Left pad source and right pad target

fairseq/data.py

@@ -142,8 +142,8 @@ def skip_group_enumerator(it, ngpus, offset=0):
 class LanguagePairDataset(object):
 
     # padding constants
-    LEFT_PAD_SOURCE = False
-    LEFT_PAD_TARGET = True
+    LEFT_PAD_SOURCE = True
+    LEFT_PAD_TARGET = False
 
     def __init__(self, src, dst, pad_idx, eos_idx):
         self.src = src

fairseq/sequence_generator.py

@@ -61,10 +61,6 @@ class SequenceGenerator(object):
             cuda_device: GPU on which to do generation.
             timer: StopwatchMeter for timing generations.
         """
-
-        def lstrip_pad(tensor):
-            return tensor[tensor.eq(self.pad).sum():]
-
         if maxlen_b is None:
             maxlen_b = self.maxlen
 
@@ -80,8 +76,8 @@ class SequenceGenerator(object):
                 timer.stop(s['ntokens'])
             for i, id in enumerate(s['id']):
                 src = input['src_tokens'].data[i, :]
-                # remove padding from ref, which appears at the beginning
-                ref = lstrip_pad(s['target'].data[i, :])
+                # remove padding from ref
+                ref = utils.rstrip_pad(s['target'].data[i, :], self.pad)
                 yield id, src, ref, hypos[i]
 
     def generate(self, src_tokens, beam_size=None, maxlen=None):

fairseq/utils.py

@@ -202,3 +202,14 @@ def post_process_prediction(hypo_tokens, src_str, alignment, align_dict, dst_dic
         # Note that the dictionary can be modified inside the method.
         hypo_tokens = tokenizer.Tokenizer.tokenize(hypo_str, dst_dict, add_if_not_exist=True)
     return hypo_tokens, hypo_str, alignment
+
+
+def lstrip_pad(tensor, pad):
+    return tensor[tensor.eq(pad).sum():]
+
+
+def rstrip_pad(tensor, pad):
+    strip = tensor.eq(pad).sum()
+    if strip > 0:
+        return tensor[:-strip]
+    return tensor