code: def on_epoch_end_from_steps(steps):
      def on_epoch_end(network):
          if network.last_epoch in steps:
              print("Saving pre-trained VIN model...")
              storage.save(network, env["pretrained_network_file"])
  
              new_step = steps[network.last_epoch]
              session = tensorflow_session()
              network.step.load(new_step, session)
  
      return on_epoch_end
  
imports: import os
  import argparse
  from functools import partial
  import tensorflow
  from neupy import init, algorithms, storage
  from neupy.layers import *
  from neupy.utils import as_tuple, asfloat, tf_utils, tensorflow_session
  from loaddata import load_data
  from settings import MODELS_DIR, environments
  from evaluation import evaluate_accuracy
label_desc: Use image node_id 4 for calling a global function with example usage: on_epoch_end_from_steps(steps) and returns: on_epoch_end