def __call__()

in src/data.py [0:0]

• 23 lines of code
• 7 McCabe index (conditional complexity)

    def __call__(self, batch):
        index = torch.tensor([ex['index'] for ex in batch])

        question = [ex['question'] for ex in batch]
        question = self.tokenizer.batch_encode_plus(
            question,
            pad_to_max_length=True,
            return_tensors="pt",
            max_length=self.question_maxlength,
            truncation=True
        )
        question_ids = question['input_ids']
        question_mask = question['attention_mask'].bool()

        if batch[0]['scores'] is None or batch[0]['passages'] is None:
            return index, question_ids, question_mask, None, None, None

        scores = [ex['scores'] for ex in batch]
        scores = torch.stack(scores, dim=0)

        passages = [ex['passages'] for ex in batch]
        passage_ids, passage_masks = encode_passages(
            passages,
            self.tokenizer,
            self.passage_maxlength
        )

        return (index, question_ids, question_mask, passage_ids, passage_masks, scores)