class_docstr: Test that the gradients for qutrit parametrized operations are correct
docstr: Test that differentiation of parametrized operations with broadcasting works.
code: def test_differentiability_broadcasted(
      self, op, obs, grad_fn, diff_method, tol
  ):
      """Test that differentiation of parametrized operations with broadcasting works."""
      phi = npp.linspace(0, 2 * np.pi, 7, requires_grad=True)
  
      dev = qml.device("default.qutrit", wires=1)
  
      @qml.qnode(dev, diff_method=diff_method)
      def circuit(phi):
          if op is qml.TRZ:
              # Without Hadamard the derivative is always 0
              qml.THadamard(wires=0, subspace=(0, 1))
          op(phi, wires=0)
          return qml.expval(obs)
  
      jac = qml.jacobian(circuit)(phi)
  
      assert np.allclose(jac, np.diag(grad_fn(phi)), atol=tol, rtol=0)
  
imports: import copy
  from functools import reduce
  import pytest
  import numpy
  from gate_data import TSHIFT, TCLOCK
  from pennylane import numpy
  import pennylane
  from pennylane.wires import Wires
label_desc: Use image node_id 2 for calling the TestGrad obj's underlying member method code with example usage: obj.test_differentiability_broadcasted(op, obs, grad_fn, diff_method, tol) and returns: qml