def create_and_check_dpr_reader(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = DPRReader(config=config)
model.to(torch_device)
model.eval()
result = model(input_ids, attention_mask=input_mask,)
self.parent.assertListEqual(list(result["start_logits"].size()), [self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].size()), [self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["relevance_logits"].size()), [self.batch_size])
def create_and_check_reader(
self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
):
model = DPRReader(config=config)
model.to(torch_device)
model.eval()
result = model(
input_ids,
attention_mask=input_mask,
)
self.parent.assertEqual(result.start_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.relevance_logits.shape, (self.batch_size,))
