from typing import Optional
import torch
from torch import Tensor
from torch_geometric.utils.num_nodes import maybe_num_nodes
[docs]def degree(index: Tensor, num_nodes: Optional[int] = None,
dtype: Optional[torch.dtype] = None) -> Tensor:
r"""Computes the (unweighted) degree of a given one-dimensional index
tensor.
Args:
index (LongTensor): Index tensor.
num_nodes (int, optional): The number of nodes, *i.e.*
:obj:`max_val + 1` of :attr:`index`. (default: :obj:`None`)
dtype (:obj:`torch.dtype`, optional): The desired data type of the
returned tensor.
:rtype: :class:`Tensor`
Example:
>>> row = torch.tensor([0, 1, 0, 2, 0])
>>> degree(row, dtype=torch.long)
tensor([3, 1, 1])
"""
N = maybe_num_nodes(index, num_nodes)
out = torch.zeros((N, ), dtype=dtype, device=index.device)
one = torch.ones((index.size(0), ), dtype=out.dtype, device=out.device)
return out.scatter_add_(0, index, one)