code: def test_riemannian_gradient_step(circuit, hamiltonian):
      """Test that we can take subsequent steps with the optimizer."""
      nqubits = max(max(ps.wires) for ps in hamiltonian.ops) + 1
  
      dev = qml.device("default.qubit", wires=nqubits)
  
      @qml.qnode(dev)
      def test_circuit():
          circuit()
          return qml.expval(hamiltonian)
  
      opt = RiemannianGradientOptimizer(circuit=test_circuit)
      opt.step()
      opt.step()
  
file_path: pennylane/tests/optimize/test_riemannian_gradient_optimizer.py
imports: import pytest
  from scipy.sparse.linalg import expm
  import numpy
  import pennylane
  from pennylane.optimize import RiemannianGradientOptimizer
label_desc: Use image node_id 7 for calling a global function with example usage: test_riemannian_gradient_step(circuit, hamiltonian) and returns: qml