code: def test_error_op_scalar(op, v_scalar):
      ctx = F.ctx()
      row = torch.tensor([1, 0, 2]).to(ctx)
      col = torch.tensor([0, 3, 2]).to(ctx)
      val = torch.randn(len(row)).to(ctx)
      A = from_coo(row, col, val, shape=(3, 4))
  
      with pytest.raises(TypeError):
          A + v_scalar
      with pytest.raises(TypeError):
          v_scalar + A
  
      with pytest.raises(TypeError):
          A - v_scalar
      with pytest.raises(TypeError):
          v_scalar - A
  
file_path: dgl/tests/python/pytorch/sparse/test_elementwise_op_sp.py
imports: import sys
  import backend
  import pytest
  import torch
  from dgl.sparse import div, from_coo, mul, power, spmatrix, val_like
  from .utils import rand_coo, rand_csc, rand_csr, rand_diag, sparse_matrix_to_dense
label_desc: Use image node_id 4 for calling a global function with example usage: test_error_op_scalar(op, v_scalar) without return types