text: 
  from collections import OrderedDict
  
  config_name = 'unet_softpool'
  
  config_dataset = OrderedDict([
      ('dataset', 'hyper'),
      ('channels', 60),
      ('n_class', 2),
      ('norm_kwargs', {'type':'data'}),
      ('npy_dir', '../cancer/npy/'),
      ('label_dir', '../cancer/label/'),
      ('train_split', '../cancer/split/split_0_train.txt'),
      ('val_split', '../cancer/split/split_0_val.txt'),
      ('test_split', '../cancer/split/split_0_test.txt'),
      ('batch_size', 1),
      ('channel_transform', 'none'),
      ('aug_config', 'none')
  ])
  
  config_model = OrderedDict([
      ('model', config_name),
      ('layers', 4),
      ('feature_root', 32),
      ('conv_repeat', 2),
      ('use_bn', True),
      ('track_running_stats', False),
      # ('track_running_stats', True),
      ('bn_momentum', 0.1),
      ('use_gn', False),
      ('num_groups', 16),
      ('epoch', 50),
      ('save_interval', 5),
      ('restore', False),  # TODO: restore training not implemented!
  ])
  
  config_optimizer = OrderedDict([
      ('loss', 'BCE'),
      ('optimizer', 'Adam'),
      ('learning_rate', 0.001),
      ('weight_decay', 0.001),
      ('scheduler', [40]),
      ('scheduler_rate', 0.1),
  ])
  
  config_utils = OrderedDict([
      ('workdir', '../cancer/workdir/{}_public/'.format(config_name)),
      ('work_phase', 'train-val-test'),
      # ('work_phase', 'train-test'),
      # ('work_phase', 'test'),
  ])
  
  config_public = OrderedDict()
  config_public.update(config_dataset)
  config_public.update(config_model)
  config_public.update(config_optimizer)
  config_public.update(config_utils)
  
  config_split_all = []
  ##################################################    split configs
  for i in range(5):
      config_split_all.append(config_public.copy())
      config_split_all[-1]['train_split'] = '../cancer/split/split_{}_train.txt'.format(i)
      config_split_all[-1]['val_split'] = '../cancer/split/split_{}_val.txt'.format(i)
      config_split_all[-1]['test_split'] = '../cancer/split/split_{}_test.txt'.format(i)
      config_split_all[-1]['workdir'] = '../cancer/workdir/{}_split_{}/'.format(config_name, i)
  ##################################################    split configs
  
  all_configs = config_split_all
  # all_configs = []
  