fix(transformers): force padding to max length in all versions

Author: JoanFM

jina/executors/encoders/nlp/transformer.py

@@ -81,11 +81,15 @@ def encode(self, data: 'np.ndarray', *args, **kwargs) -> 'np.ndarray':
             ids_info = self.tokenizer.batch_encode_plus(data,
                                                         max_length=self.max_length,
                                                         truncation=self.truncation_strategy,
-                                                        padding=True)
+                                                        pad_to_max_length=True,
+                                                        padding='max_length')
         except ValueError:
             self.tokenizer.add_special_tokens({'pad_token': '[PAD]'})
             self.model.resize_token_embeddings(len(self.tokenizer))
-            ids_info = self.tokenizer.batch_encode_plus(data, max_length=self.max_length, padding=True)
+            ids_info = self.tokenizer.batch_encode_plus(data,
+                                                        max_length=self.max_length,
+                                                        pad_to_max_length=True,
+                                                        padding='max_length')
         token_ids_batch = self.array2tensor(ids_info['input_ids'])
         mask_ids_batch = self.array2tensor(ids_info['attention_mask'])
         with self.session():