From 53b5ac7f2644693e1a949d00a1b49d1bf17d4d7f Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 10 Feb 2022 13:10:17 -0600
Subject: [PATCH] snapshot...don't unnecessarily reload chkpt files
---
modules/deeplearning/icing_cnn.py | 22 ++++++++++++++--------
1 file changed, 14 insertions(+), 8 deletions(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index dfe113af..15b3bafc 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -967,10 +967,10 @@ class IcingIntensityNN:
def do_evaluate(self, ckpt_dir=None, prob_thresh=0.5):
- if ckpt_dir is not None: # if is None, this has been done already
- ckpt = tf.train.Checkpoint(step=tf.Variable(1), model=self.model)
- ckpt_manager = tf.train.CheckpointManager(ckpt, ckpt_dir, max_to_keep=3)
- ckpt.restore(ckpt_manager.latest_checkpoint)
+ # if ckpt_dir is not None: # if is None, this has been done already
+ # ckpt = tf.train.Checkpoint(step=tf.Variable(1), model=self.model)
+ # ckpt_manager = tf.train.CheckpointManager(ckpt, ckpt_dir, max_to_keep=3)
+ # ckpt.restore(ckpt_manager.latest_checkpoint)
self.reset_test_metrics()
@@ -1115,13 +1115,19 @@ def run_evaluate_static(data_dct, num_tiles, ckpt_dir_s_path, day_night='DAY', l
probs_dct = {flvl: None for flvl in flight_levels}
preds_dct = {flvl: None for flvl in flight_levels}
+ nn = IcingIntensityNN(day_night=day_night, l1b_or_l2=l1b_or_l2, use_flight_altitude=use_flight_altitude)
+ nn.num_data_samples = num_tiles
+ nn.build_model()
+ nn.build_training()
+ nn.build_evaluation()
+
+ ckpt = tf.train.Checkpoint(step=tf.Variable(1), model=nn.model)
+ ckpt_manager = tf.train.CheckpointManager(ckpt, ckpt_dir, max_to_keep=3)
+ ckpt.restore(ckpt_manager.latest_checkpoint)
+
for flvl in flight_levels:
- nn = IcingIntensityNN(day_night=day_night, l1b_or_l2=l1b_or_l2, use_flight_altitude=use_flight_altitude)
nn.flight_level = flvl
nn.setup_eval_pipeline(data_dct, num_tiles)
- nn.build_model()
- nn.build_training()
- nn.build_evaluation()
nn.do_evaluate(ckpt_dir)
probs = nn.test_probs
--
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