def _pack_one_group()

in data/advanced_datasets.py [0:0]

• 10 lines of code
• 3 McCabe index (conditional complexity)

    def _pack_one_group(self, group_indices, batch, max_len):
        ids, lbl, am, ims = [], [], [], []

        for i in group_indices:
            ids.extend(batch[i]["input_ids"])
            lbl.extend(batch[i]["labels"])
            am.extend(batch[i]["attention_mask"])
            ims.extend(batch[i]["images"])

        # safety: assert we never overflow
        if len(ids) > max_len:
            raise ValueError(f"Packed length {len(ids)} > max_len {max_len}")

        return torch.stack(ids), torch.stack(lbl), torch.stack(am), ims