Method in_degrees

python/dgl/heterograph.py:3603–3677

Return the in-degree(s) of the given nodes. It computes the in-degree(s) w.r.t. to the edges of the given edge type. Parameters ---------- v : node IDs The node IDs. The allowed formats are: * ``int``: A single node. * Int Tensor

(self, v=ALL, etype=None)

            )

    def in_degrees(self, v=ALL, etype=None):
        """Return the in-degree(s) of the given nodes.

        It computes the in-degree(s) w.r.t. to the edges of the given edge type.

        Parameters
        ----------
        v : node IDs
            The node IDs. 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.

            If not given, return the in-degrees of all the nodes.
        etype : str or (str, str, str), optional
            The type name 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
        -------
        int or Tensor
            The in-degree(s) of the node(s) in a Tensor. The i-th element is the in-degree
            of the i-th input node. If :attr:`v` is an ``int``, return an ``int`` too.

        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, 1, 2, 3])))

        Query for all nodes.

        >>> g.in_degrees()
        tensor([0, 2, 1, 1])

        Query for nodes 1 and 2.

        >>> g.in_degrees(torch.tensor([1, 2]))
        tensor([2, 1])

        For a graph of multiple edge types, it is required to specify the edge type in query.

        >>> hg = dgl.heterograph({
        ...     ('user', 'follows', 'user'): (torch.tensor([0, 1]), torch.tensor([1, 2])),
        ...     ('user', 'plays', 'game'): (torch.tensor([3, 4]), torch.tensor([5, 6]))
        ... })