def create_and_check_distilbert_for_question_answering(
     self, config, input_ids, input_mask, sequence_labels, token_labels, choice_labels
 ):
     model = DistilBertForQuestionAnswering(config=config)
     model.to(torch_device)
     model.eval()
     result = model(
         input_ids, attention_mask=input_mask, 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))
Beispiel #2
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 def create_and_check_distilbert_for_question_answering(
         self, config, input_ids, input_mask, sequence_labels,
         token_labels, choice_labels):
     model = DistilBertForQuestionAnswering(config=config)
     model.to(torch_device)
     model.eval()
     result = model(input_ids,
                    attention_mask=input_mask,
                    start_positions=sequence_labels,
                    end_positions=sequence_labels)
     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)