code: def set_trainable(self, trainable):
      for param in self.parameters():
          param.requires_grad = bool(trainable)
  
imports: import dataclasses
  from abc import abstractmethod
  from typing import Protocol, Tuple, List, Union, Mapping, Callable
  import numpy
  import torch.jit
  from torch import nn, Tensor
  from pytorch_toolbelt.utils import pytorch_toolbelt_deprecated
label_desc: Use image node_id 3 for calling the AbstractDecoder obj's underlying member method code with example usage: obj.set_trainable(trainable) without return types