class_docstr: Configurations with MNIST data and Train & Validation setup
class_docstr_tok: ["Configurations","with","MNIST","data","and","Train","&","Validation","setup"]
code: def init(self):
      # Print losses and accuracy to screen
      tracker.set_scalar("loss.*", True)
      tracker.set_scalar("accuracy.*", True)
  
      # We need to set the metrics to calculate them for the epoch for training and validation
      self.state_modules = [self.accuracy]
  
imports: from typing import Any
  import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from labml import experiment, tracker
  from labml.configs import option
  from labml_helpers.datasets.mnist import MNISTConfigs
  from labml_helpers.metrics.accuracy import AccuracyDirect
  from labml_helpers.module import Module
  from labml_helpers.train_valid import SimpleTrainValidConfigs, BatchIndex
  from labml_nn.capsule_networks import Squash, Router, MarginLoss
label_desc: Use image node_id 1 for calling the Configs obj's underlying member method code with example usage: obj.init() without return types