Debug LukeForMaskedLM (#17499)

* add a test for a word only input

* make LukeForMaskedLM work without entity inputs

* update test

* add LukeForMaskedLM to MODEL_FOR_MASKED_LM_MAPPING_NAMES

* restore pyproject.toml

* empty line at the end of pyproject.toml

src/transformers/models/auto/modeling_auto.py

@@ -377,6 +377,7 @@ MODEL_FOR_MASKED_LM_MAPPING_NAMES = OrderedDict(
         ("ibert", "IBertForMaskedLM"),
         ("layoutlm", "LayoutLMForMaskedLM"),
         ("longformer", "LongformerForMaskedLM"),
+        ("luke", "LukeForMaskedLM"),
         ("mbart", "MBartForConditionalGeneration"),
         ("megatron-bert", "MegatronBertForMaskedLM"),
         ("mobilebert", "MobileBertForMaskedLM"),

src/transformers/models/luke/modeling_luke.py

@@ -1229,6 +1229,8 @@ class LukeForMaskedLM(LukePreTrainedModel):
                 loss = mlm_loss
 
         mep_loss = None
+        entity_logits = None
+        if outputs.entity_last_hidden_state is not None:
             entity_logits = self.entity_predictions(outputs.entity_last_hidden_state)
             if entity_labels is not None:
                 mep_loss = self.loss_fn(entity_logits.view(-1, self.config.entity_vocab_size), entity_labels.view(-1))

tests/models/luke/test_modeling_luke.py

@@ -270,9 +270,12 @@ class LukeModelTester:
             entity_labels=entity_labels,
         )
         self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, self.vocab_size))
+        if entity_ids is not None:
             self.parent.assertEqual(
                 result.entity_logits.shape, (self.batch_size, self.entity_length, self.entity_vocab_size)
             )
+        else:
+            self.parent.assertIsNone(result.entity_logits)
 
     def create_and_check_for_entity_classification(
         self,
@@ -488,6 +491,11 @@ class LukeModelTest(ModelTesterMixin, unittest.TestCase):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_masked_lm(*config_and_inputs)
 
+    def test_for_masked_lm_with_word_only(self):
+        config_and_inputs = self.model_tester.prepare_config_and_inputs()
+        config_and_inputs = (*config_and_inputs[:4], *((None,) * len(config_and_inputs[4:])))
+        self.model_tester.create_and_check_for_masked_lm(*config_and_inputs)
+
     def test_for_entity_classification(self):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_entity_classification(*config_and_inputs)