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Hi, Thank you for this amazing works. I have a little question about this funtion at this line
def cal_loss(self, im_dict, latent_in, latent_F=None, F_init=None):
In both "invert_images_in_FS" & "invert_images_in_w", it seems that you didn't pass "latent_F" & "F_init" in cal_loss to do the computation below:
if latent_F is not None and F_init is not None: l_F = self.net.cal_l_F(latent_F, F_init) loss_dic['l_F'] = l_F loss += l_F
I wonder that should we still calaulate l_F loss in somewhere? or I misunderstanding somethings?
BR, Ziv
The text was updated successfully, but these errors were encountered:
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Hi,
Thank you for this amazing works. I have a little question about this funtion at this line
In both "invert_images_in_FS" & "invert_images_in_w", it seems that you didn't pass "latent_F" & "F_init" in cal_loss to do the computation below:
I wonder that should we still calaulate l_F loss in somewhere? or I misunderstanding somethings?
BR,
Ziv
The text was updated successfully, but these errors were encountered: