From 22ac47ae45eaa195321b455af2355cc42e8242fc Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 20 May 2021 09:58:23 -0500
Subject: [PATCH] minor...
---
modules/deeplearning/icing_cnn.py | 16 ++--------------
1 file changed, 2 insertions(+), 14 deletions(-)
diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index 86e4dea0..8a93537a 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -21,7 +21,7 @@ NumLogits = 1
BATCH_SIZE = 256
NUM_EPOCHS = 200
-TRACK_MOVING_AVERAGE = False
+TRACK_MOVING_AVERAGE = True
TRIPLET = False
CONV3D = False
@@ -462,13 +462,9 @@ class IcingIntensityNN:
self.learningRateSchedule = tf.keras.optimizers.schedules.ExponentialDecay(initial_learning_rate, decay_steps, decay_rate)
optimizer = tf.keras.optimizers.Adam(learning_rate=self.learningRateSchedule)
- optimizer = tfa.optimizers.MovingAverage(optimizer)
if TRACK_MOVING_AVERAGE:
- ema = tf.train.ExponentialMovingAverage(decay=0.999)
-
- with tf.control_dependencies([optimizer]):
- optimizer = ema.apply(self.model.trainable_variables)
+ optimizer = tfa.optimizers.MovingAverage(optimizer)
self.optimizer = optimizer
self.initial_learning_rate = initial_learning_rate
@@ -498,14 +494,6 @@ class IcingIntensityNN:
self.test_false_neg = tf.keras.metrics.FalseNegatives(name='test_false_neg')
self.test_false_pos = tf.keras.metrics.FalsePositives(name='test_false_pos')
- def build_predict(self):
- _, pred = tf.nn.top_k(self.logits)
- self.pred_class = pred
-
- if TRACK_MOVING_AVERAGE:
- self.variable_averages = tf.train.ExponentialMovingAverage(0.999, self.global_step)
- self.variable_averages.apply(self.model.trainable_variables)
-
@tf.function
def train_step(self, mini_batch):
inputs = [mini_batch[0]]
--
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