code: def __init__(self, df, augmentations):
      self.df = df
      self.targets = df.label.values
      self.df = self.df.drop(columns=["label"])
      self.augmentations = augmentations
  
      self.images = self.df.to_numpy(dtype=np.float32).reshape(
          (-1, 28, 28)
      )
  
imports: import argparse
  import os
  import albumentations
  import numpy
  import pandas
  import timm
  import torch
  import torch.nn
  from sklearn import metrics, model_selection
  from tez import Tez, TezConfig
  from tez.callbacks import EarlyStopping
  from tez.utils import seed_everything
label_desc: Use image node_id 1 to create a new DigitRecognizerDataset object  with example: obj = DigitRecognizerDataset(df, augmentations)