docstr: Initialization of inherited lightning data module
docstr_tok: ["Initialization","of","inherited","lightning","data","module"]
code: def __init__(self, batch_size=64, num_workers=3):
      """
      Initialization of inherited lightning data module
      """
      super().__init__()
      self.df_train = None
      self.df_val = None
      self.df_test = None
      self.train_data_loader = None
      self.val_data_loader = None
      self.test_data_loader = None
      self.batch_size = batch_size
      self.num_workers = num_workers
  
      # transforms for images
      self.transform = transforms.Compose(
          [
              transforms.ToTensor(),
              transforms.Normalize((0.1307,), (0.3081,)),
          ]
      )
  
imports: import os
  import lightning
  import torch
  from lightning.pytorch.callbacks import EarlyStopping, LearningRateMonitor, ModelCheckpoint
  from lightning.pytorch.cli import LightningCLI
  from torch.nn import functional
  from torch.utils.data import DataLoader, random_split
  from torchmetrics.functional import accuracy
  from torchvision import datasets, transforms
  import mlflow.pytorch
label_desc: Use image node_id 1 to create a new MNISTDataModule object from inherited base class: L with example: obj = MNISTDataModule(batch_size, num_workers)