class_docstr: ## Configurations
class_docstr_tok: ["#","#","Configurations"]
docstr: ### Training loop
docstr_tok: ["#","#","#","Training","loop"]
code: def run(self):
      """
      ### Training loop
      """
      for _ in monit.loop(self.epochs):
          # Train the model
          self.train()
          # New line in the console
          tracker.new_line()
          # Save the model
          experiment.save_checkpoint()
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/unet/experiment.py
imports: import numpy
  import torch
  import torch.utils.data
  import torchvision.transforms.functional
  from torch import nn
  from labml import lab, tracker, experiment, monit
  from labml.configs import BaseConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_nn.unet.carvana import CarvanaDataset
  from labml_nn.unet import UNet
label_desc: Use image node_id 4 for calling the Configs obj's underlying member method code with example usage: obj.run() without return types