code: def configure_optimizers(self):
      opt_a = torch.optim.SGD(self.layer.parameters(), lr=0.001)
      opt_b = torch.optim.SGD(self.layer.parameters(), lr=0.001)
      return opt_a, opt_b
  
file_path: pytorch-lightning/tests/tests_pytorch/trainer/optimization/test_multiple_optimizers.py
imports: import lightning.pytorch
  import pytest
  import torch
  from lightning.pytorch.demos.boring_classes import BoringModel
label_desc: Use image node_id 1 for calling the MultiOptModel obj's underlying member method code with example usage: obj.configure_optimizers() and returns: opt_a,  opt_b