LongformerForSequenceClassification (#4580)

* LongformerForSequenceClassification

* better naming x=>hidden_states, fix typo in doc

* Update src/transformers/modeling_longformer.py

* Update src/transformers/modeling_longformer.py

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
This commit is contained in:
Suraj Patil
2020-05-28 02:00:00 +05:30
committed by GitHub
parent 4402879ee4
commit ec4cdfdd05
4 changed files with 141 additions and 1 deletions

View File

@@ -29,6 +29,7 @@ if is_torch_available():
LongformerConfig,
LongformerModel,
LongformerForMaskedLM,
LongformerForSequenceClassification,
LongformerForQuestionAnswering,
)
@@ -194,6 +195,23 @@ class LongformerModelTester(object):
self.parent.assertListEqual(list(result["end_logits"].size()), [self.batch_size, self.seq_length])
self.check_loss_output(result)
def create_and_check_longformer_for_sequence_classification(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
config.num_labels = self.num_labels
model = LongformerForSequenceClassification(config)
model.to(torch_device)
model.eval()
loss, logits = model(
input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, labels=sequence_labels
)
result = {
"loss": loss,
"logits": logits,
}
self.parent.assertListEqual(list(result["logits"].size()), [self.batch_size, self.num_labels])
self.check_loss_output(result)
def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs()
(
@@ -256,6 +274,10 @@ class LongformerModelTest(ModelTesterMixin, unittest.TestCase):
config_and_inputs = self.model_tester.prepare_config_and_inputs_for_question_answering()
self.model_tester.create_and_check_longformer_for_question_answering(*config_and_inputs)
def test_for_sequence_classification(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_longformer_for_sequence_classification(*config_and_inputs)
class LongformerModelIntegrationTest(unittest.TestCase):
@slow