5da3439c161c0ae5cb43d9f69e4d398185720be1,python/dgl/dataloading/pytorch/__init__.py,_EdgeDataLoaderIter,__next__,#_EdgeDataLoaderIter#,158

Before Change

    def __next__(self):
        if self.edge_dataloader.collator.negative_sampler is None:
            // input_nodes, pair_graph, [items], blocks
            result = next(self.iter_)
            _restore_subgraph_storage(result[1], self.edge_dataloader.collator.g)
            _restore_blocks_storage(result[-1], self.edge_dataloader.collator.g_sampling)
            return result
        else:

After Change

        _restore_subgraph_storage(result_[1], self.edge_dataloader.collator.g)
        _restore_blocks_storage(result_[-1], self.edge_dataloader.collator.g_sampling)

        result = []
        for data in result_:
            result.append(_to_device(data, self.device))
        return result

class NodeDataLoader:
    PyTorch dataloader for batch-iterating over a set of nodes, generating the list

Instances