code: def test_spspdiv(create_func, nnz, shape, nz_dim):
      dev = F.ctx()
      A = create_func(shape, nnz, dev, nz_dim)
  
      perm = torch.randperm(A.nnz, device=dev)
      rperm = torch.argsort(perm)
      B = spmatrix(A.indices()[:, perm], A.val[perm], A.shape)
      C = div(A, B)
      assert not C.has_duplicate()
      assert torch.allclose(C.val, A.val / B.val[rperm], atol=1e-05)
      assert torch.allclose(C.indices(), A.indices(), atol=1e-05)
  
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 6 for calling a global function with example usage: test_spspdiv(create_func, nnz, shape, nz_dim) without return types