graphinvent/gnn/aggregation_mpnn.py
def aggregate_message(self, nodes : torch.Tensor, node_neighbours : torch.Tensor,
                          edges : torch.Tensor, mask : torch.Tensor) -> None:
        """
        Message aggregation function, to be implemented in all `AggregationMPNN` subclasses.

        Args:
        ----
            nodes (torch.Tensor)           : Batch of node feature vectors.
            node_neighbours (torch.Tensor) : Batch of node feature vectors for neighbors.
            edges (torch.Tensor)           : Batch of edge feature vectors.
            mask (torch.Tensor)            : Mask for non-existing neighbors, where
                                             elements are 1 if corresponding element
                                             exists and 0 otherwise.

        Shapes:
        ------
            nodes           : (total N nodes in batch, N node features)
            node_neighbours : (total N nodes in batch, max node degree, N node features)
            edges           : (total N nodes in batch, max node degree, N edge features)
            mask            : (total N nodes in batch, max node degree)
        """
        raise NotImplementedError

        Message aggregation function, to be implemented in all `AggregationMPNN` subclasses.

        Args:
        ----
            nodes (torch.Tensor)           : Batch of node feature vectors.
            node_neighbours (torch.Tensor) : Batch of node feature vectors for neighbors.
            edges (torch.Tensor)           : Batch of edge feature vectors.
            mask (torch.Tensor)            : Mask for non-existing neighbors, where
                                             elements are 1 if corresponding element
                                             exists and 0 otherwise.

        Shapes:
        ------
            nodes           : (total N nodes in batch, N node features)
            node_neighbours : (total N nodes in batch, max node degree, N node features)
            edges           : (total N nodes in batch, max node degree, N edge features)
            mask            : (total N nodes in batch, max node degree)
        
Message aggregation function, to be implemented in all `AggregationMPNN` subclasses.
Message aggregation function to be implemented in all ` AggregationMPNN ` subclasses .
def aggregate_message(self, nodes : torch.Tensor, node_neighbours : torch.Tensor,
                          edges : torch.Tensor, mask : torch.Tensor) -> None:
        raise NotImplementedError
def aggregate_message ( self , nodes : torch . Tensor , node_neighbours : torch . Tensor , edges : torch . Tensor , mask : torch . Tensor ) -> None : raise NotImplementedError
Message aggregation function, to be implemented in all `AggregationMPNN` subclasses.
Message aggregation function to be implemented in all ` AggregationMPNN ` subclasses .
"""
        Message aggregation function, to be implemented in all `AggregationMPNN` subclasses.

        Args:
        ----
            nodes (torch.Tensor)           : Batch of node feature vectors.
            node_neighbours (torch.Tensor) : Batch of node feature vectors for neighbors.
            edges (torch.Tensor)           : Batch of edge feature vectors.
            mask (torch.Tensor)            : Mask for non-existing neighbors, where
                                             elements are 1 if corresponding element
                                             exists and 0 otherwise.

        Shapes:
        ------
            nodes           : (total N nodes in batch, N node features)
            node_neighbours : (total N nodes in batch, max node degree, N node features)
            edges           : (total N nodes in batch, max node degree, N edge features)
            mask            : (total N nodes in batch, max node degree)
        """
self
nodes
torch.Tensor
Batch of node feature vectors.
Batch of node feature vectors .
node_neighbours
torch.Tensor
Batch of node feature vectors for neighbors.
Batch of node feature vectors for neighbors .
edges
torch.Tensor
Batch of edge feature vectors.
Batch of edge feature vectors .
mask
torch.Tensor
Mask for non-existing neighbors, where
elements are 1 if corresponding element
exists and 0 otherwise.
Mask for non - existing neighbors where elements are 1 if corresponding element exists and 0 otherwise .