def create_and_check_xlm_simple_qa( self, config, input_ids, token_type_ids, input_lengths, sequence_labels, token_labels, is_impossible_labels, input_mask, ): model = XLMForQuestionAnsweringSimple(config) model.to(torch_device) model.eval() outputs = model(input_ids) outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels) loss, start_logits, end_logits = outputs result = { "loss": loss, "start_logits": start_logits, "end_logits": end_logits, } 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.check_loss_output(result)
def create_and_check_xlm_simple_qa( self, config, input_ids, token_type_ids, input_lengths, sequence_labels, token_labels, is_impossible_labels, choice_labels, input_mask, ): model = XLMForQuestionAnsweringSimple(config) model.to(torch_device) model.eval() outputs = model(input_ids) outputs = model(input_ids, start_positions=sequence_labels, end_positions=sequence_labels) result = outputs 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))