1 |
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2 |
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3 |
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4 | var math = require('./utils').math;
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5 | HiddenLayer = module.exports = function (settings) {
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6 | var self = this;
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7 | self.input = settings['input'];
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8 |
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9 | if(typeof settings['W'] === 'undefined') {
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10 | var a = 1. / settings['n_in'];
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11 | settings['W'] = math.randMat(settings['n_in'],settings['n_out'],-a,a);
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12 | }
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13 | if(typeof settings['b'] === 'undefined')
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14 | settings['b'] = math.zeroVec(settings['n_out']);
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15 | if(typeof settings['activation'] === 'undefined')
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16 | settings['activation'] = math.sigmoid;
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17 |
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18 | self.W = settings['W'];
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19 | self.b = settings['b'];
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20 | self.activation = settings['activation'];
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21 | }
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22 |
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23 | HiddenLayer.prototype.output = function(input) {
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24 | var self = this;
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25 | if(typeof input !== 'undefined')
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26 | self.input = input;
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27 |
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28 | var linearOutput = math.addMatVec(math.mulMat(self.input,self.W),self.b);
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29 | return math.activateMat(linearOutput,self.activation);
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30 | };
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31 |
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32 | HiddenLayer.prototype.linearOutput = function(input) {
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33 | var self = this;
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34 | if(typeof input !== 'undefined')
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35 | self.input = input;
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36 |
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37 | var linearOutput = math.addMatVec(math.mulMat(self.input,self.W),self.b);
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38 | return linearOutput;
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39 | }
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40 |
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41 | HiddenLayer.prototype.backPropagate = function (input) {
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42 | var self = this;
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43 | if(typeof input === 'undefined')
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44 | throw new Error("No BackPropagation Input.")
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45 |
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46 | var linearOutput = math.mulMat(input, m.transpose(self.W));
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47 | return linearOutput;
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48 | }
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49 |
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50 | HiddenLayer.prototype.sampleHgivenV = function(input) {
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51 | var self = this;
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52 | if(typeof input !== 'undefined')
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53 | self.input = input;
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54 |
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55 | var hMean = self.output();
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56 | var hSample = math.probToBinaryMat(hMean);
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57 | return hSample;
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58 | } |
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