keep_extend_vocab_only->keep_extended_vocab_only

wangxicoding · Feb 24, 2021 · 261c14c · 261c14c
1 parent 0c8824d
commit 261c14c
Showing 1 changed file with 6 additions and 6 deletions.
diff --git a/paddlenlp/embeddings/token_embedding.py b/paddlenlp/embeddings/token_embedding.py
@@ -58,8 +58,8 @@ class TokenEmbedding(nn.Embedding):
             The file path of extended vocabulary.
         trainable (object: `bool`, optional, default to True):
             Whether the weight of embedding can be trained.
-        keep_extend_vocab_only (object: `bool`, optional, default to True):
-            Whether keep the extend vocabulary only, only effective if provides extended_vocab_path
+        keep_extended_vocab_only (object: `bool`, optional, default to True):
+            Whether keep the extended vocabulary only, will be effective only if provides extended_vocab_path
     """
 
     def __init__(self,
@@ -68,7 +68,7 @@ def __init__(self,
                  unknown_token_vector=None,
                  extended_vocab_path=None,
                  trainable=True,
-                 keep_extend_vocab_only=False):
+                 keep_extended_vocab_only=False):
         vector_path = osp.join(EMBEDDING_HOME, embedding_name + ".npz")
         if not osp.exists(vector_path):
             # download
@@ -91,7 +91,7 @@ def __init__(self,
         if extended_vocab_path is not None:
             embedding_table = self._extend_vocab(extended_vocab_path, vector_np,
                                                  pad_vector, unk_vector,
-                                                 keep_extend_vocab_only)
+                                                 keep_extended_vocab_only)
             trainable = True
         else:
             embedding_table = self._init_without_extend_vocab(
@@ -142,7 +142,7 @@ def _read_vocab_list_from_file(self, extended_vocab_path):
         return vocab_list
 
     def _extend_vocab(self, extended_vocab_path, vector_np, pad_vector,
-                      unk_vector, keep_extend_vocab_only):
+                      unk_vector, keep_extended_vocab_only):
         """
         Construct index to word list, word to index dict and embedding weight using
         extended vocab.
@@ -186,7 +186,7 @@ def _extend_vocab(self, extended_vocab_path, vector_np, pad_vector,
         embedding_table[
             extend_vocab_intersect_index] = pretrained_embedding_table[
                 pretrained_vocab_intersect_index]
-        if not keep_extend_vocab_only:
+        if not keep_extended_vocab_only:
             for idx in pretrained_vocab_subtract_index:
                 word = pretrained_idx_to_word[idx]
                 self._idx_to_word.append(word)