new_contents: from functools import partial
  
  from toolbox.data import load_set
  from toolbox.models import compile_srcnn
  from toolbox.experiment import Experiment
  from toolbox.preprocessing import bicubic_resize
  
  
  # Model
  scale = 4
  model = compile_srcnn(c=1, f1=9, f2=1, f3=5, n1=64, n2=32)
  model.summary()
  
  # Data
  train_set = '91-image'
  val_set = 'Set5'
  test_sets = ['Set5', 'Set14']
  preprocess = partial(bicubic_resize, size=scale)
  load_set = partial(load_set, sub_size=11, sub_stride=5, scale=scale,
                     channel=0, preprocess=preprocess)
  
  # Training
  experiment = Experiment(scale=scale, model=model, preprocess=preprocess,
                          load_set=load_set, save_dir='.')
  experiment.train(train_set=train_set, val_set=val_set, epochs=500, resume=True)
  
  # Evaluation
  for test_set in test_sets:
      experiment.test(test_set=test_set)
  
subject: Update run.py