Add require_torch to tokenizer tests

src/transformers/models/luke/modeling_luke.py

@@ -689,7 +689,7 @@ class LukePreTrainedModel(PreTrainedModel):
     base_model_prefix = "luke"
 
     def _init_weights(self, module: nn.Module):
-        """ Initialize the weights """
+        """Initialize the weights"""
         if isinstance(module, nn.Linear):
             module.weight.data.normal_(mean=0.0, std=self.config.initializer_range)
             if module.bias is not None:
@@ -1074,7 +1074,7 @@ def forward(
             >>> outputs = model(**inputs)
             >>> logits = outputs.logits
             >>> predicted_class_idx = logits.argmax(-1).item()
-            >>> print("Predicted class:", model.config.id2label[predicted_class_idx]) 
+            >>> print("Predicted class:", model.config.id2label[predicted_class_idx])
         """
         return_dict = return_dict if return_dict is not None else self.config.use_return_dict
 

tests/test_tokenization_luke.py

@@ -17,7 +17,7 @@
 import unittest
 
 from transformers import AddedToken, LukeTokenizer
-from transformers.testing_utils import slow, require_torch
+from transformers.testing_utils import require_torch, slow
 
 from .test_tokenization_common import TokenizerTesterMixin