code: def training_step(self, batch, batch_idx):
      output = self.l1(batch)
      output = torch.nn.functional.l1_loss(
          output, torch.ones(output.size()).to(output.device)
      )
      return {"loss": output}
  
imports: import math
  import random
  import omegaconf
  import pytest
  import pytorch_lightning
  import torch
  import torch.optim
  from pytorch_lightning.utilities import rank_zero_only
  from nemo.core import config, optim
  from nemo.core.optim.lr_scheduler import AVAILABLE_SCHEDULERS
  from nemo.core.optim.optimizers import AVAILABLE_OPTIMIZERS
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling the ExampleModel obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: dict