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authorPaul Baltescu <pauldb89@gmail.com>2013-02-21 14:13:55 +0000
committerPaul Baltescu <pauldb89@gmail.com>2013-02-21 14:13:55 +0000
commitb5491898549c61bd799d199aa9178a8394a1ef69 (patch)
treefb2686a2aae03ff07bcdf4cd47e8c3191eff8d1e /training/crf
parent0187447a643c3ea262b13b3052cb1531990eafe6 (diff)
parentc17d9c23d023a5c08656376944f636180f0a437b (diff)
Merge branch 'master' of https://github.com/pauldb89/cdec
Diffstat (limited to 'training/crf')
-rw-r--r--training/crf/Makefile.am22
-rw-r--r--training/crf/baum_welch_example/README.md32
-rw-r--r--training/crf/baum_welch_example/cdec.ini5
-rwxr-xr-xtraining/crf/baum_welch_example/random_init.pl9
-rw-r--r--training/crf/baum_welch_example/tagset.txt1
-rw-r--r--training/crf/baum_welch_example/train.txt2000
-rw-r--r--training/crf/mpi_baum_welch.cc316
7 files changed, 2376 insertions, 9 deletions
diff --git a/training/crf/Makefile.am b/training/crf/Makefile.am
index d203df25..4a8c30fd 100644
--- a/training/crf/Makefile.am
+++ b/training/crf/Makefile.am
@@ -4,24 +4,28 @@ bin_PROGRAMS = \
mpi_extract_features \
mpi_extract_reachable \
mpi_flex_optimize \
- mpi_online_optimize
+ mpi_online_optimize \
+ mpi_baum_welch
+
+mpi_baum_welch_SOURCES = mpi_baum_welch.cc
+mpi_baum_welch_LDADD = ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
mpi_online_optimize_SOURCES = mpi_online_optimize.cc
-mpi_online_optimize_LDADD = $(top_srcdir)/training/utils/libtraining_utils.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_online_optimize_LDADD = ../../training/utils/libtraining_utils.a ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
mpi_flex_optimize_SOURCES = mpi_flex_optimize.cc
-mpi_flex_optimize_LDADD = $(top_srcdir)/training/utils/libtraining_utils.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_flex_optimize_LDADD = ../../training/utils/libtraining_utils.a ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
mpi_extract_reachable_SOURCES = mpi_extract_reachable.cc
-mpi_extract_reachable_LDADD = $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_extract_reachable_LDADD = ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
mpi_extract_features_SOURCES = mpi_extract_features.cc
-mpi_extract_features_LDADD = $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_extract_features_LDADD = ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
-mpi_batch_optimize_SOURCES = mpi_batch_optimize.cc cllh_observer.cc
-mpi_batch_optimize_LDADD = $(top_srcdir)/training/utils/libtraining_utils.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_batch_optimize_SOURCES = mpi_batch_optimize.cc cllh_observer.cc cllh_observer.h
+mpi_batch_optimize_LDADD = ../../training/utils/libtraining_utils.a ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
-mpi_compute_cllh_SOURCES = mpi_compute_cllh.cc cllh_observer.cc
-mpi_compute_cllh_LDADD = $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/klm/search/libksearch.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a $(top_srcdir)/klm/lm/libklm.a $(top_srcdir)/klm/util/libklm_util.a -lz
+mpi_compute_cllh_SOURCES = mpi_compute_cllh.cc cllh_observer.cc cllh_observer.h
+mpi_compute_cllh_LDADD = ../../decoder/libcdec.a ../../klm/search/libksearch.a ../../mteval/libmteval.a ../../utils/libutils.a ../../klm/lm/libklm.a ../../klm/util/libklm_util.a ../../klm/util/double-conversion/libklm_util_double.a -lz
AM_CPPFLAGS = -DBOOST_TEST_DYN_LINK -W -Wall -Wno-sign-compare -I$(top_srcdir)/training -I$(top_srcdir)/training/utils -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval
diff --git a/training/crf/baum_welch_example/README.md b/training/crf/baum_welch_example/README.md
new file mode 100644
index 00000000..97525da5
--- /dev/null
+++ b/training/crf/baum_welch_example/README.md
@@ -0,0 +1,32 @@
+Here's how to do Baum-Welch training with `cdec`.
+
+## Set the tags you want.
+
+First, set the number of tags you want in tagset.txt (these
+can be any symbols, listed one after another, separated
+by whitespace), e.g.:
+
+ C1 C2 C3 C4
+
+## Extract the parameter feature names
+
+ ../mpi_extract_features -c cdec.ini -t train.txt
+
+If you have compiled with MPI, you can use `mpirun`:
+
+ mpirun -np 8 ../mpi_extract_features -c cdec.ini -t train.txt
+
+## Randomly initialize the weights file
+
+ sort -u features.* | ./random_init.pl > weights.init
+
+## Run training
+
+ ../mpi_baum_welch -c cdec.ini -t train.txt -w weights.init -n 50
+
+Again, if you have compiled with MPI, you can use `mpirun`:
+
+ mpirun -np 8 ../mpi_baum_welch -c cdec.ini -t train.txt -w weights.init -n 50
+
+The `-n` flag indicates how many iterations to run for.
+
diff --git a/training/crf/baum_welch_example/cdec.ini b/training/crf/baum_welch_example/cdec.ini
new file mode 100644
index 00000000..61203da7
--- /dev/null
+++ b/training/crf/baum_welch_example/cdec.ini
@@ -0,0 +1,5 @@
+feature_function=Tagger_BigramIndicator
+feature_function=LexicalPairIndicator
+formalism=tagger
+tagger_tagset=tagset.txt
+intersection_strategy=full
diff --git a/training/crf/baum_welch_example/random_init.pl b/training/crf/baum_welch_example/random_init.pl
new file mode 100755
index 00000000..98467ed1
--- /dev/null
+++ b/training/crf/baum_welch_example/random_init.pl
@@ -0,0 +1,9 @@
+#!/usr/bin/perl -w
+while(<>) {
+ chomp;
+ my ($a,$b,@d) =split /\s+/;
+ die "Bad input" if scalar @d > 0;
+ $r = -rand() * rand() - 0.5;
+ $r = 0 if $a =~ /^Uni:/;
+ print "$a $r\n";
+}
diff --git a/training/crf/baum_welch_example/tagset.txt b/training/crf/baum_welch_example/tagset.txt
new file mode 100644
index 00000000..93a48451
--- /dev/null
+++ b/training/crf/baum_welch_example/tagset.txt
@@ -0,0 +1 @@
+1 2 3 4
diff --git a/training/crf/baum_welch_example/train.txt b/training/crf/baum_welch_example/train.txt
new file mode 100644
index 00000000..e9c3455e
--- /dev/null
+++ b/training/crf/baum_welch_example/train.txt
@@ -0,0 +1,2000 @@
+t h e
+t o
+o f
+i n
+a n d
+a
+s a i d
+f o r
+o n
+t h a t
+w i t h
+w a s
+i s
+b y
+a t
+h e
+a s
+f r o m
+i t
+h a s
+b e
+h i s
+h a v e
+w i l l
+a n
+a r e
+w e r e
+b u t
+n o t
+w h o
+a f t e r
+h a d
+y e a r
+i t s
+t w o
+t h i s
+w h i c h
+t h e y
+t h e i r
+g o v e r n m e n t
+b e e n
+w e
+p e r c e n t
+w o u l d
+n e w
+i
+a l s o
+u p
+m o r e
+o n e
+p e o p l e
+f i r s t
+l a s t
+a b o u t
+c h i n a
+p r e s i d e n t
+o v e r
+m i l l i o n
+o r
+o u t
+w o r l d
+w h e n
+a l l
+o t h e r
+m i n i s t e r
+t h r e e
+t h a n
+u n i t e d
+t h e r e
+a g a i n s t
+i n t o
+c o u n t r y
+s o m e
+p o l i c e
+n o
+t i m e
+y e a r s
+s t a t e
+w e d n e s d a y
+t u e s d a y
+t h u r s d a y
+s t a t e s
+m o n d a y
+u s
+c o u l d
+i f
+f r i d a y
+s i n c e
+b i l l i o n
+s h e
+f o r e i g n
+o f f i c i a l s
+d a y
+i n t e r n a t i o n a l
+h e r
+b e t w e e n
+o n l y
+b e f o r e
+s o u t h
+w h i l e
+d u r i n g
+n a t i o n a l
+t o l d
+s e c o n d
+g r o u p
+f o u r
+d o w n
+c i t y
+p a r t y
+t h e m
+s e c u r i t y
+d o
+m a d e
+d o l l a r s
+p o i n t s
+u n d e r
+m i l i t a r y
+b e c a u s e
+w e e k
+c o u n t r i e s
+c a n
+c h i n e s e
+o f f
+s u n d a y
+m o s t
+s o
+h i m
+e c o n o m i c
+f o r m e r
+i r a q
+f i v e
+s a t u r d a y
+a c c o r d i n g
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+o f f i c i a l
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+i n c l u d i n g
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+y o u
+i s r a e l
+t a l k s
+e n d
+t a k e
+e x p e c t e d
+p o l i t i c a l
+s i x
+s u c h
+b o t h
+m a k e
+h o m e
+l o c a l
+j a p a n
+r u s s i a
+s a y i n g
+g e n e r a l
+t o p
+a n o t h e r
+e u r o p e a n
+n o r t h
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+m a j o r
+s t a t e m e n t
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+i s r a e l i
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+c a p i t a l
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+s p o k e s m a n
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+o r d e r
+u n i v e r s i t y
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+p l a y e d
+b i g
+c a r
+t r y i n g
+e n g l a n d
+q u o t e d
+d e
+a l o n g
+i s l a m i c
+o u t s i d e
+t r a d i n g
+e d s
+c u t
+a c t i o n
+p r o b l e m s
+v i c e
+w o r k i n g
+y e n
+b u i l d i n g
+s i g n e d
+k n o w n
+c h a n g e
+c h a r g e s
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+j o u r n a l i s t s
+i n c r e a s i n g
+s t a t i s t i c s
+d e s c r i b e d
+b u r e a u
+i n j u r i e s
+p r o v i d e d
+j o i n e d
+i m m e d i a t e
+d e b a t e
+i m p a c t
+m e s s a g e
+m e e t i n g s
+r e q u e s t
+s c h o o l s
+o c c u r r e d
+r e m a r k s
+c o m m i t t e d
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+t o u g h
+s p o k e
+s t r i p
+f a c e s
+c r o w d
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+w a r n i n g
+s t o r y
+q u a l i t y
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+f r e e d o m
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+m a r t i n
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+a n y t h i n g
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+i n t e r e s t s
+n e i g h b o r i n g
+d o c t o r s
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+s h i p
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+b l a i r
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+a f p
+s u g g e s t e d
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+a n n a n
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+l a
+c o n s u m e r
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+c o m p u t e r
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+d r a f t
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+p a r t l y
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+e
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+g r e a t e r
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+c u t s
+r i c h a r d
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+l i n k e d
+p e a c e f u l
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+t o u r i s t s
+m a i n l y
+p r i s o n e r s
+p o w e r f u l
+c r o a t i a
+f i l e d
+k u w a i t
+f o r u m
+r e s e r v e
+m i l a n
+b l a s t
+a n n i v e r s a r y
+a t t e n d e d
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+d e v e l o p e d
+c e r t a i n
+b e l o w
+f e l t
+p r o v i n c i a l
+c y p r u s
+c r i t i c i z e d
+o p p o r t u n i t y
+s m i t h
+p o l i t i c s
+s e l f
+h u m a n i t a r i a n
+r e a s o n
+l a w y e r s
+r e v e n u e
+d o c u m e n t s
+w r o t e
+q u e s t i o n s
+n o r w a y
+d o w
+p a n e l
+f e a r
+s e n t e n c e d
+b a n n e d
+c i v i l i a n
+c u l t u r a l
+p e r s o n n e l
+b e l g i u m
+a b u
+c a p a c i t y
+a m o u n t
+s e c u r i t i e s
+b l o o d
+s i g n i f i c a n t
+e x p e r i e n c e
+a s e a n
+h o u s i n g
+j o h n s o n
+p h o t o s
+r o y a l
+i m p o r t s
+a d d i t i o n a l
+y e l t s i n
+c d y
+h e a r d
+t h o m a s
+b a n k i n g
+l e a d s
+v i s i t e d
+f e a r s
+u g a n d a
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+c o n t r o l l e d
+d e m a n d s
+i n s t i t u t i o n s
+a l i
+c h r i s t i a n
+s t o r m
+f o r e c a s t
+g r a f
+f i g h t e r s
+s t r e e t s
+r e s p e c t
+s p o t
+w e b
+m i s s e d
+s c i e n c e
+h e a d s
+h i t s
+m a s s i v e
+c u l t u r e
+c o u p l e
+v e n e z u e l a
+r e p o r t e d l y
+i n s u r a n c e
+s p r e a d
+s o l u t i o n
+p l a c e d
+s e r v e d
+f a c i l i t i e s
+s t r a t e g y
+t e c h n i c a l
+s t e p s
+d e e p
+h o p e d
+d e c i d e
+s a l e
+j a i l
+d i s c u s s e d
+s a v e
+n e p a l
+a r a b i a
+e n v o y
+a t t a c k e d
+w a y s
+r e c e i v e
+h a p p y
+h a l l
+g u i l t y
+p r a c t i c e
+l o v e
+e u r o s
+o p e r a t i n g
+c h a n g e d
+b o s t o n
+d e c a d e
+d e f i c i t
+p r o d u c t
+l i n e s
+p a t i e n t s
+f r i e n d s
+s y d n e y
+a c c o r d
+t i e d
+s p e e d
+w o r d s
+t i e
+s c o r e
+c o n d u c t e d
+c r i t i c i s m
+m u s l i m s
+b r o t h e r
+c l a s s
+r o m a n i a
+h e l p i n g
+f a s t
+h a p p e n e d
+d e f e n d i n g
+n a v y
+w i t n e s s e s
+f u l l y
+s u s p e c t
+i s l a n d s
+m a i n t a i n
+p r e s e n c e
+j a k a r t a
+p a c k a g e
+y a r d s
+g a i n
+a c c o u n t
+s q u a d
+s h a r o n
+w i n g
+a c t i o n s
+a t h e n s
+s t r a t e g i c
+s t r e n g t h e n
+f r i e n d l y
+d e s t r o y e d
+a p p a r e n t l y
+c o n s e r v a t i v e
+g a i n s
+f a i l u r e
+f u t u r e s
+s h o t s
+r e l a t i o n s h i p
+c o m m i s s i o n e r
+m a l a y s i a n
+r e q u i r e d
+a t l a n t a
+a g r e e
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+s t r i k e r
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+h o u s e s
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+s a f e
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+f r e s h
+v i d e o
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+p u l l e d
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+d a u g h t e r
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+s h o r t l y
+c o m m e r c e
+n e t a n y a h u
+a d v a n c e
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+a b r o a d
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+l o a n
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+e l e c t r i c i t y
+t e h r a n
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+n i n t h
+o n l i n e
+h e l i c o p t e r
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+p a r t n e r s
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+m a c a o
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+s u n
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+t e l l
+s o u t h w e s t
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+r e s o l v e
+c h a n c e s
+m i a m i
+e l
+e n t i r e
diff --git a/training/crf/mpi_baum_welch.cc b/training/crf/mpi_baum_welch.cc
new file mode 100644
index 00000000..d69b1769
--- /dev/null
+++ b/training/crf/mpi_baum_welch.cc
@@ -0,0 +1,316 @@
+#include <sstream>
+#include <iostream>
+#include <vector>
+#include <cassert>
+#include <cmath>
+
+#include "config.h"
+#ifdef HAVE_MPI
+#include <boost/mpi/timer.hpp>
+#include <boost/mpi.hpp>
+namespace mpi = boost::mpi;
+#endif
+
+#include <boost/unordered_map.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/shared_ptr.hpp>
+#include <boost/program_options.hpp>
+#include <boost/program_options/variables_map.hpp>
+
+#include "sentence_metadata.h"
+#include "verbose.h"
+#include "hg.h"
+#include "prob.h"
+#include "inside_outside.h"
+#include "ff_register.h"
+#include "decoder.h"
+#include "filelib.h"
+#include "stringlib.h"
+#include "fdict.h"
+#include "weights.h"
+#include "sparse_vector.h"
+
+using namespace std;
+namespace po = boost::program_options;
+
+bool InitCommandLine(int argc, char** argv, po::variables_map* conf) {
+ po::options_description opts("Configuration options");
+ opts.add_options()
+ ("input_weights,w",po::value<string>(),"Input feature weights file")
+ ("iterations,n",po::value<unsigned>()->default_value(50), "Number of training iterations")
+ ("training_data,t",po::value<string>(),"Training data")
+ ("decoder_config,c",po::value<string>(),"Decoder configuration file");
+ po::options_description clo("Command line options");
+ clo.add_options()
+ ("config", po::value<string>(), "Configuration file")
+ ("help,h", "Print this help message and exit");
+ po::options_description dconfig_options, dcmdline_options;
+ dconfig_options.add(opts);
+ dcmdline_options.add(opts).add(clo);
+
+ po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
+ if (conf->count("config")) {
+ ifstream config((*conf)["config"].as<string>().c_str());
+ po::store(po::parse_config_file(config, dconfig_options), *conf);
+ }
+ po::notify(*conf);
+
+ if (conf->count("help") || !conf->count("input_weights") || !(conf->count("training_data")) || !conf->count("decoder_config")) {
+ cerr << dcmdline_options << endl;
+ return false;
+ }
+ return true;
+}
+
+void ReadTrainingCorpus(const string& fname, int rank, int size, vector<string>* c) {
+ ReadFile rf(fname);
+ istream& in = *rf.stream();
+ string line;
+ int lc = 0;
+ while(in) {
+ getline(in, line);
+ if (!in) break;
+ if (lc % size == rank) c->push_back(line);
+ ++lc;
+ }
+}
+
+static const double kMINUS_EPSILON = -1e-6;
+
+struct TrainingObserver : public DecoderObserver {
+ void Reset() {
+ acc_grad.clear();
+ acc_obj = 0;
+ total_complete = 0;
+ trg_words = 0;
+ }
+
+ void SetLocalGradientAndObjective(vector<double>* g, double* o) const {
+ *o = acc_obj;
+ for (SparseVector<double>::const_iterator it = acc_grad.begin(); it != acc_grad.end(); ++it)
+ (*g)[it->first] = it->second;
+ }
+
+ virtual void NotifyDecodingStart(const SentenceMetadata& smeta) {
+ state = 1;
+ }
+
+ // compute model expectations, denominator of objective
+ virtual void NotifyTranslationForest(const SentenceMetadata& smeta, Hypergraph* hg) {
+ assert(state == 1);
+ trg_words += smeta.GetSourceLength();
+ state = 2;
+ SparseVector<prob_t> exps;
+ const prob_t z = InsideOutside<prob_t,
+ EdgeProb,
+ SparseVector<prob_t>,
+ EdgeFeaturesAndProbWeightFunction>(*hg, &exps);
+ exps /= z;
+ for (SparseVector<prob_t>::iterator it = exps.begin(); it != exps.end(); ++it)
+ acc_grad.add_value(it->first, it->second.as_float());
+
+ acc_obj += log(z);
+ }
+
+ // compute "empirical" expectations, numerator of objective
+ virtual void NotifyAlignmentForest(const SentenceMetadata& smeta, Hypergraph* hg) {
+ cerr << "Shouldn't get an alignment forest!\n";
+ abort();
+ }
+
+ virtual void NotifyDecodingComplete(const SentenceMetadata& smeta) {
+ ++total_complete;
+ }
+
+ int total_complete;
+ SparseVector<double> acc_grad;
+ double acc_obj;
+ unsigned trg_words;
+ int state;
+};
+
+void ReadConfig(const string& ini, vector<string>* out) {
+ ReadFile rf(ini);
+ istream& in = *rf.stream();
+ while(in) {
+ string line;
+ getline(in, line);
+ if (!in) continue;
+ out->push_back(line);
+ }
+}
+
+void StoreConfig(const vector<string>& cfg, istringstream* o) {
+ ostringstream os;
+ for (int i = 0; i < cfg.size(); ++i) { os << cfg[i] << endl; }
+ o->str(os.str());
+}
+
+#if 0
+template <typename T>
+struct VectorPlus : public binary_function<vector<T>, vector<T>, vector<T> > {
+ vector<T> operator()(const vector<int>& a, const vector<int>& b) const {
+ assert(a.size() == b.size());
+ vector<T> v(a.size());
+ transform(a.begin(), a.end(), b.begin(), v.begin(), plus<T>());
+ return v;
+ }
+};
+#endif
+
+int main(int argc, char** argv) {
+#ifdef HAVE_MPI
+ mpi::environment env(argc, argv);
+ mpi::communicator world;
+ const int size = world.size();
+ const int rank = world.rank();
+#else
+ const int size = 1;
+ const int rank = 0;
+#endif
+ SetSilent(true); // turn off verbose decoder output
+ register_feature_functions();
+
+ po::variables_map conf;
+ if (!InitCommandLine(argc, argv, &conf)) return 1;
+ const unsigned iterations = conf["iterations"].as<unsigned>();
+
+ // load cdec.ini and set up decoder
+ vector<string> cdec_ini;
+ ReadConfig(conf["decoder_config"].as<string>(), &cdec_ini);
+ istringstream ini;
+ StoreConfig(cdec_ini, &ini);
+ Decoder* decoder = new Decoder(&ini);
+ if (decoder->GetConf()["input"].as<string>() != "-") {
+ cerr << "cdec.ini must not set an input file\n";
+ return 1;
+ }
+
+ // load initial weights
+ if (rank == 0) { cerr << "Loading weights...\n"; }
+ vector<weight_t>& lambdas = decoder->CurrentWeightVector();
+ Weights::InitFromFile(conf["input_weights"].as<string>(), &lambdas);
+ if (rank == 0) { cerr << "Done loading weights.\n"; }
+
+ // freeze feature set (should be optional?)
+ const bool freeze_feature_set = true;
+ if (freeze_feature_set) FD::Freeze();
+
+ const int num_feats = FD::NumFeats();
+ if (rank == 0) cerr << "Number of features: " << num_feats << endl;
+ lambdas.resize(num_feats);
+
+ vector<double> gradient(num_feats, 0.0);
+ vector<double> rcv_grad;
+ rcv_grad.clear();
+ bool converged = false;
+
+ vector<string> corpus, test_corpus;
+ ReadTrainingCorpus(conf["training_data"].as<string>(), rank, size, &corpus);
+ assert(corpus.size() > 0);
+ if (conf.count("test_data"))
+ ReadTrainingCorpus(conf["test_data"].as<string>(), rank, size, &test_corpus);
+
+ // build map from feature id to the accumulator that should normalize
+ boost::unordered_map<std::string, boost::unordered_map<int, double>, boost::hash<std::string> > ccs;
+ vector<boost::unordered_map<int, double>* > cpd_to_acc;
+ if (rank == 0) {
+ cpd_to_acc.resize(num_feats);
+ for (unsigned f = 1; f < num_feats; ++f) {
+ string normalizer;
+ //0 ||| 7 9 ||| Bi:BOS_7=1 Bi:7_9=1 Bi:9_EOS=1 Id:a:7=1 Uni:7=1 Id:b:9=1 Uni:9=1 ||| 0
+ const string& fstr = FD::Convert(f);
+ if (fstr.find("Bi:") == 0) {
+ size_t pos = fstr.rfind('_');
+ if (pos < fstr.size())
+ normalizer = fstr.substr(0, pos);
+ } else if (fstr.find("Id:") == 0) {
+ size_t pos = fstr.rfind(':');
+ if (pos < fstr.size()) {
+ normalizer = "Emit:";
+ normalizer += fstr.substr(pos);
+ }
+ }
+ if (normalizer.size() > 0) {
+ boost::unordered_map<int, double>& acc = ccs[normalizer];
+ cpd_to_acc[f] = &acc;
+ }
+ }
+ }
+
+ TrainingObserver observer;
+ int iteration = 0;
+ while (!converged) {
+ ++iteration;
+ observer.Reset();
+#ifdef HAVE_MPI
+ mpi::timer timer;
+ world.barrier();
+#endif
+ if (rank == 0) {
+ cerr << "Starting decoding... (~" << corpus.size() << " sentences / proc)\n";
+ cerr << " Testset size: " << test_corpus.size() << " sentences / proc)\n";
+ for(boost::unordered_map<string, boost::unordered_map<int,double>, boost::hash<string> >::iterator it = ccs.begin(); it != ccs.end(); ++it)
+ it->second.clear();
+ }
+ for (int i = 0; i < corpus.size(); ++i)
+ decoder->Decode(corpus[i], &observer);
+ cerr << " process " << rank << '/' << size << " done\n";
+ fill(gradient.begin(), gradient.end(), 0);
+ double objective = 0;
+ observer.SetLocalGradientAndObjective(&gradient, &objective);
+
+ unsigned total_words = 0;
+#ifdef HAVE_MPI
+ double to = 0;
+ rcv_grad.resize(num_feats, 0.0);
+ mpi::reduce(world, &gradient[0], gradient.size(), &rcv_grad[0], plus<double>(), 0);
+ swap(gradient, rcv_grad);
+ rcv_grad.clear();
+
+ reduce(world, observer.trg_words, total_words, std::plus<unsigned>(), 0);
+ mpi::reduce(world, objective, to, plus<double>(), 0);
+ objective = to;
+#else
+ total_words = observer.trg_words;
+#endif
+ if (rank == 0) { // run optimizer only on rank=0 node
+ cerr << "TRAINING CORPUS: ln p(x)=" << objective << "\t log_2 p(x) = " << (objective/log(2)) << "\t cross entropy = " << (objective/log(2) / total_words) << "\t ppl = " << pow(2, (-objective/log(2) / total_words)) << endl;
+ for (unsigned f = 1; f < num_feats; ++f) {
+ boost::unordered_map<int, double>* m = cpd_to_acc[f];
+ if (m && gradient[f]) {
+ (*m)[f] += gradient[f];
+ }
+ for(boost::unordered_map<string, boost::unordered_map<int,double>, boost::hash<string> >::iterator it = ccs.begin(); it != ccs.end(); ++it) {
+ const boost::unordered_map<int,double>& ccs = it->second;
+ double z = 0;
+ for (boost::unordered_map<int,double>::const_iterator ci = ccs.begin(); ci != ccs.end(); ++ci)
+ z += ci->second + 1e-09;
+ double lz = log(z);
+ for (boost::unordered_map<int,double>::const_iterator ci = ccs.begin(); ci != ccs.end(); ++ci)
+ lambdas[ci->first] = log(ci->second + 1e-09) - lz;
+ }
+ }
+ Weights::SanityCheck(lambdas);
+ Weights::ShowLargestFeatures(lambdas);
+
+ converged = (iteration == iterations);
+
+ string fname = "weights.cur.gz";
+ if (converged) { fname = "weights.final.gz"; }
+ ostringstream vv;
+ vv << "Objective = " << objective << " (eval count=" << iteration << ")";
+ const string svv = vv.str();
+ Weights::WriteToFile(fname, lambdas, true, &svv);
+ } // rank == 0
+ int cint = converged;
+#ifdef HAVE_MPI
+ mpi::broadcast(world, &lambdas[0], lambdas.size(), 0);
+ mpi::broadcast(world, cint, 0);
+ if (rank == 0) { cerr << " ELAPSED TIME THIS ITERATION=" << timer.elapsed() << endl; }
+#endif
+ converged = cint;
+ }
+ return 0;
+}
+