From 511bd42587edd5ea15dc2e7a88d65d8a3b31df8c Mon Sep 17 00:00:00 2001
From: Felix Kleinert <f.kleinert@fz-juelich.de>
Date: Tue, 9 Nov 2021 08:25:18 +0100
Subject: [PATCH] update UNet to TF2
---
mlair/model_modules/model_class.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/mlair/model_modules/model_class.py b/mlair/model_modules/model_class.py
index 0604c777..4b507db3 100644
--- a/mlair/model_modules/model_class.py
+++ b/mlair/model_modules/model_class.py
@@ -660,16 +660,16 @@ class MyUnet(AbstractModelClass):
p3 = keras.layers.MaxPooling2D(self.pool_size)(c3)
### own LSTM Block ###
- ls1 = keras.layers.Reshape((p3.shape[1].value, p3.shape[-1].value))(p3)
+ ls1 = keras.layers.Reshape((p3.shape[1], p3.shape[-1]))(p3)
ls1 = keras.layers.LSTM(64*2, return_sequences=True)(ls1)
ls1 = keras.layers.LSTM(64*2, return_sequences=True)(ls1)
- c4 = keras.layers.Reshape((p3.shape[1].value, 1, -1))(ls1)
+ c4 = keras.layers.Reshape((p3.shape[1], 1, -1))(ls1)
### own 2nd LSTM Block ###
- ls2 = keras.layers.Reshape((c3.shape[1].value, c3.shape[-1].value))(c3)
+ ls2 = keras.layers.Reshape((c3.shape[1], c3.shape[-1]))(c3)
ls2 = keras.layers.LSTM(64 * 2, return_sequences=True)(ls2)
ls2 = keras.layers.LSTM(64 * 2, return_sequences=True)(ls2)
- c4_2 = keras.layers.Reshape((c3.shape[1].value, 1, -1))(ls2)
+ c4_2 = keras.layers.Reshape((c3.shape[1], 1, -1))(ls2)
# c4 = Padding2D("SymPad2D")(padding=pad_size)(p3)
# c4 = keras.layers.Conv2D(128, self.kernel_size, activation=self.activation, kernel_initializer=self.kernel_initializer)(c4)
--
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