d9e93765aad7a42aafc357fabcd3ef644aa6dde6,implementations/cgan/cgan.py,,sample_image,#,138

Before Change

    // Sample noise
    z = Variable(FloatTensor(np.random.normal(0, 1, (10, opt.latent_dim))))
    // Get labels ranging from 0 to n_classes for n rows
    labels = np.arange(0, 10, 10)
    labels = Variable(LongTensor(labels))
    gen_imgs = generator(z, labels)
    save_image(gen_imgs.data, "images/%d.png" % batches_done, nrow=5, normalize=True)

After Change

    // Sample noise
    z = Variable(FloatTensor(np.random.normal(0, 1, (n_row**2, opt.latent_dim))))
    // Get labels ranging from 0 to n_classes for n rows
    labels = np.array([num for _ in range(n_row) for num in range(n_row)])
    labels = Variable(LongTensor(labels))
    gen_imgs = generator(z, labels)
    save_image(gen_imgs.data, "images/%d.png" % batches_done, nrow=n_row, normalize=True)

Instances