Multi-processing grammar extraction

+ various surface fixes

1 files changed, 5 insertions, 6 deletions

diff --git a/python/examples/rampion.py b/python/examples/rampion.py
index 66d89a61..30244cf7 100644
--- a/python/examples/rampion.py
+++ b/python/examples/rampion.py
@@ -15,7 +15,7 @@ cost = lambda c: 10 * (1 - c.score) # cost definition
 
 def rampion(decoder, sources, references):
     # Empty k-best lists
-    cs = [cdec.score.BLEU(refs).candidate_set() for refs in references]
+    candidate_sets = [cdec.score.BLEU(refs).candidate_set() for refs in references]
     # Weight vector -> sparse
     w = decoder.weights.tosparse()
     w0 = w.copy()
@@ -25,7 +25,7 @@ def rampion(decoder, sources, references):
         logging.info('Iteration {0}: translating...'.format(t+1))
         # Get the hypergraphs and extend the k-best lists
         hgs = []
-        for src, candidates in izip(sources, cs):
+        for src, candidates in izip(sources, candidate_sets):
             hg = decoder.translate(src)
             hgs.append(hg)
             candidates.add_kbest(hg, K)
@@ -36,17 +36,16 @@ def rampion(decoder, sources, references):
         for _ in range(T2):
             # y_i^+, h_i^+; i=1..N
             plus = [max(candidates, key=lambda c: w.dot(c.fmap) - cost(c)).fmap
-                    for candidates in cs]
+                    for candidates in candidate_sets]
             for _ in range(T3):
-                for fp, candidates in izip(plus, cs):
+                for fp, candidates in izip(plus, candidate_sets):
                     # y^-, h^-
                     fm = max(candidates, key=lambda c: w.dot(c.fmap) + cost(c)).fmap
                     # update weights (line 11-12)
                     w += eta * ((fp - fm) - C/N * (w - w0))
         logging.info('Updated weight vector: {0}'.format(dict(w)))
         # Update decoder weights
-        for fname, fval in w:
-            decoder.weights[fname] = fval
+        decoder.weights = w
 
 def main():
     logging.basicConfig(level=logging.INFO, format='%(message)s')