code: def get_model_optimizer(self, resolution=32):
      set_seed(0)
      model = UNet2DModel(
          sample_size=resolution, in_channels=3, out_channels=3
      )
      optimizer = torch.optim.SGD(model.parameters(), lr=0.0001)
      return model, optimizer
  
file_path: diffusers/tests/others/test_training.py
imports: import unittest
  import torch
  from diffusers import DDIMScheduler, DDPMScheduler, UNet2DModel
  from diffusers.training_utils import set_seed
  from diffusers.utils.testing_utils import slow
label_desc: Use image node_id 1 for calling the TrainingTests obj's underlying member method code with example usage: obj.get_model_optimizer(resolution) and returns: model,  optimizer