f8a55bfe352901533595dfd1a36e51cfc0092e42,torch_geometric/utils/to_dense_adj.py,,to_dense_adj,#Any#Any#Any#Any#,5

Before Change

        max_num_nodes = num_nodes.max().item()

    size = [batch_size, max_num_nodes, max_num_nodes]
    size = size if edge_attr is None else size + list(edge_attr.size())[1:]
    dtype = torch.float if edge_attr is None else edge_attr.dtype
    adj = torch.zeros(size, dtype=dtype, device=edge_index.device)

    edge_index_0 = batch[edge_index[0]].view(1, -1)

After Change

    flattened_size = batch_size * max_num_nodes * max_num_nodes
    adj = adj.view([flattened_size] + list(adj.size())[3:])
    idx = idx0 * max_num_nodes * max_num_nodes + idx1 * max_num_nodes + idx2
    scatter(edge_attr, idx, dim=0, out=adj, reduce="add")
    adj = adj.view(size)

    return adj

Instances