Function generate_examples

ProGAN/demo.py:282–294

Tried using truncation trick here but not sure it actually helped anything, you can remove it if you like and just sample from torch.randn

(gen, steps, truncation=0.7, n=100)

    torch.backends.cudnn.benchmark = False

def generate_examples(gen, steps, truncation=0.7, n=100):
    """
    Tried using truncation trick here but not sure it actually helped anything, you can
    remove it if you like and just sample from torch.randn
    """
    gen.eval()
    alpha = 1.0
    for i in range(n):
        with torch.no_grad():
            noise = torch.tensor(truncnorm.rvs(-truncation, truncation, size=(1,Z_DIM, 1, 1)), device=DEVICE, dtype=torch.float32)
            img = gen(noise, alpha, steps)
            save_image(img*0.5+0.5, f"saved_examples/img_{i}.png")
    gen.train()