示例#1
0
 def create_and_check_xxx_for_question_answering(self, config, input_ids,
                                                 token_type_ids, input_mask,
                                                 sequence_labels,
                                                 token_labels,
                                                 choice_labels):
     model = XxxForQuestionAnswering(config=config)
     model.to(torch_device)
     model.eval()
     loss, start_logits, end_logits = model(
         input_ids,
         attention_mask=input_mask,
         token_type_ids=token_type_ids,
         start_positions=sequence_labels,
         end_positions=sequence_labels,
     )
     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)
示例#2
0
 def create_and_check_for_question_answering(
     self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels
 ):
     model = XxxForQuestionAnswering(config=config)
     model.to(torch_device)
     model.eval()
     result = model(
         input_ids,
         attention_mask=input_mask,
         token_type_ids=token_type_ids,
         start_positions=sequence_labels,
         end_positions=sequence_labels,
     )
     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))