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",
)