text: import torch
  from tqdm import tqdm
  
  
  def train_classifier(
      clf, optimizer_clf, train_loader, loss_criterion, epochs, device
  ):
      clf.to(device)
      total_classifier_loss = 0
      steps = 0
      pbar = tqdm(range(epochs))
      for _ in pbar:
          epoch_loss = 0
          epoch_batches = 0
  
          for data in train_loader:
  
              inputs, label, _ = data
              inputs, label = inputs.to(device), label.to(device)
  
              optimizer_clf.zero_grad()
  
              classifier_output = clf(inputs)
              classifier_loss = loss_criterion(classifier_output, label)
              classifier_loss.backward()
              optimizer_clf.step()
              total_classifier_loss += classifier_loss.item()
              epoch_loss += classifier_loss.item()
              epoch_batches += 1
              steps += 1
  
              pbar.set_description(
                  f"Average Clf epoch loss: {epoch_loss/epoch_batches}"
              )
  
      print("Average Clf batch loss: ", total_classifier_loss / steps)
  
      return clf
  