Fix two bugs : 1. Add decode_list in ClassLabelEncoder, 2. Fix the bug for language model problem's beam search (#679)

* 1. add decode_list for ClassLabelEncoder
2. For language model problem(with no inputs), fix the wrong beam_size
searching in Transformer model.

* Make the transformer as the original one

Author: yynil

tensor2tensor/data_generators/text_encoder.py

@@ -208,10 +208,12 @@ def encode(self, label_str):
 
   def decode(self, label_id):
     if isinstance(label_id, list):
-      assert len(label_id) == 1
-      label_id, = label_id
+      return self._class_labels[label_id[0]]
     return self._class_labels[label_id]
 
+  def decode_list(self, ids):
+    return [self._class_labels[i] for i in ids]
+
   @property
   def vocab_size(self):
     return len(self._class_labels)

tensor2tensor/models/transformer.py

@@ -389,8 +389,10 @@ def forced_logits():
         top_beams=top_beams,
         alpha=alpha,
         batch_size=batch_size)
-    if partial_targets is not None:
+    if partial_targets is not None and beam_size == 1:
       ret["outputs"] = ret["outputs"][:, partial_targets_length:]
+    elif partial_targets is not None and beam_size > 1:
+        ret["outputs"] = ret["outputs"][:, :,partial_targets_length:]
     return ret