fc9e5824ad7bd3094f5012dc6fc3d2348481a2f4,implementations/bicyclegan/bicyclegan.py,,sample_images,#Any#,112

Before Change

        real_A = Variable(real_A.type(Tensor))
        // Get interpolated noise [-1, 1]
        sampled_z = np.repeat(np.linspace(-1, 1, 8)[:, np.newaxis], opt.latent_dim, 1)
        sampled_z = Variable(Tensor(sampled_z))
        // Generator samples
        fake_B = generator(real_A, sampled_z)
        // Concatenate samples horisontally
        fake_B = torch.cat([x for x in fake_B.data.cpu()], -1)

After Change

        real_A = img_A.view(1, *img_A.shape).repeat(opt.latent_dim, 1, 1, 1)
        real_A = Variable(real_A.type(Tensor))
        // Sample latent representations
        sampled_z = Variable(Tensor(np.random.normal(0, 1, (opt.latent_dim, opt.latent_dim))))
        // Generate samples
        fake_B = generator(real_A, sampled_z)
        // Concatenate samples horisontally
        fake_B = torch.cat([x for x in fake_B.data.cpu()], -1)

Instances