code: def spspmm(
      src: SparseTensor, other: SparseTensor, reduce: str = "sum"
  ) -> SparseTensor:
      if reduce == "sum" or reduce == "add":
          return spspmm_sum(src, other)
      elif reduce == "mean" or reduce == "min" or reduce == "max":
          raise NotImplementedError
      else:
          raise ValueError
  
file_path: pytorch_sparse/torch_sparse/matmul.py
imports: from typing import Optional, Tuple
  import torch
  from torch import Tensor
  from torch_sparse.tensor import SparseTensor
label_desc: Use image node_id 9 for calling a global function with example usage: spspmm(src, other, reduce) and returns: spspmm_sum