Fix for model without pad

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

auto_transformers.py

@@ -103,9 +103,8 @@ class AutoTransformers(NNOperator):
     def __call__(self, txt: str, return_sentence_emb: bool = False) -> numpy.ndarray:
         try:
             inputs = self.tokenizer(txt, padding=True, truncation=True, return_tensors="pt").to(self.device)
-        except Exception as e:
-            log.error(f'Invalid input for the tokenizer: {self.model_name}')
-            raise e
+        except Exception:
+            inputs = self.tokenizer(dummy_input, truncation=True, return_tensors='pt').to(self.device)
         try:
             outs = self.model(**inputs)
         except Exception as e:
@@ -144,7 +143,10 @@ class AutoTransformers(NNOperator):
                 raise AttributeError('Unsupported model_type.')
 
         dummy_input = '[CLS]'
-        inputs = self.tokenizer(dummy_input, padding=True, truncation=True, return_tensors='pt')  # a dictionary
+        try:
+            inputs = self.tokenizer(dummy_input, padding=True, truncation=True, return_tensors='pt')  # a dictionary
+        except Exception:
+            inputs = self.tokenizer(dummy_input, truncation=True, return_tensors='pt')
         if model_type == 'pytorch':
             torch.save(self._model, output_file)
         elif model_type == 'torchscript':