open source pkg v1

pkg/OpenFace/model_training/CCNF/CCRF/lib/gradientCCRFFull.m

@@ -0,0 +1,39 @@
+function [ gradientParams, SigmaInvs, CholDecomps, Sigmas ] = gradientCCRFFull( params, lambda_a, lambda_b, PrecalcBs, x, y, Precalc_yBys, PrecalcBsFlat)
+%GRADIENTPRF Summary of this function goes here
+%   Detailed explanation goes here
+
+    nExamples = numel(x);
+
+    numBetas = size(PrecalcBsFlat{1},2);
+    numAlphas = numel(params) - numBetas;
+    
+    alphasInit = params(1:numAlphas);
+    betasInit = params(numAlphas+1:end);
+    gradientParams = zeros(size(params));
+    
+    % These might be use to calculate the LogLikelihood, don't want to
+    % recompute them
+    SigmaInvs = cell(nExamples, 1);
+    CholDecomps = cell(nExamples, 1);
+    Sigmas = cell(nExamples, 1);
+    gradients = zeros(nExamples, numel(params));
+    for q = 1 : nExamples
+
+        yq = y{q};
+        xq = x{q};
+
+        PrecalcB = PrecalcBs{q};
+        PrecalcB_flat = PrecalcBsFlat{q};
+        
+        [ logGradientsAlphas, logGradientsBetas, SigmaInv, CholDecomp, Sigma ] = gradientCCRF_withoutReg(alphasInit, betasInit, PrecalcB, xq, yq, Precalc_yBys(q, :), PrecalcB_flat);
+        SigmaInvs{q} = SigmaInv;
+        CholDecomps{q} = CholDecomp;
+        Sigmas{q} = Sigma;
+        
+        gradients(q,:) = [logGradientsAlphas; logGradientsBetas];
+    end
+    gradientParams = sum(gradients,1)';
+    regAlpha = alphasInit * lambda_a;
+    regBeta = betasInit * lambda_b;
+    gradientParams = gradientParams - [regAlpha; regBeta];
+end