[style] consistent nn. and nn.functional: part 3 tests (#12155)

* consistent nn. and nn.functional: p3 templates

* restore

tests/test_modeling_common.py

@@ -44,6 +44,7 @@ from transformers.testing_utils import (
 if is_torch_available():
     import numpy as np
     import torch
+    from torch import nn
 
     from transformers import (
         BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
@@ -1150,10 +1151,10 @@ class ModelTesterMixin:
 
         for model_class in self.all_model_classes:
             model = model_class(config)
-            self.assertIsInstance(model.get_input_embeddings(), (torch.nn.Embedding, AdaptiveEmbedding))
-            model.set_input_embeddings(torch.nn.Embedding(10, 10))
+            self.assertIsInstance(model.get_input_embeddings(), (nn.Embedding, AdaptiveEmbedding))
+            model.set_input_embeddings(nn.Embedding(10, 10))
             x = model.get_output_embeddings()
-            self.assertTrue(x is None or isinstance(x, torch.nn.Linear))
+            self.assertTrue(x is None or isinstance(x, nn.Linear))
 
     def test_correct_missing_keys(self):
         if not self.test_missing_keys:
@@ -1337,7 +1338,7 @@ class ModelTesterMixin:
             model.eval()
 
             # Wrap model in nn.DataParallel
-            model = torch.nn.DataParallel(model)
+            model = nn.DataParallel(model)
             with torch.no_grad():
                 _ = model(**self._prepare_for_class(inputs_dict, model_class))