code: def set_trainable_params(self):
      for layer in self.layers:
          # Set `requires_grad` to `False` for the entire layer.
          layer.requires_grad_(False)
          #
          for p in self.get_trainable_params().values():
              p.requires_grad_(True)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/neox/utils/finetune.py
imports: from typing import List, Dict
  import torch
  from torch import nn
  from labml_nn.neox.model import TransformerLayer, NeoXModule
label_desc: Use image node_id 4 for calling the FineTuner obj's underlying member method code with example usage: obj.set_trainable_params() without return types