[mlpack-git] master: Minor style and formatting changes. (c13f764)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Fri Nov 13 12:45:53 EST 2015
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/0f4e83dc9cc4dcdc315d2cceee32b23ebab114c2...7388de71d5398103ee3a0b32b4026902a40a67b3
>---------------------------------------------------------------
commit c13f7645086896eff39bd748abceaa87e4bf2c09
Author: marcus <marcus.edel at fu-berlin.de>
Date: Thu Nov 12 14:46:24 2015 +0100
Minor style and formatting changes.
>---------------------------------------------------------------
c13f7645086896eff39bd748abceaa87e4bf2c09
src/mlpack/tests/feedforward_network_test.cpp | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/src/mlpack/tests/feedforward_network_test.cpp b/src/mlpack/tests/feedforward_network_test.cpp
index f8b964e..4c54e77 100644
--- a/src/mlpack/tests/feedforward_network_test.cpp
+++ b/src/mlpack/tests/feedforward_network_test.cpp
@@ -82,7 +82,7 @@ void BuildVanillaNetwork(MatType& trainData,
OutputLayerType classOutputLayer;
auto modules = std::tie(inputLayer, inputBiasLayer, inputBaseLayer,
- hiddenLayer1, hiddenBiasLayer1, outputLayer);
+ hiddenLayer1, hiddenBiasLayer1, outputLayer);
FFN<decltype(modules), decltype(classOutputLayer), PerformanceFunctionType>
net(modules, classOutputLayer);
@@ -95,8 +95,8 @@ void BuildVanillaNetwork(MatType& trainData,
for (size_t i = 0; i < testData.n_cols; i++)
{
- MatType predictionInput = testData.unsafe_col(i);
- MatType targetOutput = testLabels.unsafe_col(i);
+ MatType predictionInput = testData.unsafe_col(i);
+ MatType targetOutput = testLabels.unsafe_col(i);
net.Predict(predictionInput, prediction);
@@ -212,7 +212,7 @@ void BuildDropoutNetwork(MatType& trainData,
OutputLayerType classOutputLayer;
auto modules = std::tie(inputLayer, biasLayer, hiddenLayer0, dropoutLayer0,
- hiddenLayer1, outputLayer);
+ hiddenLayer1, outputLayer);
FFN<decltype(modules), decltype(classOutputLayer), PerformanceFunctionType>
net(modules, classOutputLayer);
@@ -225,10 +225,10 @@ void BuildDropoutNetwork(MatType& trainData,
for (size_t i = 0; i < testData.n_cols; i++)
{
- MatType input = testData.unsafe_col(i);
+ MatType input = testData.unsafe_col(i);
net.Predict(input, prediction);
if (arma::sum(arma::sum(arma::abs(
- prediction - testLabels.unsafe_col(i)))) == 0)
+ prediction - testLabels.unsafe_col(i)))) == 0)
error++;
}
@@ -388,7 +388,7 @@ void BuildNetworkOptimzer(MatType& trainData,
OutputLayerType classOutputLayer;
auto modules = std::tie(inputLayer, inputBiasLayer, inputBaseLayer,
- hiddenLayer1, hiddenBiasLayer1, outputLayer);
+ hiddenLayer1, hiddenBiasLayer1, outputLayer);
FFN<decltype(modules), OutputLayerType, PerformanceFunctionType>
net(modules, classOutputLayer);
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