code: def generate_shifted_tapes(
      tape, index, shifts, multipliers=None, broadcast=False
  ):
      r"""Generate a list of tapes or a single broadcasted tape, where one marked
      trainable parameter has been shifted by the provided shift values.
  
      Args:
          tape (.QuantumTape): input quantum tape
          index (int): index of the trainable parameter to shift
          shifts (Sequence[float or int]): sequence of shift values.
              The length determines how many parameter-shifted tapes are created.
          multipliers (Sequence[float or int]): sequence of multiplier values.
              The length should match the one of ``shifts``. Each multiplier scales the
              corresponding gate parameter before the shift is applied. If not provided, the
              parameters will not be scaled.
          broadcast (bool): Whether or not to use broadcasting to create a single tape
              with the shifted parameters.
  
      Returns:
          list[QuantumTape]: List of quantum tapes. In each tape the parameter indicated
              by ``index`` has been shifted by the values in ``shifts``. The number of tapes
              matches the length of ``shifts`` and ``multipliers`` (if provided).
              If ``broadcast=True`` was used, the list contains a single broadcasted tape
              with all shifts distributed over the broadcasting dimension. In this case,
              the ``batch_size`` of the returned tape matches the length of ``shifts``.
      """
  
      if multipliers is None:
          multipliers = np.ones_like(shifts)
  
      if broadcast:
          return (
              _copy_and_shift_params(
                  tape, [index], [shifts], [multipliers]
              ),
          )
  
      return tuple(
          _copy_and_shift_params(tape, [index], [shift], [multiplier])
          for shift, multiplier in zip(shifts, multipliers)
      )
  
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 11 for calling a global function with example usage: generate_shifted_tapes(tape, index, shifts, multipliers, broadcast) and returns: tuple, _copy_and_shift_params