mlpack/methods/ann/layer/bias_layer.hpp>
-#include <mlpack/methods/ann/layer/linear_layer.hpp>
-#include <mlpack/methods/ann/layer/base_layer.hpp>
-
 #include <boost/test/unit_test.hpp>
 #include "old_boost_test_definitions.hpp"
 
 using namespace arma;
-using namespace mlpack;
 using namespace mlpack::optimization;
 using namespace mlpack::optimization::test;
 
 using namespace mlpack::distribution;
 using namespace mlpack::regression;
 
-using namespace mlpack::ann;
+using namespace mlpack;
 
 BOOST_AUTO_TEST_SUITE(AdaDeltaTest);
 
 /**
- * Train and evaluate a vanilla network with the specified structure. Using the
- * iris data, the data set contains 3 classes. One class is linearly separable
- * from the other 2. The other two aren't linearly separable from each other.
+ * Tests the Adadelta optimizer using a simple test function.
  */
-
 BOOST_AUTO_TEST_CASE(SimpleAdaDeltaTestFunction)
 {
   SGDTestFunction f;
@@ -48,7 +36,6 @@ BOOST_AUTO_TEST_CASE(SimpleAdaDeltaTestFunction)
   arma::mat coordinates = f.GetInitialPoint();
   const double result = optimizer.Optimize(coordinates);
 
-  BOOST_REQUIRE_LE(std::abs(result) - 1.0, 0.2);
   BOOST_REQUIRE_SMALL(coordinates[0], 1e-3);
   BOOST_REQUIRE_SMALL(coordinates[1], 1e-3);
   BOOST_REQUIRE_SMALL(coordinates[2], 1e-3);
@@ -115,46 +102,4 @@ BOOST_AUTO_TEST_CASE(LogisticRegressionTest)
   BOOST_REQUIRE_CLOSE(testAcc, 100.0, 0.6); // 0.6% error tolerance.
 }
 
-/**
- * Run AdaDelta on a feedforward neural network and make sure the results are
- * acceptable.
- */
-BOOST_AUTO_TEST_CASE(FeedforwardTest)
-{
-  // Test on a non-linearly separable dataset (XOR).
-  arma::mat input, labels;
-  input << 0 << 1 << 1 << 0 << arma::endr
-        << 1 << 0 << 1 << 0 << arma::endr;
-  labels << 0 << 0 << 1 << 1;
-
-  // Instantiate the first layer.
-  LinearLayer<> inputLayer(input.n_rows, 4);
-  BiasLayer<> biasLayer(4);
-  SigmoidLayer<> hiddenLayer0;
-
-  // Instantiate the second layer.
-  LinearLayer<> hiddenLayer1(4, labels.n_rows);
-  SigmoidLayer<> outputLayer;
-
-  // Instantiate the output layer.
-  BinaryClassificationLayer classOutputLayer;
-
-  // Instantiate the feedforward network.
-  auto modules = std::tie(inputLayer, biasLayer, hiddenLayer0, hiddenLayer1,
-      outputLayer);
-  FFN<decltype(modules), decltype(classOutputLayer), RandomInitialization,
-      MeanSquaredErrorFunction> net(modules, classOutputLayer);
-
-  AdaDelta<decltype(net)> opt(net, 0.88, 1e-15,
-      300 * input.n_cols, 1e-18);
-
-  net.Train(input, labels, opt);
-
-  arma::mat prediction;
-  net.Predict(input, prediction);
-
-  const bool b = arma::accu(prediction - labels) == 0;
-  BOOST_REQUIRE_EQUAL(b, true);
-}
-
 BOOST_AUTO_TEST_SUITE_END();