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Fixed dimensions of input transform

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-04-18 12:17:01 +02:00
parent 71623db905
commit 2140b13857
1 changed files with 1 additions and 1 deletions
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src/twomartens/masterthesis/aae/model.py
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@ -90,7 +90,7 @@ class Decoder(keras.Model):
weight_init = keras.initializers.RandomNormal(mean=0, stddev=0.02) weight_init = keras.initializers.RandomNormal(mean=0, stddev=0.02)
# calculate dimension of last conv layer in encoder # calculate dimension of last conv layer in encoder
conv_image_size = image_size / (2 ** 3) conv_image_size = image_size / (2 ** 3)
dimensions = zsize * conv_image_size dimensions = zsize * conv_image_size * conv_image_size
self.conv_shape = (-1, conv_image_size, conv_image_size, zsize) self.conv_shape = (-1, conv_image_size, conv_image_size, zsize)
self.transform = keras.layers.Dense(units=dimensions, name='input_transform') self.transform = keras.layers.Dense(units=dimensions, name='input_transform')
self.deconv1 = keras.layers.Conv2DTranspose(filters=zsize, kernel_size=3, strides=1, name='deconv1', self.deconv1 = keras.layers.Conv2DTranspose(filters=zsize, kernel_size=3, strides=1, name='deconv1',