jens
7b34529b24
git-svn-id: http://moon:8086/svn/matlab/trunk@91 801c6759-fa7c-4059-a304-17956f83a07c
43 lines
1002 B
Matlab
43 lines
1002 B
Matlab
function [ cost, grad, pred_prob] = supervised_dnn_cost( theta, ei, data, labels, pred_only)
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%SPNETCOSTSLAVE Slave cost function for simple phone net
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% Does all the work of cost / gradient computation
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% Returns cost broken into cross-entropy, weight norm, and prox reg
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% components (ceCost, wCost, pCost)
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%% default values
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po = false;
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if exist('pred_only','var')
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po = pred_only;
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end;
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%% reshape into network
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stack = params2stack(theta, ei);
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numHidden = numel(ei.layer_sizes) - 1;
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hAct = cell(numHidden+1, 1);
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gradStack = cell(numHidden+1, 1);
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%% forward prop
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%%% YOUR CODE HERE %%%
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%% return here if only predictions desired.
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if po
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cost = -1; ceCost = -1; wCost = -1; numCorrect = -1;
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grad = [];
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return;
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end;
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%% compute cost
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%%% YOUR CODE HERE %%%
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%% compute gradients using backpropagation
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%%% YOUR CODE HERE %%%
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%% compute weight penalty cost and gradient for non-bias terms
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%%% YOUR CODE HERE %%%
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%% reshape gradients into vector
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[grad] = stack2params(gradStack);
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end
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