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makebatches.m
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makebatches.m
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% Version 1.000
%
% Code provided by Ruslan Salakhutdinov and Geoff Hinton
%
% Permission is granted for anyone to copy, use, modify, or distribute this
% program and accompanying programs and documents for any purpose, provided
% this copyright notice is retained and prominently displayed, along with
% a note saying that the original programs are available from our
% web page.
% The programs and documents are distributed without any warranty, express or
% implied. As the programs were written for research purposes only, they have
% not been tested to the degree that would be advisable in any important
% application. All use of these programs is entirely at the user's own risk.
digitdata=[];
targets=[];
load digit0; digitdata = [digitdata; D]; targets = [targets; repmat([1 0 0 0 0 0 0 0 0 0], size(D,1), 1)];
load digit1; digitdata = [digitdata; D]; targets = [targets; repmat([0 1 0 0 0 0 0 0 0 0], size(D,1), 1)];
load digit2; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 1 0 0 0 0 0 0 0], size(D,1), 1)];
load digit3; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 1 0 0 0 0 0 0], size(D,1), 1)];
load digit4; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 1 0 0 0 0 0], size(D,1), 1)];
load digit5; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 1 0 0 0 0], size(D,1), 1)];
load digit6; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 1 0 0 0], size(D,1), 1)];
load digit7; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 1 0 0], size(D,1), 1)];
load digit8; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 0 1 0], size(D,1), 1)];
load digit9; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 0 0 1], size(D,1), 1)];
digitdata = digitdata/255;
totnum=size(digitdata,1);
fprintf(1, 'Size of the training dataset= %5d \n', totnum);
rand('state',0); %so we know the permutation of the training data
randomorder=randperm(totnum);
numbatches=totnum/100;
numdims = size(digitdata,2);
batchsize = 100;
batchdata = zeros(batchsize, numdims, numbatches);
batchtargets = zeros(batchsize, 10, numbatches);
for b=1:numbatches
batchdata(:,:,b) = digitdata(randomorder(1+(b-1)*batchsize:b*batchsize), :);
batchtargets(:,:,b) = targets(randomorder(1+(b-1)*batchsize:b*batchsize), :);
end;
clear digitdata targets;
digitdata=[];
targets=[];
load test0; digitdata = [digitdata; D]; targets = [targets; repmat([1 0 0 0 0 0 0 0 0 0], size(D,1), 1)];
load test1; digitdata = [digitdata; D]; targets = [targets; repmat([0 1 0 0 0 0 0 0 0 0], size(D,1), 1)];
load test2; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 1 0 0 0 0 0 0 0], size(D,1), 1)];
load test3; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 1 0 0 0 0 0 0], size(D,1), 1)];
load test4; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 1 0 0 0 0 0], size(D,1), 1)];
load test5; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 1 0 0 0 0], size(D,1), 1)];
load test6; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 1 0 0 0], size(D,1), 1)];
load test7; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 1 0 0], size(D,1), 1)];
load test8; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 0 1 0], size(D,1), 1)];
load test9; digitdata = [digitdata; D]; targets = [targets; repmat([0 0 0 0 0 0 0 0 0 1], size(D,1), 1)];
digitdata = digitdata/255;
totnum=size(digitdata,1);
fprintf(1, 'Size of the test dataset= %5d \n', totnum);
rand('state',0); %so we know the permutation of the training data
randomorder=randperm(totnum);
numbatches=totnum/100;
numdims = size(digitdata,2);
batchsize = 100;
testbatchdata = zeros(batchsize, numdims, numbatches);
testbatchtargets = zeros(batchsize, 10, numbatches);
for b=1:numbatches
testbatchdata(:,:,b) = digitdata(randomorder(1+(b-1)*batchsize:b*batchsize), :);
testbatchtargets(:,:,b) = targets(randomorder(1+(b-1)*batchsize:b*batchsize), :);
end;
clear digitdata targets;
%%% Reset random seeds
rand('state',sum(100*clock));
randn('state',sum(100*clock));