snapshot...

modules/deeplearning/icing_fcn.py

 import tensorflow as tf
 from util.setup import logdir, modeldir, cachepath, now, ancillary_path, home_dir
 from util.util import EarlyStop, normalize
-from icing.util import make_for_full_domain_predict, get_training_parameters
 from util.geos_nav import get_navigation
 from util.augment import augment_image_3arg
 
@@ -1095,13 +1094,13 @@ class IcingIntensityFCN:
         if self.h5f_l2_tst is not None:
             self.h5f_l2_tst.close()
 
-    def run_evaluate(self, filename, ckpt_dir):
-        data_dct, ll, cc = make_for_full_domain_predict(filename, name_list=self.train_params)
-        self.setup_eval_pipeline(data_dct, len(ll))
-        self.build_model()
-        self.build_training()
-        self.build_evaluation()
-        self.do_evaluate(ckpt_dir)
+    # def run_evaluate(self, filename, ckpt_dir):
+    #     data_dct, ll, cc = make_for_full_domain_predict(filename, name_list=self.train_params)
+    #     self.setup_eval_pipeline(data_dct, len(ll))
+    #     self.build_model()
+    #     self.build_training()
+    #     self.build_evaluation()
+    #     self.do_evaluate(ckpt_dir)
 
 
 def run_restore_static(filename_l1b, filename_l2, ckpt_dir_s_path, day_night='DAY', l1b_or_l2='both',