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classification dataset fix and clean
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@RubyAM
RubyAM committed Jan 28, 2025
1 parent 4897391 commit 09bfe61
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124 changes: 1 addition & 123 deletions blank/main.cpp
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Expand Up @@ -6,7 +6,6 @@
// Artificial Intelligence Techniques SL
// [email protected]


#include <iostream>
#include <fstream>
#include <sstream>
Expand All @@ -25,129 +24,8 @@ int main()
{
try
{
cout << "OpenNN. ViT Example." << endl;

// Eigen::Tensor<float, 4> input(1, 1, 1, 1);
// input.setRandom();

// Eigen::Tensor<float, 2> kernel(1, 1, 1, 1);
// kernel.setRandom();

// Eigen::Tensor<float, 4> output(1, 1, 1, 1);

// Eigen::array<int, 3> dims;
// output = input.convolve(kernel, dims);

// std::cout << "input:\n\n" << input << "\n\n";
// std::cout << "kernel:\n\n" << kernel << "\n\n";
// std::cout << "output:\n\n" << output << "\n\n";


// const Index samples_number = get_random_index(1, 10);
// const Index inputs_number = get_random_index(1, 10);
// const Index targets_number = get_random_index(1, 10);
// const Index neurons_number = get_random_index(1, 10);
// Index a = 0;
// Index b = 0;
// Tensor<bool, 0> truefalse = a == b;
// cout<<truefalse<<endl;
// throw runtime_error("Stop");
// srand(static_cast<unsigned>(time(nullptr)));

// // Data set

// ImageDataSet image_data_set;

// image_data_set.set_data_source_path("/home/artelnics/Escritorio/andres_alonso/ViT/dataset/bmp/cifar10_bmp1");

// image_data_set.read_bmp();

// vector<string> completion_vocabulary = language_data_set.get_completion_vocabulary();
// vector<string> context_vocabulary = language_data_set.get_context_vocabulary();

// // Neural network

// const Index input_length = image_data_set.get_samples_number();
// const Index number_labels = image_data_set.get_variables_number(DataSet::VariableUse::Target);
// const Index number_channels = image_data_set.get_channels_number();
// const Index height = image_data_set.get_image_height();
// const Index width = image_data_set.get_image_width();

// Index number_of_layers = 1;
// Index depth = 64;
// Index perceptron_depth = 128;
// Index heads_number = 4;



// Transformer transformer({ input_length, decoder_length, inputs_dimension, context_dimension,
// depth, perceptron_depth, heads_number, number_of_layers });

// transformer.set_model_type_string("TextClassification");
// transformer.set_dropout_rate(0);

// cout << "Total number of parameters: " << transformer.get_parameters_number() << endl;

// transformer.set_input_vocabulary(completion_vocabulary);
// transformer.set_context_vocabulary(context_vocabulary);

// // Training strategy

// TrainingStrategy training_strategy(&transformer, &language_data_set);

// training_strategy.set_loss_method(TrainingStrategy::LossMethod::CROSS_ENTROPY_ERROR_3D);

// training_strategy.get_loss_index()->set_regularization_method(LossIndex::RegularizationMethod::NoRegularization);

// training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::ADAPTIVE_MOMENT_ESTIMATION);

// training_strategy.get_adaptive_moment_estimation()->set_custom_learning_rate(depth);

// training_strategy.get_adaptive_moment_estimation()->set_loss_goal(0.99);
// training_strategy.get_adaptive_moment_estimation()->set_maximum_epochs_number(4000);
// training_strategy.get_adaptive_moment_estimation()->set_maximum_time(237600);
// training_strategy.get_adaptive_moment_estimation()->set_batch_samples_number(64);

// training_strategy.get_adaptive_moment_estimation()->set_display(true);
// training_strategy.get_adaptive_moment_estimation()->set_display_period(1);

// TrainingResults training_results = training_strategy.perform_training();

// const TestingAnalysis testing_analysis(&transformer, &language_data_set);

// pair<type, type> transformer_error_accuracy = testing_analysis.test_transformer();

// cout << "TESTING ANALYSIS:" << endl;
// cout << "Testing error: " << transformer_error_accuracy.first << endl;
// cout << "Testing accuracy: " << transformer_error_accuracy.second << endl;

// // // Save results-

// // transformer.save("/home/artelnics/Escritorio/andres_alonso/ViT/ENtoES_model.xml");

// // // Testing analysis

// // transformer.load("/home/artelnics/Escritorio/andres_alonso/ViT/Weights/ENtoES_model.xml");

// // const TestingAnalysis testing_analysis(&transformer, &language_data_set);

// // pair<type, type> transformer_error_accuracy = testing_analysis.test_transformer();

// // cout << "TESTING ANALYSIS:" << endl;
// // cout << "Testing error: " << transformer_error_accuracy.first << endl;
// // cout << "Testing accuracy: " << transformer_error_accuracy.second << endl;


// ForwardPropagation forward_propagation(samples_number, &neural_network);

// neural_network.forward_propagate(batch.get_input_pairs(), forward_propagation, true);

// Loss index

// NormalizedSquaredError normalized_squared_error(&neural_network, &data_set);
cout << "OpenNN. Blank." << endl;

// BackPropagation back_propagation(samples_number, &normalized_squared_error);
// normalized_squared_error.back_propagate(batch, forward_propagation, back_propagation);

cout << "Bye!" << endl;

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11 changes: 2 additions & 9 deletions examples/airfoil_self_noise/main.cpp
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Expand Up @@ -26,13 +26,6 @@ int main()
const Index target_variables_number = data_set.get_variables_number(DataSet::VariableUse::Target);

data_set.set(DataSet::SampleUse::Training);

//data_set.save("data/neural_network.xml");
//data_set.print();

//DataSet data_set_xml;
//data_set_xml.load("data/neural_network.xml");
//data_set_xml.print();

// Neural network

Expand All @@ -51,11 +44,11 @@ int main()
// training_strategy.set_loss_method(TrainingStrategy::LossMethod::MEAN_SQUARED_ERROR);
//training_strategy.set_loss_method(TrainingStrategy::LossMethod::MINKOWSKI_ERROR); // @todo gives 0.56

training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::QUASI_NEWTON_METHOD);
//training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::QUASI_NEWTON_METHOD);
//training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::CONJUGATE_GRADIENT);
//training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::LEVENBERG_MARQUARDT_ALGORITHM); //Fail-Mean Squared error / Doesnt work with MINKOWSKI_ERROR / is not implemented yet with weighted squared error
//training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::STOCHASTIC_GRADIENT_DESCENT);
//training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::ADAPTIVE_MOMENT_ESTIMATION);
training_strategy.set_optimization_method(TrainingStrategy::OptimizationMethod::ADAPTIVE_MOMENT_ESTIMATION);

training_strategy.set_maximum_epochs_number(10000);

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6 changes: 1 addition & 5 deletions examples/breast_cancer/main.cpp
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Expand Up @@ -73,11 +73,7 @@ int main()
neural_network.save("../data/neural_network.xml");
neural_network.save_expression(NeuralNetwork::ProgrammingLanguage::Python, "../data/breast_cancer.py");

cout << "End breast cancer application" << endl;

// OKR
cout << " \n write_loss_method \n" << training_strategy.write_loss_method_text();
cout << " \n write_opt_method \n" << training_strategy.write_optimization_method_text();
cout << "Good bye!" << endl;

return 0;
}
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3 changes: 0 additions & 3 deletions examples/iris_plant/data/confusion.csv
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53 changes: 0 additions & 53 deletions examples/iris_plant/data/data_set.xml
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128 changes: 0 additions & 128 deletions examples/iris_plant/data/neural_network.c
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