review fix

Author: Grégoire

doc/rnnslu.txt

@@ -172,13 +172,14 @@ Using Theano, it gives::
 
     # nv :: size of our vocabulary
     # de :: dimension of the embedding space
-    nv, de = 1000, 50
+    # cs :: context window size 
+    nv, de, cs = 1000, 50, 5
 
     embeddings = theano.shared(0.2 * numpy.random.uniform(-1.0, 1.0, \
         (nv+1, de)).astype(theano.config.floatX)) # add one for PADDING at the end
 
     idxs = T.imatrix() # as many columns as words in the context window and as many lines as words in the sentence
-    x, _ = theano.scan(fn=lambda idx: embeddings[idx].flatten(), sequences=idxs)
+    x    = self.emb[idxs].reshape((idxs.shape[0], de*cs))
 
 The x symbolic variable corresponds to a matrix of shape (number of words in the
 sentences, dimension of the embedding space X context window size).