From eebafafb8892061b8238eb169910a9622f095ee8 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Fri, 14 May 2021 13:12:50 -0500
Subject: [PATCH] minor...
---
modules/deeplearning/icing_cnn.py | 9 ++++++++-
1 file changed, 8 insertions(+), 1 deletion(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index 386cf749..5409e32c 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -148,6 +148,7 @@ class IcingIntensityNN:
self.test_loss = None
self.test_accuracy = None
self.test_auc = None
+ self.test_f1 = None
self.test_recall = None
self.test_precision = None
self.test_confusion_matrix = None
@@ -462,12 +463,14 @@ class IcingIntensityNN:
self.train_accuracy = tf.keras.metrics.BinaryAccuracy(name='train_accuracy')
self.test_accuracy = tf.keras.metrics.BinaryAccuracy(name='test_accuracy')
self.test_auc = tf.keras.metrics.AUC(name='test_auc')
+ self.test_f1 = tfa.metrics.F1Score(name='test_f1')
self.test_recall = tf.keras.metrics.Recall(name='test_recall')
self.test_precision = tf.keras.metrics.Precision(name='test_precision')
else:
self.train_accuracy = tf.keras.metrics.SparseCategoricalAccuracy(name='train_accuracy')
self.test_accuracy = tf.keras.metrics.SparseCategoricalAccuracy(name='test_accuracy')
self.test_auc = tf.keras.metrics.AUC(name='test_auc')
+ self.test_f1 = tfa.metrics.F1Score(name='f1_score')
self.test_recall = tf.keras.metrics.Recall(name='test_recall')
self.test_precision = tf.keras.metrics.Precision(name='test_precision')
@@ -509,6 +512,7 @@ class IcingIntensityNN:
self.test_accuracy(labels, pred)
if NumClasses == 2:
self.test_auc(labels, pred)
+ self.test_f1(labels, pred)
self.test_recall(labels, pred)
self.test_precision(labels, pred)
@@ -524,6 +528,7 @@ class IcingIntensityNN:
self.test_loss(t_loss)
self.test_accuracy(labels, pred)
self.test_auc(labels, pred)
+ self.test_f1(labels, pred)
self.test_recall(labels, pred)
self.test_precision(labels, pred)
@@ -580,6 +585,7 @@ class IcingIntensityNN:
tf.summary.scalar('loss_val', self.test_loss.result(), step=step)
tf.summary.scalar('acc_val', self.test_accuracy.result(), step=step)
tf.summary.scalar('auc_val', self.test_auc.result(), step=step)
+ tf.summary.scalar('f1_val', self.test_f1.result(), step=step)
tf.summary.scalar('recall_val', self.test_recall.result(), step=step)
tf.summary.scalar('prec_val', self.test_precision.result(), step=step)
tf.summary.scalar('num_train_steps', step, step=step)
@@ -601,6 +607,7 @@ class IcingIntensityNN:
self.test_loss.reset_states()
self.test_accuracy.reset_states()
self.test_auc.reset_states()
+ self.test_f1.reset_states()
self.test_recall.reset_states()
self.test_precision.reset_states()
@@ -611,7 +618,7 @@ class IcingIntensityNN:
self.test_step(mini_batch)
print('loss, acc, auc, recall, precision: ', self.test_loss.result().numpy(), self.test_accuracy.result().numpy(),
- self.test_auc.result().numpy(), self.test_recall.result().numpy(), self.test_precision.result().numpy())
+ self.test_auc.result().numpy(), self.test_f1.result().numpy(), self.test_recall.result().numpy(), self.test_precision.result().numpy())
print('--------------------------------------------------')
ckpt_manager.save()
--
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