87 lines
3.3 KiB
C++
87 lines
3.3 KiB
C++
/********************************************************
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* ██████╗ ██████╗████████╗██╗
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* ██╔════╝ ██╔════╝╚══██╔══╝██║
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* ██║ ███╗██║ ██║ ██║
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* ██║ ██║██║ ██║ ██║
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* ╚██████╔╝╚██████╗ ██║ ███████╗
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* ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝
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* Geophysical Computational Tools & Library (GCTL)
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*
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* Copyright (c) 2022 Yi Zhang (yizhang-geo@zju.edu.cn)
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*
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* GCTL is distributed under a dual licensing scheme. You can redistribute
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* it and/or modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation, either version 2
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* of the License, or (at your option) any later version. You should have
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* received a copy of the GNU Lesser General Public License along with this
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* program. If not, see <http://www.gnu.org/licenses/>.
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*
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* If the terms and conditions of the LGPL v.2. would prevent you from using
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* the GCTL, please consider the option to obtain a commercial license for a
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* fee. These licenses are offered by the GCTL's original author. As a rule,
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* licenses are provided "as-is", unlimited in time for a one time fee. Please
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* send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget
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* to include some description of your company and the realm of its activities.
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* Also add information on how to contact you by electronic and paper mail.
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******************************************************/
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#include "../data/MNIST/mnist_database.h"
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#include "../lib/dnn.h"
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using namespace gctl;
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int main(int argc, char const *argv[]) try
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{
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mnist_database data("data/MNIST");
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dnn my_nn("Ex-MNIST");
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my_nn.load_network("data/saved_networks/mnist_m1.gctl.dnn");
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my_nn.show_network();
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my_nn.save_layer2text(0, "data/saved_networks/mnist_m1_layer1");
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my_nn.save_layer2text(1, "data/saved_networks/mnist_m1_layer2");
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/*
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matrix<double> test_obs(784, 10000), test_lab(10, 10000, 0.0), predicts(10, 10000);
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const std::vector<std::vector<double> > &dt_obs2 = data.test_images();
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for (size_t i = 0; i < 10000; i++)
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{
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for (size_t j = 0; j < 784; j++)
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{
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test_obs[j][i] = dt_obs2[i][j]/255.0;
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}
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}
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const std::vector<double> &dt_lab2 = data.test_labels();
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for (size_t i = 0; i < 10000; i++)
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{
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test_lab[dt_lab2[i]][i] = 1.0;
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}
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my_nn.predict(test_obs, predicts);
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int wrong_predicts = 0;
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int test_id, pre_id;
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double test_scr, pre_scr;
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for (size_t j = 0; j < 10000; j++)
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{
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test_id = pre_id = 0;
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test_scr = pre_scr = 0;
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for (size_t i = 0; i < 10; i++)
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{
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if (test_lab[i][j] > test_scr) {test_scr = test_lab[i][j]; test_id = i;}
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if (predicts[i][j] > pre_scr) {pre_scr = predicts[i][j]; pre_id = i;}
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}
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if (test_id != pre_id)
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{
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wrong_predicts++;
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}
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}
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std::cout << "Correct Rate = " << (10000 - wrong_predicts)/100.0 << "%\n";
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*/
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return 0;
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}
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catch (std::exception &e)
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{
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GCTL_ShowWhatError(e.what(), GCTL_ERROR_ERROR, 0, 0, 0);
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} |