code: def test_equal():
      row = torch.tensor([0, 0, 0, 1, 1])
      col = torch.tensor([0, 1, 2, 0, 2])
      value = torch.arange(1, 6)
      matA = SparseTensor(row=row, col=col, value=value)
      matB = SparseTensor(row=row, col=col, value=value)
      col = torch.tensor([0, 1, 2, 0, 1])
      matC = SparseTensor(row=row, col=col, value=value)
  
      assert id(matA) != id(matB)
      assert matA == matB
  
      assert id(matA) != id(matC)
      assert matA != matC
  
imports: from itertools import product
  import pytest
  import torch
  from torch_sparse import SparseTensor
  from torch_sparse.testing import devices, grad_dtypes
label_desc: Use image node_id 3 for calling a global function with example usage: test_equal() without return types