plot.py

for x_adv, grad in iterator:

    # get model predictions
    x_adv_predictions = predict(model, x_adv)
    
    plot(x_original, x_adv, grad, epsilon,
         x_label=x_predictions['label'],
         x_prob=x_predictions['confidence'],
         x_adv_label=x_adv_predictions['label'],
         x_adv_prob=x_adv_predictions['confidence'])
    
    # starting image new iteration
    x_original = x_adv
    x_predictions = predict(model, x_original)