code: def __init__(self, lr: float, layer_1: int, layer_2: int):
      super(LightningMNISTClassifier, self).__init__()
  
      self.lr = lr
      # mnist images are (1, 28, 28) (channels, width, height)
      self.layer_1 = torch.nn.Linear(28 * 28, layer_1)
      self.layer_2 = torch.nn.Linear(layer_1, layer_2)
      self.layer_3 = torch.nn.Linear(layer_2, 10)
      self.accuracy = Accuracy(
          task="multiclass", num_classes=10, top_k=1
      )
      self.val_acc_list = []
      self.val_loss_list = []
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from torchmetrics import Accuracy
  from ray import train
  from ray.train.lightning._lightning_utils import import_lightning
label_desc: Use image node_id 1 to create a new LightningMNISTClassifier object from inherited base classes: pl with example: obj = LightningMNISTClassifier(lr, layer_1, layer_2)