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in parer loss hair is difine as
but in train_mapper.py this loss do not dot with hair mask.. wondering why
loss_l2_latent = self.latent_l2_loss(w_hat, res_w) loss_dict['loss_l2_latent'] = float(loss_l2_latent) loss += loss_l2_latent * self.latent_l2_lambda loss_l2_img = torch.mean(((res_x - x_hat)) ** 2, dim=[0, 1, 2, 3]) ### do not dot with hair mask loss_dict['loss_l2_res_img'] = float(loss_l2_img) loss += loss_l2_img * self.img_l2_lambda_res loss_l2_img = torch.mean(((origin_img - x_hat) * mask) ** 2, dim=[0, 1, 2, 3]) loss_dict['loss_l2_origin_img'] = float(loss_l2_img) loss += loss_l2_img * self.img_l2_lambda_origin
The text was updated successfully, but these errors were encountered:
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in parer loss hair is difine as
but in train_mapper.py this loss do not dot with hair mask.. wondering why
The text was updated successfully, but these errors were encountered: