diff --git a/src/mlpack/methods/ann/cnn_impl.hpp b/src/mlpack/methods/ann/cnn_impl.hpp index 3b568c46f6..a4e773346d 100644 --- a/src/mlpack/methods/ann/cnn_impl.hpp +++ b/src/mlpack/methods/ann/cnn_impl.hpp @@ -46,8 +46,8 @@ CNN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); // Train the model. Timer::Start("cnn_optimization"); @@ -83,8 +83,8 @@ CNN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); Train(predictors, responses); } @@ -112,8 +112,8 @@ CNN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); } template::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); // Train the model. Timer::Start("ffn_optimization"); @@ -83,8 +83,8 @@ FFN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); Train(predictors, responses); } @@ -112,8 +112,8 @@ FFN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); } template::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); // Train the model. Timer::Start("rnn_optimization"); @@ -87,8 +87,8 @@ RNN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); Train(predictors, responses); } @@ -118,8 +118,8 @@ RNN::value, "The type of outputLayer must be OutputLayerType."); - initializeRule.Initialize(parameter, NetworkSize(network), 1); - NetworkWeights(parameter, network); + initializeRule.Initialize(parameter, NetworkSize(this->network), 1); + NetworkWeights(parameter, this->network); } template