code: def prepare(
      self,
      model: nn.Module,
      trainer_config: ECDTrainerConfig,
      base_learning_rate: float,
  ) -> tuple[nn.Module, Optimizer]:
      return model, create_optimizer(
          model, trainer_config.optimizer, base_learning_rate
      )
  
imports: from __future__ import annotations
  import contextlib
  from abc import ABC, abstractmethod
  from typing import Any, Callable, TYPE_CHECKING
  import torch
  from torch import nn
  from torch.optim import Optimizer
  from ludwig.modules.optimization_modules import create_optimizer
  from ludwig.utils.torch_utils import get_torch_device
label_desc: Use image node_id 1 for calling the LocalStrategy obj's underlying member method code with example usage: obj.prepare(model, trainer_config, base_learning_rate) and returns: model,  create_optimizer