From 437f8030bc7cf6afbebb19f64e2c886dfbf2f7a0 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 9 Aug 2021 16:34:50 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/icing_cnn.py | 12 ++++++++----
1 file changed, 8 insertions(+), 4 deletions(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index d73948e4..5221e041 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -419,7 +419,7 @@ class IcingIntensityNN:
momentum = 0.99
# num_filters = 16
- num_filters = 12
+ num_filters = 24
conv = tf.keras.layers.Conv2D(num_filters, 5, strides=[1, 1], padding=padding, activation=activation)(self.inputs[0])
conv = tf.keras.layers.MaxPool2D(padding=padding)(conv)
@@ -871,12 +871,16 @@ class IcingIntensityNN:
return filename, ice_lons, ice_lats
-def run_restore_static(filename_tst, ckpt_dir_s):
+def run_restore_static(filename_tst, ckpt_dir_s_path):
+ ckpt_dir_s = os.listdir(ckpt_dir_s_path)
cm_s = []
- for ckpt_dir in ckpt_dir_s:
+ for ckpt in ckpt_dir_s:
+ ckpt_dir = ckpt_dir_s_path + ckpt
+ if not os.path.isdir(ckpt_dir):
+ continue
nn = IcingIntensityNN()
nn.run_restore(filename_tst, ckpt_dir)
- cm_s.append(tf.math.confusion_matrix(nn.test_labels, nn.test_preds))
+ cm_s.append(tf.math.confusion_matrix(nn.test_labels.flatten(), nn.test_preds.flatten()))
num = len(cm_s)
cm_avg = cm_s[0]
for k in range(num-1):
--
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