code: def _iterate_shift_rule(rule, order, period=None):
      r"""Helper method to repeat a shift rule multiple times along the same
      parameter axis for higher-order derivatives."""
      if len(rule[0]) == 3:
          return _iterate_shift_rule_with_multipliers(
              rule, order, period
          )
  
      # TODO: optimization: Without multipliers, the order of shifts does not matter,
      # so that we can only iterate over the symmetric part of the combined_rules tensor.
      # This requires the corresponding multinomial prefactors to be included in the coeffs.
      combined_rules = np.array(
          list(itertools.product(rule, repeat=order))
      )
      # multiply the coefficients of each rule
      coeffs = np.prod(combined_rules[..., 0], axis=1)
      # sum the shifts of each rule
      shifts = np.sum(combined_rules[..., 1], axis=1)
      if period is not None:
          # if a period is provided, make sure the shift value is within [-period/2, period/2)
          shifts = np.mod(shifts + 0.5 * period, period) - 0.5 * period
      return qml.math.stack([coeffs, shifts]).T
  
imports: import functools
  import itertools
  import numbers
  import warnings
  import numpy
  import pennylane
  from pennylane.measurements import MeasurementProcess
  from pennylane.ops.functions import bind_new_parameters
  from pennylane.tape import QuantumScript
label_desc: Use image node_id 6 for calling a global function with example usage: _iterate_shift_rule(rule, order, period) and returns: qml, _iterate_shift_rule_with_multipliers