From 8a9892ba6083d29d016ec3124f30c00d81928e9f Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 24 Jan 2024 13:17:34 -0600
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_fraction_fcn_abi_hkm_refl.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/modules/deeplearning/cloud_fraction_fcn_abi_hkm_refl.py b/modules/deeplearning/cloud_fraction_fcn_abi_hkm_refl.py
index 65fcd44b..21ecd091 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi_hkm_refl.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi_hkm_refl.py
@@ -519,6 +519,7 @@ class SRCNN:
momentum = 0.99
num_filters = 64
+ num_filters_hkm = 8
input_2d = self.inputs[0]
input_hkm_2d = self.inputs[1]
@@ -530,12 +531,11 @@ class SRCNN:
conv_hkm = conv_hkm_b = tf.keras.layers.Conv2D(num_filters, kernel_size=KERNEL_SIZE, kernel_initializer='he_uniform', activation=activation, padding='VALID')(input_hkm_2d)
print(conv_hkm.shape)
- num_filters_hkm = 8
conv_hkm = build_conv2d_block(conv_hkm, num_filters_hkm, activation, 'Conv2D_1')
num_filters_hkm *= 2
conv_hkm = build_conv2d_block(conv_hkm, num_filters_hkm, activation, 'Conv2D_2')
- conv_b = conv_b + conv_hkm
+ conv_b = tf.keras.layers.concatenate([conv_b, conv_hkm])
print(conv_b.shape)
# if NOISE_TRAINING:
@@ -549,7 +549,7 @@ class SRCNN:
conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_3', kernel_size=KERNEL_SIZE, scale=scale)
- conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
+ #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
#conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_5', kernel_size=KERNEL_SIZE, scale=scale)
--
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