code: def __init__(self, learning_rate1=0.01, learning_rate2=0.05) -> None:
      super().__init__()
  
      self.save_hyperparameters()
  
imports: import os
  import pytest
  from unittest import TestCase
  from test.pytorch.utils._train_torch_lightning import create_data_loader, data_transform
  from test.pytorch.utils._train_torch_lightning import create_test_data_loader
  from bigdl.nano.pytorch.vision.models import vision
  from bigdl.nano.pytorch import Trainer
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_1_10, TORCH_VERSION_LESS_2_0
  import pytorch_lightning
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new ResNetWith2Optimizers object from inherited base classes: ResNetBase with example: obj = ResNetWith2Optimizers(learning_rate1, learning_rate2)