/* Fast Artificial Neural Network Library (fann) Copyright (C) 2003-2012 Steffen Nissen (sn@leenissen.dk) This library is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version. This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this library; if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */ #ifndef __fann_io_h__ #define __fann_io_h__ /* Section: FANN File Input/Output It is possible to save an entire ann to a file with for future loading with . */ /* Group: File Input and Output */ /* Function: fann_create_from_file Constructs a backpropagation neural network from a configuration file, which have been saved by . See also: , This function appears in FANN >= 1.0.0. */ FANN_EXTERNAL struct fann *FANN_API fann_create_from_file(const char *configuration_file); /* Function: fann_save Save the entire network to a configuration file. The configuration file contains all information about the neural network and enables to create an exact copy of the neural network and all of the parameters associated with the neural network. These three parameters (, , ) are *NOT* saved to the file because they cannot safely be ported to a different location. Also temporary parameters generated during training like is not saved. Return: The function returns 0 on success and -1 on failure. See also: , This function appears in FANN >= 1.0.0. */ FANN_EXTERNAL int FANN_API fann_save(struct fann *ann, const char *configuration_file); /* Function: fann_save_to_fixed Saves the entire network to a configuration file. But it is saved in fixed point format no matter which format it is currently in. This is usefull for training a network in floating points, and then later executing it in fixed point. The function returns the bit position of the fix point, which can be used to find out how accurate the fixed point network will be. A high value indicates high precision, and a low value indicates low precision. A negative value indicates very low precision, and a very strong possibility for overflow. (the actual fix point will be set to 0, since a negative fix point does not make sence). Generally, a fix point lower than 6 is bad, and should be avoided. The best way to avoid this, is to have less connections to each neuron, or just less neurons in each layer. The fixed point use of this network is only intended for use on machines that have no floating point processor, like an iPAQ. On normal computers the floating point version is actually faster. See also: , This function appears in FANN >= 1.0.0. */ FANN_EXTERNAL int FANN_API fann_save_to_fixed(struct fann *ann, const char *configuration_file); #endif