docstr: Trigger the resample for each :meth:`supernet_modules`.
  Sometimes (e.g., in differentiable cases), it does nothing.
  
  Returns
  -------
  dict
      Sampled architecture.
code: def resample(self) -> Sample:
      """Trigger the resample for each :meth:`supernet_modules`.
      Sometimes (e.g., in differentiable cases), it does nothing.
  
      Returns
      -------
      dict
          Sampled architecture.
      """
      result = {}
      for module in self.supernet_modules():
          result.update(module.resample(memo=result))
      return result
  
imports: from __future__ import annotations
  import warnings
  from typing import Any, Iterable, List, cast, TYPE_CHECKING
  import torch.optim
  import torch.nn
  from torch.optim import Optimizer
  import nni.nas.nn.pytorch
  from nni.nas.evaluator.pytorch import LightningModule, Trainer
  from nni.mutable import Sample
  from .supermodule.base import BaseSuperNetModule
label_desc: Use image node_id 6 for calling the BaseOneShotLightningModule obj's underlying member method code with example usage: obj.resample() and returns: result