/usr/share/octave/packages/nnet-0.1.13/saveMLPStruct.m is in octave-nnet 0.1.13-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 | ## Copyright (C) 2005 Michel D. Schmid <michaelschmid@users.sourceforge.net>
##
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2, or (at your option)
## any later version.
##
## This program 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
## General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; see the file COPYING. If not, see
## <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {} saveMLPStruct (@var{net},@var{strFileName})
## @code{saveStruct} saves a neural network structure to *.txt files
## @end deftypefn
## Author: Michel D. Schmid
function saveMLPStruct(net,strFileName)
## the variable net holds the neural network structure..
# check if "net" is a structure type
if !__checknetstruct(net)
error("Structure doesn't seem to be a neural network")
endif
# open the first level file
fid1 = fopen(strFileName,"w+t","ieee-le");
if (fid1 < 0)
error ("Can not open %s", strFileName);
endif
## print header
# try ## wird nicht mehr benötigt..
__printMLPHeader(fid1);
# catch
# ## Add saveMLPStructure directory to the path and try again
# addpath ([fileparts(mfilename()),"/saveMLPStructure"]);
# __printMLPHeader(fid1);
# end_try_catch
## check for field "networkType"
__printNetworkType(fid1,net);
## check for field "numInputs"
__printNumInputs(fid1,net);
## check for field "numLayers"
__printNumLayers(fid1,net)
## check for field "biasConnect"
__printBiasConnect(fid1,net)
## check for field "inputConnect"
__printInputConnect(fid1,net)
## check for field "layerConnect"
__printLayerConnect(fid1,net)
## check for field "outputConnect"
__printOutputConnect(fid1,net)
## check for field "targetConnect"
__printTargetConnect(fid1,net)
## print one empty line
fprintf(fid1,"\n");
## check for numOutputs
__printNumOutputs(fid1,net);
## check for numTargets
__printNumTargets(fid1,net);
## check for numInputDelays
__printNumInputDelays(fid1,net);
## check for numLayerDelays
__printNumLayerDelays(fid1,net);
## print one empty line
fprintf(fid1,"\n");
## print subobject structures:
fprintf(fid1," subobject structures:\n");
## print one empty line
fprintf(fid1,"\n");
## print inputs
__printInputs(fid1,net);
## print layers
__printLayers(fid1,net);
## print outputs
__printOutputs(fid1,net);
## print targets
__printTargets(fid1,net);
## print biases
__printBiases(fid1,net);
## print inputweights
__printInputWeights(fid1,net);
## print layerweights
__printLayerWeights(fid1,net);
## print one empty line
fprintf(fid1,"\n");
## print subobject structures:
fprintf(fid1," functions:\n");
## print one empty line
fprintf(fid1,"\n");
## print adaptFcn
__printAdaptFcn(fid1,net);
## print initFcn
__printInitFcn(fid1,net);
## print performFcn
__printPerformFcn(fid1,net);
## print performFcn
__printTrainFcn(fid1,net);
## print one empty line
fprintf(fid1,"\n");
## print subobject structures:
fprintf(fid1," parameters:\n");
## print one empty line
fprintf(fid1,"\n");
## print adaptParam
__printAdaptParam(fid1,net);
## print initParam
__printInitParam(fid1,net);
## print performParam
__printPerformParam(fid1,net);
## print trainParam
__printTrainParam(fid1,net);
## print one empty line
fprintf(fid1,"\n");
## print subobject structures:
fprintf(fid1," weight & bias values:\n");
## print one empty line
fprintf(fid1,"\n");
## print IW
__printIW(fid1,net);
## print LW
__printLW(fid1,net);
## print b
__printB(fid1,net);
## print one empty line
fprintf(fid1,"\n");
## print subobject structures:
fprintf(fid1," other:\n");
fclose(fid1);
endfunction
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