docstr: Generic data loader function
  
  :param df: Input tensor
  
  :return: Returns the constructed dataloader
docstr_tok: ["Generic","data","loader","function",":","param","df",":","Input","tensor",":","return",":","Returns","the","constructed","dataloader"]
code: def create_data_loader(self, df):
      """
      Generic data loader function
  
      :param df: Input tensor
  
      :return: Returns the constructed dataloader
      """
      return DataLoader(
          df, batch_size=self.batch_size, num_workers=self.num_workers
      )
  
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 3 for calling the MNISTDataModule obj's underlying member method code with example usage: obj.create_data_loader(df) and returns: DataLoader