text: import torch.nn as nn
  import torch
  
  import lib
  import data
  import utils
  import metrics
  import viz
  
  def test():
  
      inputs = {
          'model': nn.Sequential(nn.Linear(28*28, 32), nn.ReLU(), nn.Linear(32, 2)),
          'learning_rate': 0.1,
          'dataset_size': 512,
          'batch_size': 512,
          'epochs': 10000,
          'parameters_seed': 0,
          'loss_function': metrics.cross_entropy_loss,
          'classification_labels': ['3', '7'],
          'whiten_images': False,
          'data_path': utils.download_dataset('mnist_sample', 'data'),
          'randomize_dataset_seed': 0,
          'experiment_nickname': 'TEST-EXPERIMENT'
      }
  
      experiment = lib.run_one_experiment(**inputs)
  
      return experiment
  