From b7a276305b0aee801b24fd72afdc914819f57794 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Thu, 6 Oct 2022 14:40:11 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/srcnn_l1b_l2.py | 12 +++++++++++-
1 file changed, 11 insertions(+), 1 deletion(-)
diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 60d89f0d..bb3bfbf3 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -73,13 +73,23 @@ t = np.arange(0, 64, 0.5)
s = np.arange(0, 64, 0.5)
-def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.relu, padding='SAME', kernel_initializer='he_uniform', scale=None):
+def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.relu, padding='SAME',
+ kernel_initializer='he_uniform', scale=None,
+ do_drop_out=False, drop_rate=0.5, do_batch_norm=False):
with tf.name_scope(block_name):
skip = tf.keras.layers.Conv2D(num_filters, kernel_size=3, padding=padding, kernel_initializer=kernel_initializer, activation=activation)(conv)
skip = tf.keras.layers.Conv2D(num_filters, kernel_size=3, padding=padding, activation=None)(skip)
+
if scale is not None:
skip = tf.keras.layers.Lambda(lambda x: x * scale)(skip)
+
+ if do_drop_out:
+ skip = tf.keras.layers.Dropout(drop_rate)(skip)
+
+ if do_batch_norm:
+ skip = tf.keras.layers.BatchNormalization()(skip)
+
conv = conv + skip
print(block_name+':', conv.shape)
--
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