def create_and_check_model(self, config, input_ids, token_type_ids,
input_mask, sequence_labels, token_labels,
choice_labels):
model = SplinterModel(config=config)
model.to(torch_device)
model.eval()
result = model(input_ids,
attention_mask=input_mask,
token_type_ids=token_type_ids)
result = model(input_ids, token_type_ids=token_type_ids)
result = model(input_ids)
self.parent.assertEqual(
result.last_hidden_state.shape,
(self.batch_size, self.seq_length, self.hidden_size))
def test_model_from_pretrained(self):
for model_name in SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = SplinterModel.from_pretrained(model_name)
self.assertIsNotNone(model)