[update]对最近几个issue的更新

fastNLP/core/dataset.py

@@ -908,12 +908,17 @@ class DataSet(object):
         :param bool shuffle: 在split前是否shuffle一下
         :return: [ :class:`~fastNLP.读取后的DataSet` , :class:`~fastNLP.读取后的DataSet` ]
         """
+        assert len(self) > 1, f'DataSet with {len(self)} instance cannot be split.'
         assert isinstance(ratio, float)
         assert 0 < ratio < 1
         all_indices = [_ for _ in range(len(self))]
         if shuffle:
             np.random.shuffle(all_indices)
         split = int(ratio * len(self))
+        if split == 0:
+            error_msg = f'Dev DataSet has {split} instance after split.'
+            logger.error(error_msg)
+            raise IndexError(error_msg)
         dev_indices = all_indices[:split]
         train_indices = all_indices[split:]
         dev_set = DataSet()

fastNLP/core/vocabulary.py

@@ -209,7 +209,7 @@ class Vocabulary(object):
             self._word2idx = {}
             if self.padding is not None:
                 self._word2idx[self.padding] = len(self._word2idx)
-            if self.unknown is not None:
+            if (self.unknown is not None) and (self.unknown != self.padding):
                 self._word2idx[self.unknown] = len(self._word2idx)
         
         max_size = min(self.max_size, len(self.word_count)) if self.max_size else None

fastNLP/modules/encoder/attention.py

@@ -26,7 +26,7 @@ class DotAttention(nn.Module):
         self.value_size = value_size
         self.scale = math.sqrt(key_size)
         self.drop = nn.Dropout(dropout)
-        self.softmax = nn.Softmax(dim=2)
+        self.softmax = nn.Softmax(dim=-1)
 
     def forward(self, Q, K, V, mask_out=None):
         """