8776ca2dcfa98412a6dafc33d360ee1ba0d1b551,src/test.py,,main,#,8

Before Change

    img1 = img1.cuda()
    imgs = [img1]
    names = ["input"]
    for idx2, img2 in enumerate(loader2):
      if idx2 == opts.num:
        break
      img2 = img2.cuda()
      with torch.no_grad():
        if opts.a2b:
          img = model.test_forward(img1, img2, opts.random_z, a2b=True)
        else:
          img = model.test_forward(img2, img1, opts.random_z, a2b=False)
      imgs.append(img)
      names.append("output_{}".format(idx2))
    save_imgs(imgs, names, os.path.join(result_dir, "{}".format(idx1)))

  return

After Change

    img1 = img1.cuda()
    imgs = [img1]
    names = ["input"]
    for n in range(opts.num):
      with torch.no_grad():
        img = model.test_forward(img1, a2b=opts.a2d)
      imgs.append(img)
      names.append("output_{}".format(idx2))
    save_imgs(imgs, names, os.path.join(result_dir, "{}".format(idx1)))

  return

Instances