snapshot...

modules/deeplearning/cnn_cld_frac_mod_res.py

@@ -184,8 +184,9 @@ def get_min_max_std(grd_k):
     lo = np.nanmin([a, b, c, d], axis=0)
     hi = np.nanmax([a, b, c, d], axis=0)
     std = np.nanstd([a, b, c, d], axis=0)
+    avg = np.nanmean([a, b, c, d], axis=0)
 
-    return lo, hi, std
+    return lo, hi, std, mean
 
 
 def get_label_data(grd_k):
@@ -605,7 +606,6 @@ class SRCNN:
     # @tf.function(input_signature=[tf.TensorSpec(None, tf.float32), tf.TensorSpec(None, tf.float32)])
     # decorator commented out because pred.numpy(): pred not evaluated yet.
     def predict(self, inputs, labels):
-        labels = tf.squeeze(labels)
         pred = self.model([inputs], training=False)
         t_loss = self.loss(tf.squeeze(labels), pred)