sustaining_gazes/matlab_version/face_validation/DeepLearnToolbox/CAE/caeexamples.m

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2016-04-28 19:40:36 +00:00
%% mnist data
clear all; close all; clc;
load mnist_uint8;
x = cell(100, 1);
N = 600;
for i = 1 : 100
x{i}{1} = reshape(train_x(((i - 1) * N + 1) : (i) * N, :), N, 28, 28) * 255;
end
%% ex 1
scae = {
struct('outputmaps', 10, 'inputkernel', [1 5 5], 'outputkernel', [1 5 5], 'scale', [1 2 2], 'sigma', 0.1, 'momentum', 0.9, 'noise', 0)
};
opts.rounds = 1000;
opts.batchsize = 1;
opts.alpha = 0.01;
opts.ddinterval = 10;
opts.ddhist = 0.5;
scae = scaesetup(scae, x, opts);
scae = scaetrain(scae, x, opts);
cae = scae{1};
%Visualize the average reconstruction error
plot(cae.rL);
%Visualize the output kernels
ff=[];
for i=1:numel(cae.ok{1});
mm = cae.ok{1}{i}(1,:,:);
ff(i,:) = mm(:);
end;
figure;visualize(ff')