content: import os
  from tqdm import tqdm
  import numpy as np
  from mypath import Path
  
  def calculate_weigths_labels(dataset, dataloader, num_classes):
      # Create an instance from the data loader
      z = np.zeros((num_classes,))
      # Initialize tqdm
      tqdm_batch = tqdm(dataloader)
      print('Calculating classes weights')
      for sample in tqdm_batch:
          y = sample['label']
          y = y.detach().cpu().numpy()
          mask = (y >= 0) & (y < num_classes)
          labels = y[mask].astype(np.uint8)
          count_l = np.bincount(labels, minlength=num_classes)
          z += count_l
      tqdm_batch.close()
      total_frequency = np.sum(z)
      class_weights = []
      for frequency in z:
          class_weight = 1 / (np.log(1.02 + (frequency / total_frequency)))
          class_weights.append(class_weight)
      ret = np.array(class_weights)
      classes_weights_path = os.path.join(Path.db_root_dir(dataset), dataset+'_classes_weights.npy')
      np.save(classes_weights_path, ret)
  
      return ret