Remove unused variables in tests.

tests/test_modeling_common.py

@@ -284,7 +284,6 @@ class ModelTesterMixin:
             multihead_outputs = head_mask.grad
 
             attentions = outputs[-1]
-            hidden_states = outputs[-2]
 
             # Remove Nan
             for t in attentions:
@@ -590,7 +589,7 @@ class ModelTesterMixin:
                 inputs_dict["decoder_inputs_embeds"] = wte(decoder_input_ids)
 
             with torch.no_grad():
-                outputs = model(**inputs_dict)
+                model(**inputs_dict)
 
 
 class ConfigTester(object):

tests/test_modeling_tf_common.py

@@ -332,7 +332,7 @@ class TFModelTesterMixin:
                 inputs_dict["encoder_inputs_embeds"] = self._get_embeds(wte, encoder_input_ids)
                 inputs_dict["decoder_inputs_embeds"] = self._get_embeds(wte, decoder_input_ids)
 
-            outputs = model(inputs_dict)
+            model(inputs_dict)
 
 
 def ids_tensor(shape, vocab_size, rng=None, name=None, dtype=None):

tests/test_modeling_tf_xlm.py

@@ -224,7 +224,6 @@ class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
 
             inputs = {"input_ids": input_ids, "lengths": input_lengths}
 
-            outputs = model(inputs)
             start_logits, end_logits = model(inputs)
 
             result = {

tests/test_tokenization_common.py

@@ -159,7 +159,6 @@ class TokenizerTesterMixin:
         self.assertEqual(all_size_2, all_size + len(new_toks))
 
         tokens = tokenizer.encode("aaaaa bbbbbb low cccccccccdddddddd l", add_special_tokens=False)
-        out_string = tokenizer.decode(tokens)
 
         self.assertGreaterEqual(len(tokens), 4)
         self.assertGreater(tokens[0], tokenizer.vocab_size - 1)
@@ -178,7 +177,6 @@ class TokenizerTesterMixin:
         tokens = tokenizer.encode(
             ">>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l", add_special_tokens=False
         )
-        out_string = tokenizer.decode(tokens)
 
         self.assertGreaterEqual(len(tokens), 6)
         self.assertGreater(tokens[0], tokenizer.vocab_size - 1)