Batch k-best MIRA is written and integrated into mert-moses.pl

Regression tests all check out, and kbmira seems to work fine
on a Hansard French->English task.

HypPackEnumerator class may be of interest to pro.cpp and future
optimizers, as it abstracts a lot of the boilerplate involved in
enumerating multiple k-best lists.

MiraWeightVector is not really mira-specific - just a weight vector
that enables efficient averaging. Could be useful to a perceptron
as well. Same goes for MiraFeatureVector.

Interaction with sparse features is written, but untested.

1 files changed, 3 insertions, 0 deletions

diff --git a/mert/FeatureDataIterator.h b/mert/FeatureDataIterator.h
index 58345829c..9bc5f03f7 100644
--- a/mert/FeatureDataIterator.h
+++ b/mert/FeatureDataIterator.h
@@ -61,6 +61,9 @@ class FeatureDataItem
     SparseVector sparse;
 };
 
+bool operator==(FeatureDataItem const& item1, FeatureDataItem const& item2);
+std::size_t hash_value(FeatureDataItem const& item);
+
 class FeatureDataIterator : 
   public boost::iterator_facade<FeatureDataIterator,
                                 const std::vector<FeatureDataItem>,