time | Calls | line |
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| | 1 | function best_model = newton(prob, prob_v, param, model, net)
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| | 2 |
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193.105 | 1 | 3 | [net, f, grad] = fungrad_minibatch(prob, param, model, net, 'fungrad');
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< 0.001 | 1 | 4 | fprintf('initial f: %g\n', f);
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| | 5 |
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< 0.001 | 1 | 6 | best_model = model;
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< 0.001 | 1 | 7 | if ~isempty(fieldnames(prob_v))
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| | 8 | best_val_acc = 0.0;
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< 0.001 | 1 | 9 | end
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| | 10 |
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< 0.001 | 1 | 11 | total_CG = 0;
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| | 12 |
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< 0.001 | 1 | 13 | for k = 1 : param.iter_max
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0.002 | 5 | 14 | if mod(k, ceil(prob.l/param.GNsize)) == 1 || (prob.l == param.GNsize)
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0.007 | 1 | 15 | batch_idx = assign_inst_idx(param.GNsize, prob.l);
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< 0.001 | 5 | 16 | end
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< 0.001 | 5 | 17 | current_batch = mod(k-1, ceil(prob.l/param.GNsize)) + 1;
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656.868 | 5 | 18 | [x, CGiter, gs, sGs] = CG(prob.data(:, batch_idx{current_batch}), param, model, net, grad);
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< 0.001 | 5 | 19 | total_CG = total_CG + CGiter;
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| | 20 |
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| | 21 | % line search
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< 0.001 | 5 | 22 | fold = f;
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< 0.001 | 5 | 23 | alpha = 1;
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< 0.001 | 5 | 24 | while 1
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0.019 | 5 | 25 | model = update_weights(model, alpha, x);
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< 0.001 | 5 | 26 | prered = alpha*gs + 0.5*(alpha^2)*sGs;
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| | 27 |
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421.656 | 5 | 28 | [~, f, ~] = fungrad_minibatch(prob, param, model, net, 'funonly');
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< 0.001 | 5 | 29 | actred = f - fold;
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< 0.001 | 5 | 30 | if (actred <= param.eta*alpha*gs)
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< 0.001 | 5 | 31 | break;
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| | 32 | end
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| | 33 | alpha = alpha * 0.5;
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| | 34 | end
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0.004 | 5 | 35 | param = update_lambda(param, actred, prered);
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933.018 | 5 | 36 | [net, f, grad] = fungrad_minibatch(prob, param, model, net, 'fungrad');
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| | 37 |
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| | 38 | % gradient norm
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0.008 | 5 | 39 | gnorm = calc_gnorm(grad, model.L);
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| | 40 |
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< 0.001 | 5 | 41 | if ~isempty(fieldnames(prob_v))
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| | 42 | % update best_model by val_acc
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| | 43 | val_results = predict(prob_v, param, model, net);
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| | 44 | val_acc = cal_accuracy(val_results, prob_v.y);
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| | 45 | if val_acc > best_val_acc
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| | 46 | best_model = model;
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| | 47 | best_val_acc = val_acc;
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| | 48 | end
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| | 49 | fprintf('%d-iter f: %g |g|: %g alpha: %g ratio: %g lambda: %g #CG: %d actred: %g prered: %g val_acc: %g\n', k, f, gnorm, alpha, actred/prered, param.lambda, CGiter, actred, prered, val_acc);
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< 0.001 | 5 | 50 | else
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< 0.001 | 5 | 51 | best_model = model;
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0.003 | 5 | 52 | fprintf('%d-iter f: %g |g|: %g alpha: %g ratio: %g lambda: %g #CG: %d actred: %g prered: %g\n', k, f, gnorm, alpha, actred/prered, param.lambda, CGiter, actred, prered);
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< 0.001 | 5 | 53 | end
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< 0.001 | 5 | 54 | end
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| | 55 |
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0.079 | 1 | 56 | fprintf('total_#CG: %d\n', total_CG);
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Other subfunctions in this file are not included in this listing.
