code: def expected_jvp(params, tangent):
      """Expected result of the JVP of the below circuit ansatz."""
      j = qml.jacobian(expected_probs)(params)
      if qml.math.ndim(params) > 1:
          # If there is broadcasting, take the diagonal over
          # the two axes corresponding to broadcasting
          j = np.stack([j[i, :, i, :] for i in range(len(j))])
  
      return np.tensordot(j, tangent, axes=1)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane.gradients import param_shift
label_desc: Use image node_id 2 for calling a global function with example usage: expected_jvp(params, tangent) and returns: np