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#include "minimizers/PRCG.hpp" |
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void PRCGMinimizer::init(){ |
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calcG(); |
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for(int i = 0; i < direction.size(); i++){ |
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direction[i] = -curG[i]; |
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} |
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} |
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int PRCGMinimizer::step(){ |
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int lsStatus; |
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prevF = curF; |
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prevG = curG; |
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prevX = curX; |
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//optimize along the search direction and reset minimum point value |
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lsStatus = doLineSearch(direction, stepSize); |
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if (lsStatus < 0) |
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return -1; |
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else |
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return 1; |
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} |
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void PRCGMinimizer::prepareStep(){ |
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std::vector<double> deltaGrad; |
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double beta; |
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size_t i; |
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deltaGrad.resize(ndim); |
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//calculate the new direction using Polak-Ribiere Conjugate Gradient |
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for(i = 0; i < curG.size(); i++) |
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deltaGrad[i] = curG[i] - prevG[i]; |
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#ifndef IS_MPI |
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beta = dotProduct(deltaGrad, curG) / dotProduct(prevG, prevG); |
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#else |
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double localDP1; |
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double localDP2; |
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double globalDP1; |
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double globalDP2; |
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|
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localDP1 = dotProduct(deltaGrad, curG); |
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localDP2 = dotProduct(prevG, prevG); |
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MPI_Allreduce(&localDP1, &globalDP1, 1, MPI_DOUBLE,MPI_SUM, MPI_COMM_WORLD); |
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MPI_Allreduce(&localDP2, &globalDP2, 1, MPI_DOUBLE,MPI_SUM, MPI_COMM_WORLD); |
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beta = globalDP1 / globalDP2; |
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#endif |
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for(i = 0; i < direction.size(); i++) |
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direction[i] = -curG[i] + beta * direction[i]; |
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} |
