class_docstr: Sets the sparsity level of each parameter group to the final sl
  plus a given exponential function.
  
  .. math::
  
      s_i = s_f + (s_0 - s_f) \cdot \left( 1 - \frac{t - t_0}{n\Delta t} \right)^3
  
  where :math:`s_i` is the sparsity at epoch :math:`t`, :math;`s_f` is the final
  sparsity level, :math:`f(i)` is the function to be applied to the current epoch
  :math:`t`, initial epoch :math:`t_0`, and final epoch :math:`t_f`.
  :math:`\Delta t` is used to control how often the update of the sparsity level
  happens. By default,
  
  Args:
      sparsifier (BaseSparsifier): Wrapped sparsifier.
      init_sl (int, list): Initial level of sparsity
      init_t (int, list): Initial step, when pruning starts
      delta_t (int, list): Pruning frequency
      total_t (int, list): Total number of pruning steps
      initially_zero (bool, list): If True, sets the level of sparsity to 0
          before init_t (:math:`t_0`). Otherwise, the sparsity level before
          init_t (:math:`t_0`) is set to init_sl(:math:`s_0`)
      last_epoch (int): The index of last epoch. Default: -1.
      verbose (bool): If ``True``, prints a message to stdout for
          each update. Default: ``False``.
code: def get_sl(self):
      if not self._get_sl_called_within_step:
          warnings.warn(
              "To get the last sparsity level computed by the scheduler, "
              "please use `get_last_sl()`."
          )
      return [
          self.sparsity_compute_fn(
              s_0=initial_sparsity,
              s_f=final_sparsity,
              t=self.last_epoch,
              t_0=initial_epoch,
              dt=delta_epoch,
              n=interval_epochs,
              initially_zero=initially_zero,
          )
          for initial_sparsity, final_sparsity, initial_epoch, delta_epoch, interval_epochs, initially_zero in zip(
              self.init_sl,
              self.base_sl,
              self.init_t,
              self.delta_t,
              self.total_t,
              self.initially_zero,
          )
      ]
  
file_path: pytorch/torch/ao/pruning/scheduler/cubic_scheduler.py
imports: import warnings
  from .base_scheduler import BaseScheduler
label_desc: Use image node_id 3 for calling the CubicSL obj's underlying member method code with example usage: obj.get_sl() and returns: unknown