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authorAvneesh Saluja <asaluja@gmail.com>2013-03-28 18:28:16 -0700
committerAvneesh Saluja <asaluja@gmail.com>2013-03-28 18:28:16 -0700
commit3d8d656fa7911524e0e6885647173474524e0784 (patch)
tree81b1ee2fcb67980376d03f0aa48e42e53abff222 /training/dpmert/line_optimizer.h
parentbe7f57fdd484e063775d7abf083b9fa4c403b610 (diff)
parent96fedabebafe7a38a6d5928be8fff767e411d705 (diff)
fixed conflicts
Diffstat (limited to 'training/dpmert/line_optimizer.h')
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+#ifndef LINE_OPTIMIZER_H_
+#define LINE_OPTIMIZER_H_
+
+#include <vector>
+
+#include "sparse_vector.h"
+#include "error_surface.h"
+#include "sampler.h"
+
+class EvaluationMetric;
+class Weights;
+
+struct LineOptimizer {
+
+ // use MINIMIZE_SCORE for things like TER, WER
+ // MAXIMIZE_SCORE for things like BLEU
+ enum ScoreType { MAXIMIZE_SCORE, MINIMIZE_SCORE };
+
+ // merge all the error surfaces together into a global
+ // error surface and find (the middle of) the best segment
+ static double LineOptimize(
+ const EvaluationMetric* metric,
+ const std::vector<ErrorSurface>& envs,
+ const LineOptimizer::ScoreType type,
+ float* best_score,
+ const double epsilon = 1.0/65536.0);
+
+ // return a random vector of length 1 where all dimensions
+ // not listed in dimensions will be 0.
+ static void RandomUnitVector(const std::vector<int>& dimensions,
+ SparseVector<double>* axis,
+ RandomNumberGenerator<boost::mt19937>* rng);
+
+ // generate a list of directions to optimize; the list will
+ // contain the orthogonal vectors corresponding to the dimensions in
+ // primary and then additional_random_directions directions in those
+ // dimensions as well. All vectors will be length 1.
+ static void CreateOptimizationDirections(
+ const std::vector<int>& primary,
+ int additional_random_directions,
+ RandomNumberGenerator<boost::mt19937>* rng,
+ std::vector<SparseVector<double> >* dirs
+ , bool include_primary=true
+ );
+
+};
+
+#endif