class_docstr: An abstract base class for implementing custom node selections as
  described in the `"Understanding Pooling in Graph Neural Networks"
  <https://arxiv.org/abs/1905.05178>`_ paper, which maps the nodes of an
  input graph to supernodes in the coarsened graph.
  
  Specifically, :class:`Select` returns a :class:`SelectOutput` output, which
  holds a (sparse) mapping :math:`\mathbf{C} \in {[0, 1]}^{N \times C}` that
  assigns selected nodes to one or more of :math:`C` super nodes.
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code: def forward(self, *args, **kwargs) -> SelectOutput:
      raise NotImplementedError
  
file_path: pytorch_geometric/torch_geometric/nn/pool/select/base.py
imports: from dataclasses import dataclass
  from typing import Optional
  import torch
  from torch import Tensor
  import torch_geometric.typing
label_desc: Use image node_id 2 for calling the Select obj's underlying member method code with example usage: obj.forward() without return types