code: def _default_optimizer(self, base_lr):
      params = [
          param
          for param in self.model.parameters()
          if param.requires_grad
      ]
      return params, AdamW(params, lr=base_lr, eps=1e-8)
  
imports: import unittest
  import pytest
  import torch
  import numpy
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
label_desc: Use image node_id 2 for calling the PytorchClassifierImplementation obj's underlying member method code with example usage: obj._default_optimizer(base_lr) and returns: params,  AdamW