class_docstr: Test that the wrapped NumPy functionality integrates well
  with standard NumPy functions.
class_docstr_tok: ["Test","that","the","wrapped","NumPy","functionality","integrates","well","with","standard","NumPy","functions","."]
docstr: Test that binary operators (add, subtract, divide, multiply, matmul)
  correctly work on tensors.
docstr_tok: ["Test","that","binary","operators","(","add",",","subtract",",","divide",",","multiply",",","matmul",")","correctly","work","on","tensors","."]
code: def test_binary_operators(self):
      """Test that binary operators (add, subtract, divide, multiply, matmul)
      correctly work on tensors."""
      x = np.array([[1, 2], [3, 4]])
      y = np.array([[5, 6], [7, 8]])
      res = x + y
      assert isinstance(res, np.tensor)
      assert res.requires_grad
  
      res = x - y
      assert isinstance(res, np.tensor)
      assert res.requires_grad
  
      res = x / y
      assert isinstance(res, np.tensor)
      assert res.requires_grad
  
      res = x * y
      assert isinstance(res, np.tensor)
      assert res.requires_grad
  
      res = x @ y
      assert isinstance(res, np.tensor)
      assert res.requires_grad
  
imports: import numpy
  import pytest
  from autograd.numpy.numpy_boxes import ArrayBox
  import pennylane
  from pennylane import numpy
  from pennylane.numpy.tensor import tensor_to_arraybox
label_desc: Use image node_id 14 for calling the TestNumpyIntegration obj's underlying member method code with example usage: obj.test_binary_operators() without return types