From f590f9ad66d6e485f47de8340c2fd526b0445d6d Mon Sep 17 00:00:00 2001 From: khalednasr Date: Mon, 17 Mar 2014 13:30:12 +0200 Subject: [PATCH] fixed indents --- .../neuralnets/neuralnets_digits.ipynb | 4 +-- src/shogun/neuralnets/NeuralLayer.cpp | 10 ------ src/shogun/neuralnets/NeuralLayer.h | 12 +++---- src/shogun/neuralnets/NeuralLinearLayer.h | 16 +++++----- src/shogun/neuralnets/NeuralLogisticLayer.cpp | 14 ++------- src/shogun/neuralnets/NeuralLogisticLayer.h | 6 ++-- src/shogun/neuralnets/NeuralNetwork.cpp | 31 +++++-------------- src/shogun/neuralnets/NeuralNetwork.h | 16 +++++----- 8 files changed, 35 insertions(+), 74 deletions(-) diff --git a/doc/ipython-notebooks/neuralnets/neuralnets_digits.ipynb b/doc/ipython-notebooks/neuralnets/neuralnets_digits.ipynb index ff9c74de216..53aaff73e87 100644 --- a/doc/ipython-notebooks/neuralnets/neuralnets_digits.ipynb +++ b/doc/ipython-notebooks/neuralnets/neuralnets_digits.ipynb @@ -87,11 +87,11 @@ "output_type": "stream", "stream": "stdout", "text": [ - "Test Error = 8.58938547486 %\n" + "Test Error = 8.54283054004 %\n" ] } ], - "prompt_number": 4 + "prompt_number": 1 }, { "cell_type": "code", diff --git a/src/shogun/neuralnets/NeuralLayer.cpp b/src/shogun/neuralnets/NeuralLayer.cpp index aa57ebab678..8598ecbde96 100644 --- a/src/shogun/neuralnets/NeuralLayer.cpp +++ b/src/shogun/neuralnets/NeuralLayer.cpp @@ -85,13 +85,3 @@ void CNeuralLayer::shallow_copy(const CNeuralLayer &orig) m_input_gradients = SGVector(orig.m_input_gradients); m_local_gradients = SGVector(orig.m_local_gradients); } - - - - - - - - - - diff --git a/src/shogun/neuralnets/NeuralLayer.h b/src/shogun/neuralnets/NeuralLayer.h index f327c219588..caaad39b82e 100644 --- a/src/shogun/neuralnets/NeuralLayer.h +++ b/src/shogun/neuralnets/NeuralLayer.h @@ -96,8 +96,8 @@ class CNeuralLayer : public CSGObject * parameters */ virtual void initialize_parameters(float64_t* parameters, - bool* parameter_regularizable, - float64_t sigma = 0.01f) = 0; + bool* parameter_regularizable, + float64_t sigma = 0.01f) = 0; /** Computes the activations of the neurons in this layer, results should * be stored in m_activations @@ -136,10 +136,10 @@ class CNeuralLayer : public CSGObject * layer */ virtual void compute_gradients(float64_t* parameters, - bool is_output, - float64_t* p, - float64_t* previous_layer_activations, - float64_t* parameter_gradients) = 0; + bool is_output, + float64_t* p, + float64_t* previous_layer_activations, + float64_t* parameter_gradients) = 0; /** Computes the error between the layer's current activations and the given * target activations. Should only be used with output layers diff --git a/src/shogun/neuralnets/NeuralLinearLayer.h b/src/shogun/neuralnets/NeuralLinearLayer.h index b5f4ab09c61..3dfb32ec6fd 100644 --- a/src/shogun/neuralnets/NeuralLinearLayer.h +++ b/src/shogun/neuralnets/NeuralLinearLayer.h @@ -64,8 +64,8 @@ class CNeuralLinearLayer : public CNeuralLayer * parameters */ virtual void initialize_parameters(float64_t* parameters, - bool* parameter_regularizable, - float64_t sigma = 0.01f); + bool* parameter_regularizable, + float64_t sigma = 0.01f); /** Computes the activations of the neurons in this layer, results should * be stored in m_activations @@ -77,7 +77,7 @@ class CNeuralLinearLayer : public CNeuralLayer * previous layer, matrix of size previous_layer_num_neurons * batch_size */ virtual void compute_activations(float64_t* parameters, - float64_t* previous_layer_activations); + float64_t* previous_layer_activations); /** Computes the gradients that are relevent to this layer: * - The gradients of the error with respect to the layer's parameters @@ -104,10 +104,10 @@ class CNeuralLinearLayer : public CNeuralLayer * layer */ virtual void compute_gradients(float64_t* parameters, - bool is_output, - float64_t* p, - float64_t* previous_layer_activations, - float64_t* parameter_gradients); + bool is_output, + float64_t* p, + float64_t* previous_layer_activations, + float64_t* parameter_gradients); /** Computes the error between the layer's current activations and the given * target activations. Should only be used with output layers @@ -144,4 +144,4 @@ class CNeuralLinearLayer : public CNeuralLayer }; } -#endif \ No newline at end of file +#endif diff --git a/src/shogun/neuralnets/NeuralLogisticLayer.cpp b/src/shogun/neuralnets/NeuralLogisticLayer.cpp index 5b6ddc9b56c..c7419e131c4 100644 --- a/src/shogun/neuralnets/NeuralLogisticLayer.cpp +++ b/src/shogun/neuralnets/NeuralLogisticLayer.cpp @@ -29,7 +29,7 @@ CNeuralLinearLayer(num_neurons) } void CNeuralLogisticLayer::compute_activations(float64_t* parameters, - float64_t* previous_layer_activations) + float64_t* previous_layer_activations) { CNeuralLinearLayer::compute_activations(parameters, previous_layer_activations); @@ -41,7 +41,7 @@ void CNeuralLogisticLayer::compute_activations(float64_t* parameters, } void CNeuralLogisticLayer::compute_local_gradients(bool is_output, - float64_t* p) + float64_t* p) { CNeuralLinearLayer::compute_local_gradients(is_output,p); @@ -50,13 +50,3 @@ void CNeuralLogisticLayer::compute_local_gradients(bool is_output, for (int32_t i=0; i -#include #include #ifdef HAVE_EIGEN3 @@ -52,7 +50,7 @@ class CNeuralLogisticLayer : public CNeuralLinearLayer * previous layer, matrix of size previous_layer_num_neurons * batch_size */ virtual void compute_activations(float64_t* parameters, - float64_t* previous_layer_activations); + float64_t* previous_layer_activations); /** Computes the gradients of the error with respect to this layer's * activations. Results are stored in m_local_gradients. @@ -76,4 +74,4 @@ class CNeuralLogisticLayer : public CNeuralLinearLayer }; } -#endif \ No newline at end of file +#endif diff --git a/src/shogun/neuralnets/NeuralNetwork.cpp b/src/shogun/neuralnets/NeuralNetwork.cpp index 140ae422e6c..d1db008351f 100644 --- a/src/shogun/neuralnets/NeuralNetwork.cpp +++ b/src/shogun/neuralnets/NeuralNetwork.cpp @@ -76,7 +76,7 @@ CNeuralNetwork::~CNeuralNetwork() } CDenseFeatures* CNeuralNetwork::apply( - CDenseFeatures* inputs) + CDenseFeatures* inputs) { ASSERT(inputs->get_num_features()==m_num_inputs); @@ -101,12 +101,12 @@ CDenseFeatures* CNeuralNetwork::apply( } void CNeuralNetwork::train_gradient_descent( - CDenseFeatures< float64_t >* inputs, - CDenseFeatures< float64_t >* targets, - int32_t max_num_epochs, - int32_t batch_size, - float64_t learning_rate, - float64_t momentum) + CDenseFeatures< float64_t >* inputs, + CDenseFeatures< float64_t >* targets, + int32_t max_num_epochs, + int32_t batch_size, + float64_t learning_rate, + float64_t momentum) { int32_t training_set_size = inputs->get_num_vectors(); int32_t _batch_size = batch_size; @@ -321,20 +321,3 @@ void CNeuralNetwork::shallow_copy(const CNeuralNetwork& orig) m_param_gradients = SGVector(orig.m_param_gradients); m_param_regularizable = SGVector(orig.m_param_regularizable); } - - - - - - - - - - - - - - - - - diff --git a/src/shogun/neuralnets/NeuralNetwork.h b/src/shogun/neuralnets/NeuralNetwork.h index 93faeaac178..5d89bc94548 100644 --- a/src/shogun/neuralnets/NeuralNetwork.h +++ b/src/shogun/neuralnets/NeuralNetwork.h @@ -91,11 +91,11 @@ class CNeuralNetwork : public CSGObject * @param momentum momentum multiplier */ virtual void train_gradient_descent(CDenseFeatures* inputs, - CDenseFeatures* targets, - int32_t max_num_epochs = 1000, - int32_t batch_size = 0, - float64_t learning_rate = 0.1, - float64_t momentum = 0.9); + CDenseFeatures* targets, + int32_t max_num_epochs = 1000, + int32_t batch_size = 0, + float64_t learning_rate = 0.1, + float64_t momentum = 0.9); /** Checks if the gradients computed using backpropagation are correct by * comparing them with gradients computed using numerical approximation. @@ -109,7 +109,7 @@ class CNeuralNetwork : public CSGObject * @return true if the gradients are correct, false otherwise */ virtual bool check_gradients(float64_t epsilon=1.0e-06, - float64_t tolerance=1.0e-09); + float64_t tolerance=1.0e-09); /** returns the totat number of parameters in the network */ int32_t get_num_parameters() {return m_total_num_parameters;} @@ -177,7 +177,7 @@ class CNeuralNetwork : public CSGObject * update the activations before the error is computed. */ virtual float64_t compute_error(float64_t* targets, - float64_t* inputs=NULL); + float64_t* inputs=NULL); private: /** returns a pointer to layer i in the network */ @@ -254,4 +254,4 @@ class CNeuralNetwork : public CSGObject }; } -#endif \ No newline at end of file +#endif