diff --git a/modules/deeplearning/cloud_opd_fcn_abi.py b/modules/deeplearning/cloud_opd_fcn_abi.py
index 0c3f8007d60cb6eb28d8a76831159709a0947bcd..314cbf1d66120b42207185584cbb27b61ca84a2e 100644
--- a/modules/deeplearning/cloud_opd_fcn_abi.py
+++ b/modules/deeplearning/cloud_opd_fcn_abi.py
@@ -687,7 +687,6 @@ class SRCNN:
         preds = np.concatenate(self.test_preds)
         inputs = np.concatenate(self.test_input)
         cat_cld_frac = np.concatenate(self.test_cat_cf)
-        print(labels.shape, preds.shape, cat_cld_frac.shape, inputs.shape)
 
         # labels = denormalize(labels, label_param, mean_std_dct)
         # preds = denormalize(preds, label_param, mean_std_dct)
@@ -897,12 +896,13 @@ def run_restore_static(directory, ckpt_dir, out_file=None):
     if out_file is not None:
         y_hi, x_hi = (Y_LEN // 4) + 1, (X_LEN // 4) + 1
         np.save(out_file,
-                [labels, preds,
+                [labels[:, :, :, 0], preds[:, :, :, 0],
                  inputs[:, 1:y_hi, 1:x_hi, 0],
                  descale(inputs[:, 1:y_hi, 1:x_hi, 1], 'refl_0_65um_nom', mean_std_dct),
                  descale(inputs[:, 1:y_hi, 1:x_hi, 2], 'refl_0_65um_nom', mean_std_dct),
                  inputs[:, 1:y_hi, 1:x_hi, 3],
-                 descale(inputs[:, 1:y_hi, 1:x_hi, 4], label_param, mean_std_dct)])
+                 descale(inputs[:, 1:y_hi, 1:x_hi, 4], label_param, mean_std_dct),
+                 cat_cld_frac[:, :, :]])
 
 
 def run_evaluate_static(in_file, out_file, ckpt_dir):