def visualize_demo4_data(): data_dir = get_data_dir(2) train_data, test_data = load_pickled_data(join(data_dir, "shapes.pkl")) name = "Shape" idxs = np.random.choice(len(train_data), replace=False, size=(100, )) images = train_data[idxs] * 255 show_samples(images, title=f"{name} Samples")
def demo4_save_results(fn): data_dir = get_data_dir(2) train_data, test_data = load_pickled_data(join(data_dir, 'shapes.pkl')) train_losses, test_losses, samples, floored_samples = fn(train_data, test_data) samples = samples.astype('float') floored_samples = floored_samples.astype('float') print(f'Final Test Loss: {test_losses[-1]:.4f}') save_training_plot(train_losses, test_losses, f'Q2 Dataset Train Plot', 'results/demo4_train_plot.png') show_samples(samples * 255.0) show_samples(floored_samples * 255.0, title='Samples with Flooring')
def demo6_save_results(fn, part): data_dir = get_data_dir(2) train_data, test_data = load_pickled_data(join(data_dir, 'celeb.pkl')) train_losses, test_losses, samples, interpolations = fn(train_data, test_data) samples = samples.astype('float') interpolations = interpolations.astype('float') print(f'Final Test Loss: {test_losses[-1]:.4f}') save_training_plot(train_losses, test_losses, f'RealNVP Train Plot', f'results/demo6_{part}_train_plot.png') show_samples(samples * 255.0, f'results/demo6_{part}_samples.png') show_samples(interpolations * 255.0, f'results/demo6_{part}_interpolations.png', nrow=6, title='Interpolations')
def demo4_save_results(fn): data_dir = get_data_dir(2) train_data, test_data = load_pickled_data(join(data_dir, "shapes.pkl")) train_losses, test_losses, samples, floored_samples = fn( train_data, test_data) samples = samples.astype("float") floored_samples = floored_samples.astype("float") print(f"Final Test Loss: {test_losses[-1]:.4f}") save_training_plot( train_losses, test_losses, f"Q2 Dataset Train Plot", "results/demo4_train_plot.png", ) show_samples(samples * 255.0) show_samples(floored_samples * 255.0, title="Samples with Flooring")
def demo6_save_results(fn, part): data_dir = get_data_dir(2) train_data, test_data = load_pickled_data(join(data_dir, "celeb.pkl")) train_losses, test_losses, samples, interpolations = fn( train_data, test_data) samples = samples.astype("float") interpolations = interpolations.astype("float") print(f"Final Test Loss: {test_losses[-1]:.4f}") save_training_plot( train_losses, test_losses, f"RealNVP Train Plot", f"results/demo6_{part}_train_plot.png", ) show_samples(samples * 255.0, f"results/demo6_{part}_samples.png") show_samples( interpolations * 255.0, f"results/demo6_{part}_interpolations.png", nrow=6, title="Interpolations", )