Convolutional Auto-Encoders卷积自编码器（Matlab代码）

function cae = caenumgradcheck(cae, x, y) epsilon = 1e-4; er = 1e-6; disp('performing numerical gradient checking...') for i = 1 : numel(cae.o) p_cae = cae; p_cae.c{i} = p_cae.c{i} + epsilon; m_cae = cae; m_cae.c{i} = m_cae.c{i} - epsilon; [m_cae, p_cae] = caerun(m_cae, p_cae, x, y); d = (p_cae.L - m_cae.L) / (2 * epsilon); e = abs(d - cae.dc{i}); if e > er disp('OUTPUT BIAS numerical gradient checking failed'); disp(e); disp(d / cae.dc{i}); keyboard end end for a = 1 : numel(cae.a) p_cae = cae; p_cae.b{a} = p_cae.b{a} + epsilon; m_cae = cae; m_cae.b{a} = m_cae.b{a} - epsilon; [m_cae, p_cae] = caerun(m_cae, p_cae, x, y); d = (p_cae.L - m_cae.L) / (2 * epsilon); % cae.dok{i}{a}(u) = d; e = abs(d - cae.db{a}); if e > er disp('BIAS numerical gradient checking failed'); disp(e); disp(d / cae.db{a}); keyboard end for i = 1 : numel(cae.o) for u = 1 : numel(cae.ok{i}{a}) p_cae = cae; p_cae.ok{i}{a}(u) = p_cae.ok{i}{a}(u) + epsilon; m_cae = cae; m_cae.ok{i}{a}(u) = m_cae.ok{i}{a}(u) - epsilon; [m_cae, p_cae] = caerun(m_cae, p_cae, x, y); d = (p_cae.L - m_cae.L) / (2 * epsilon); % cae.dok{i}{a}(u) = d; e = abs(d - cae.dok{i}{a}(u)); if e > er disp('OUTPUT KERNEL numerical gradient checking failed'); disp(e); disp(d / cae.dok{i}{a}(u)); % keyboard end end end for i = 1 : numel(cae.i) for u = 1 : numel(cae.ik{i}{a}) p_cae = cae; m_cae = cae; p_cae.ik{i}{a}(u) = p_cae.ik{i}{a}(u) + epsilon; m_cae.ik{i}{a}(u) = m_cae.ik{i}{a}(u) - epsilon; [m_cae, p_cae] = caerun(m_cae, p_cae, x, y); d = (p_cae.L - m_cae.L) / (2 * epsilon); % cae.dik{i}{a}(u) = d; e = abs(d - cae.dik{i}{a}(u)); if e > er disp('INPUT KERNEL numerical gradient checking failed'); disp(e); disp(d / cae.dik{i}{a}(u)); end end end end disp('done') end function [m_cae, p_cae] = caerun(m_cae, p_cae, x, y) m_cae = caeup(m_cae, x); m_cae = caedown(m_cae); m_cae = caebp(m_cae, y); p_cae = caeup(p_cae, x); p_cae = caedown(p_cae); p_cae = caebp(p_cae, y); end %function checknumgrad(cae,what,x,y) % epsilon = 1e-4; % er = 1e-9; % % for i = 1 : numel(eval(what)) % if iscell(eval(['cae.' what])) % checknumgrad(cae,[what '{' num2str(i) '}'], x, y) % else % p_cae = cae; % m_cae = cae; % eval(['p_cae.' what '(' num2str(i) ')']) = eval([what '(' num2str(i) ')']) + epsilon; % eval(['m_cae.' what '(' num2str(i) ')']) = eval([what '(' num2str(i) ')']) - epsilon; % % m_cae = caeff(m_cae, x); m_cae = caedown(m_cae); m_cae = caebp(m_cae, y); % p_cae = caeff(p_cae, x); p_cae = caedown(p_cae); p_cae = caebp(p_cae, y); % % d = (p_cae.L - m_cae.L) / (2 * epsilon); % e = abs(d - eval(['cae.d' what '(' num2str(i) ')'])); % if e > er % error('numerical gradient checking failed'); % end % end % end % % end