def create_and_check_for_question_answering( self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels ): config.return_dict = True model = TFLongformerForQuestionAnswering(config=config) result = model( input_ids, attention_mask=input_mask, token_type_ids=token_type_ids, start_positions=sequence_labels, end_positions=sequence_labels, ) self.parent.assertListEqual(shape_list(result.start_logits), [self.batch_size, self.seq_length]) self.parent.assertListEqual(shape_list(result.end_logits), [self.batch_size, self.seq_length])
def create_and_check_longformer_for_question_answering( self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels ): model = TFLongformerForQuestionAnswering(config=config) 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(shape_list(result["start_logits"]), [self.batch_size, self.seq_length]) self.parent.assertListEqual(shape_list(result["end_logits"]), [self.batch_size, self.seq_length])