From d4ee60d8ea106802dd6ca4353f96e7340608dcdb Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 13 Nov 2023 13:04:44 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/icing_fcn.py | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/modules/deeplearning/icing_fcn.py b/modules/deeplearning/icing_fcn.py
index 7271cd68..aeb70a63 100644
--- a/modules/deeplearning/icing_fcn.py
+++ b/modules/deeplearning/icing_fcn.py
@@ -1191,18 +1191,18 @@ def run_evaluate_static_avg(ckpt_dir_s_path, day_night='NIGHT', l1b_andor_l2='BO
sum += w
avg_weights = sum / len(weight_s)
- # ---------------------------------------------
-
+ # -- Make a new model for the averaged weights
new_model = IcingIntensityFCN(day_night=day_night, l1b_or_l2=l1b_andor_l2, use_flight_altitude=use_flight_altitude)
new_model.build_model()
new_model.build_training()
new_model.build_evaluation()
- if ckpt_dir is None:
- if not os.path.exists(modeldir):
- os.mkdir(modeldir)
- ckpt = tf.train.Checkpoint(step=tf.Variable(1), model=new_model.model)
- ckpt_manager = tf.train.CheckpointManager(ckpt, modeldir, max_to_keep=3)
+ # -- save the averaged weights to a new the model
+ if not os.path.exists(modeldir):
+ os.mkdir(modeldir)
+ ckpt = tf.train.Checkpoint(step=tf.Variable(1), model=new_model.model)
+ ckpt_manager = tf.train.CheckpointManager(ckpt, modeldir, max_to_keep=3)
+
new_model.model.set_weights(avg_weights)
ckpt_manager.save()
--
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