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Removed first deconv layer to achieve symmetry in convolutions

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-04-14 09:36:10 +02:00
parent 1764e10da4
commit c8e49bd0da
1 changed files with 2 additions and 7 deletions
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9
src/twomartens/masterthesis/aae/model.py
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@ -80,16 +80,13 @@ class Decoder(keras.Model):
def __init__(self, channels: int, zsize: int) -> None:
super().__init__(name='decoder')
weight_init = keras.initializers.RandomNormal(mean=0, stddev=0.02)
self.deconv1 = keras.layers.Conv2D(filters=zsize, kernel_size=7, strides=1, name='deconv1',
self.deconv1 = keras.layers.Conv2D(filters=zsize * 2, kernel_size=7, strides=1, name='deconv1',
padding='same', kernel_initializer=weight_init)
self.deconv1_a = keras.layers.ReLU()
self.deconv2 = keras.layers.Conv2D(filters=zsize * 2, kernel_size=7, strides=1, name='deconv2',
padding='same', kernel_initializer=weight_init)
self.deconv2_a = keras.layers.ReLU()
self.deconv3 = keras.layers.Conv2D(filters=zsize * 2, kernel_size=7, strides=1, name='deconv3',
padding='same', kernel_initializer=weight_init)
self.deconv3_a = keras.layers.ReLU()
self.deconv4 = keras.layers.Conv2D(filters=channels, kernel_size=7, strides=1, name='deconv4',
self.deconv3 = keras.layers.Conv2D(filters=channels, kernel_size=7, strides=1, name='deconv3',
padding='same', kernel_initializer=weight_init)
def call(self, inputs: tf.Tensor, **kwargs) -> tf.Tensor:
@ -99,8 +96,6 @@ class Decoder(keras.Model):
result = self.deconv2(result)
result = self.deconv2_a(result)
result = self.deconv3(result)
result = self.deconv3_a(result)
result = self.deconv4(result)
result = k.sigmoid(result)
return result