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https://github.com/lxsang/antd-lua-plugin
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92 lines
2.8 KiB
C
92 lines
2.8 KiB
C
/*
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Fast Artificial Neural Network Library (fann)
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Copyright (C) 2003-2016 Steffen Nissen (steffen.fann@gmail.com)
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*/
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#include <stdio.h>
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#include "fann.h"
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int FANN_API test_callback(struct fann *ann, struct fann_train_data *train,
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unsigned int max_epochs, unsigned int epochs_between_reports,
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float desired_error, unsigned int epochs)
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{
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printf("Epochs %8d. MSE: %.5f. Desired-MSE: %.5f\n", epochs, fann_get_MSE(ann), desired_error);
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return 0;
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}
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int main()
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{
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fann_type *calc_out;
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const unsigned int num_input = 2;
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const unsigned int num_output = 1;
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const unsigned int num_layers = 3;
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const unsigned int num_neurons_hidden = 3;
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const float desired_error = (const float) 0;
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const unsigned int max_epochs = 1000;
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const unsigned int epochs_between_reports = 10;
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struct fann *ann;
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struct fann_train_data *data;
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unsigned int i = 0;
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unsigned int decimal_point;
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printf("Creating network.\n");
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ann = fann_create_standard(num_layers, num_input, num_neurons_hidden, num_output);
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data = fann_read_train_from_file("xor.data");
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fann_set_activation_steepness_hidden(ann, 1);
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fann_set_activation_steepness_output(ann, 1);
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fann_set_activation_function_hidden(ann, FANN_SIGMOID_SYMMETRIC);
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fann_set_activation_function_output(ann, FANN_SIGMOID_SYMMETRIC);
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fann_set_train_stop_function(ann, FANN_STOPFUNC_BIT);
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fann_set_bit_fail_limit(ann, 0.01f);
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fann_set_training_algorithm(ann, FANN_TRAIN_RPROP);
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fann_init_weights(ann, data);
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printf("Training network.\n");
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fann_train_on_data(ann, data, max_epochs, epochs_between_reports, desired_error);
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printf("Testing network. %f\n", fann_test_data(ann, data));
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for(i = 0; i < fann_length_train_data(data); i++)
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{
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calc_out = fann_run(ann, data->input[i]);
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printf("XOR test (%f,%f) -> %f, should be %f, difference=%f\n",
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data->input[i][0], data->input[i][1], calc_out[0], data->output[i][0],
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fann_abs(calc_out[0] - data->output[i][0]));
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}
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printf("Saving network.\n");
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fann_save(ann, "xor_float.net");
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decimal_point = fann_save_to_fixed(ann, "xor_fixed.net");
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fann_save_train_to_fixed(data, "xor_fixed.data", decimal_point);
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printf("Cleaning up.\n");
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fann_destroy_train(data);
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fann_destroy(ann);
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return 0;
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}
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