code: def __init__(self, batch_size, dataset_len, drop_last, max_steps):
      super().__init__()
      self.l1 = torch.nn.modules.Linear(in_features=2, out_features=1)
      self.batch_size = batch_size
      self.dataset_len = dataset_len
      self.drop_last = drop_last
      self.max_steps = max_steps
  
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 1 to create a new ExampleModel object from inherited base classes: pl with example: obj = ExampleModel(batch_size, dataset_len, drop_last, max_steps)