Method has_edges_between

python/dgl/heterograph.py:2936–3028

Return whether the graph contains the given edges. Parameters ---------- u : node IDs The source node IDs of the edges. The allowed formats are: * ``int``: A single node. * Int Tensor: Each element is a node ID. The tensor must have the s

(self, u, v, etype=None)

            return F.astype(ret, F.bool)

    def has_edges_between(self, u, v, etype=None):
        """Return whether the graph contains the given edges.

        Parameters
        ----------
        u : node IDs
            The source node IDs of the edges. The allowed formats are:

            * ``int``: A single node.
            * Int Tensor: Each element is a node ID. The tensor must have the same device type
              and ID data type as the graph's.
            * iterable[int]: Each element is a node ID.

        v : node IDs
            The destination node IDs of the edges. The allowed formats are:

            * ``int``: A single node.
            * Int Tensor: Each element is a node ID. The tensor must have the same device type
              and ID data type as the graph's.
            * iterable[int]: Each element is a node ID.

        etype : str or (str, str, str), optional
            The type names of the edges. The allowed type name formats are:

            * ``(str, str, str)`` for source node type, edge type and destination node type.
            * or one ``str`` edge type name if the name can uniquely identify a
              triplet format in the graph.

            Can be omitted if the graph has only one type of edges.


        Returns
        -------
        bool or bool Tensor
            A tensor of bool flags where each element is True if the node is in the graph.
            If the input is a single node, return one bool value.

        Examples
        --------

        The following example uses PyTorch backend.

        >>> import dgl
        >>> import torch

        Create a homogeneous graph.

        >>> g = dgl.graph((torch.tensor([0, 0, 1, 1]), torch.tensor([1, 0, 2, 3])))

        Query for the edges.

        >>> g.has_edges_between(1, 2)
        True
        >>> g.has_edges_between(torch.tensor([1, 2]), torch.tensor([2, 3]))
        tensor([ True, False])

        If the graph has multiple edge types, one need to specify the edge type.