code: def all_close_sparse(A, row, col, val, shape):
      rowA, colA = A.coo()
      valA = A.val
      assert torch.allclose(rowA, row)
      assert torch.allclose(colA, col)
      assert torch.allclose(valA, val)
      assert A.shape == shape
  
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 1 for calling a global function with example usage: all_close_sparse(A, row, col, val, shape) without return types