62a05d5e2611f6ec8fda2c7d7c5b57cf8b64402b,torch_geometric/nn/functional/pool/pool.py,,max_pool,#Any#Any#Any#Any#,5

Before Change

    input = scatter_max(cluster, input)
    position = scatter_mean(cluster, position)

    index = cluster[index.view(-1)].view(2, -1)  // Replace edge indices with cluster indices.
    mask = index[0, :] != index[1, :]  // Remove self-loops.
    index = coalesce(index)  // Remove duplicates.

    return input, index, position

After Change

    return index, position

def max_pool(input, index, position, cluster):
    _cluster = cluster.unsqueeze(1).expand(-1, input.size(1))
    input = scatter_add(_cluster, input, dim=0)
    return (input,) + _pool(index, position, cluster)


def average_pool(input, index, position, cluster):

Instances