Misleading printing?

[FairyOnIce]

I am using l0_attack.py.
The default printing shows:

            equal_count = self.model.image_size**2-np.sum(np.all(np.abs(img-nimg[0])<.0001,axis=2))
            print("Forced equal:",np.sum(1-valid),
                  "Equal count:",equal_count)

"Equal count" may be misleading as this number is the number of pixels that are different from (not equal to) the original image at the current iteration. Should it be

            print("Forced equal:",np.sum(1-valid),
                  "Different count:",equal_count)

or

            print("Forced equal:",np.sum(1-valid),
                  "L0:",equal_count)

nn_robust_attacks/l0_attack.py

Line 227 in 610c43f

equal_count = self.model.image_size**2-np.sum(np.all(np.abs(img-nimg[0])<.0001,axis=2))