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| author | nunzip <np.scarh@gmail.com> | 2019-03-13 21:37:31 +0000 |
|---|---|---|
| committer | nunzip <np.scarh@gmail.com> | 2019-03-13 21:37:31 +0000 |
| commit | 4c4a8054033f5e3bacb1913adcc56ca09267ea9f (patch) | |
| tree | 1ab29926ff552016f48bcaf98fa9e77a58aaa602 /dcgan.py | |
| parent | 8e997dd9bf12ce35d6c56a9da1c85bd8ef2d0f8c (diff) | |
| parent | 7d27d947d20ef28d3959cd358569f27bd0310111 (diff) | |
| download | e4-gan-4c4a8054033f5e3bacb1913adcc56ca09267ea9f.tar.gz e4-gan-4c4a8054033f5e3bacb1913adcc56ca09267ea9f.tar.bz2 e4-gan-4c4a8054033f5e3bacb1913adcc56ca09267ea9f.zip | |
Merge branch 'master' of skozl.com:e4-gan
Diffstat (limited to 'dcgan.py')
| -rw-r--r-- | dcgan.py | 5 |
1 files changed, 2 insertions, 3 deletions
@@ -1,4 +1,5 @@ from __future__ import print_function, division +import tensorflow.keras as keras from keras.datasets import mnist from keras.layers import Input, Dense, Reshape, Flatten, Dropout from keras.layers import BatchNormalization, Activation, ZeroPadding2D @@ -76,7 +77,7 @@ class DCGAN(): model.add(Conv2D(self.channels, kernel_size=3, padding="same")) model.add(Activation("tanh")) - #model.summary() + model.summary() noise = Input(shape=(self.latent_dim,)) img = model(noise) @@ -191,8 +192,6 @@ class DCGAN(): fig.savefig("images/mnist_%d.png" % epoch) plt.close() -''' if __name__ == '__main__': dcgan = DCGAN() dcgan.train(epochs=4000, batch_size=32, save_interval=50) -''' |