diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py
index 6ae3fb5..3f4864a 100644
--- a/models/Model_SAEHD/Model.py
+++ b/models/Model_SAEHD/Model.py
@@ -465,7 +465,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
                         gpu_src_loss += tf.reduce_mean( (10*bg_style_power)*tf.square(gpu_psd_target_dst_style_anti_masked - gpu_target_dst_style_anti_masked), axis=[1,2,3] )
 
                     if self.options['ms_ssim_loss']:
-                        gpu_dst_loss =  tf.reduce_mean ( 10*nn.MsSsim(resolution)(gpu_target_dst_masked_opt, gpu_pred_dst_dst_masked_opt, max_val=1.0))
+                        gpu_dst_loss = 10*nn.MsSsim(resolution)(gpu_target_dst_masked_opt, gpu_pred_dst_dst_masked_opt, max_val=1.0)
                     else:
                         if resolution < 256:
                             gpu_dst_loss = tf.reduce_mean ( 10*nn.dssim(gpu_target_dst_masked_opt, gpu_pred_dst_dst_masked_opt, max_val=1.0, filter_size=int(resolution/11.6) ), axis=[1])
@@ -484,15 +484,14 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
                             gpu_target_part_mask = gpu_target_dstm_mouth
 
                         if self.options['ms_ssim_loss']:
-                            gpu_dst_loss += tf.reduce_mean ( 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_dst*gpu_target_part_mask, gpu_pred_dst_dst*gpu_target_part_mask, max_val=1.0))
+                            gpu_dst_loss += 300 * nn.MsSsim(resolution, kernel_size=5)(gpu_target_dst*gpu_target_part_mask, gpu_pred_dst_dst*gpu_target_part_mask, max_val=1.0)
                         else:
                             gpu_dst_loss += tf.reduce_mean ( 300*tf.abs ( gpu_target_dst*gpu_target_part_mask - gpu_pred_dst_dst*gpu_target_part_mask ), axis=[1,2,3])
 
-                    # FIXME
-                    # if self.options['ms_ssim_loss']:
-                    #     gpu_dst_loss +=  tf.reduce_mean ( 10*nn.MsSsim(resolution)(gpu_target_dstm, gpu_pred_dst_dstm, max_val=1.0))
-                    # else:
-                    gpu_dst_loss += tf.reduce_mean ( 10*tf.square( gpu_target_dstm - gpu_pred_dst_dstm ),axis=[1,2,3] )
+                    if self.options['ms_ssim_loss']:
+                        gpu_dst_loss += 10 * nn.MsSsim(resolution)(gpu_target_dstm, gpu_pred_dst_dstm, max_val=1.0)
+                    else:
+                        gpu_dst_loss += tf.reduce_mean ( 10*tf.square( gpu_target_dstm - gpu_pred_dst_dstm ),axis=[1,2,3] )
 
                     gpu_src_losses += [gpu_src_loss]
                     gpu_dst_losses += [gpu_dst_loss]