From 5ca9348b98a519015c4080186ea1a6fe42ef4a2b Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Sun, 10 Nov 2013 03:56:11 -0500 Subject: fixes --- decoder/tromble_loss.h | 40 ---------------------------------------- 1 file changed, 40 deletions(-) delete mode 100644 decoder/tromble_loss.h (limited to 'decoder/tromble_loss.h') diff --git a/decoder/tromble_loss.h b/decoder/tromble_loss.h deleted file mode 100644 index fde33100..00000000 --- a/decoder/tromble_loss.h +++ /dev/null @@ -1,40 +0,0 @@ -#ifndef _TROMBLE_LOSS_H_ -#define _TROMBLE_LOSS_H_ - -#include -#include -#include - -#include "ff.h" -#include "wordid.h" - -// this may not be the most elegant way to implement this computation, but since we -// may need cube pruning and state splitting, we reuse the feature detector framework. -// the loss is then stored in a feature #0 (which is guaranteed to have weight 0 and -// never be a "real" feature). -class TrombleLossComputerImpl; -class TrombleLossComputer : private boost::base_from_member >, public FeatureFunction { - private: - typedef boost::scoped_ptr PImpl; - typedef FeatureFunction Base; - - public: - // String parameters are ref.txt num_ref weight1 weight2 ... weightn - // where ref.txt contains references on per line, with num_ref references per sentence - // The weights are the weight on each length n-gram. - explicit TrombleLossComputer(const std::string ¶ms); - - ~TrombleLossComputer(); - - protected: - virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, - const HG::Edge& edge, - const std::vector& ant_contexts, - SparseVector* features, - SparseVector* estimated_features, - void* out_context) const; - private: - const int fid_; -}; - -#endif -- cgit v1.2.3