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| author | Vasil Zlatanov <v@skozl.com> | 2019-03-04 17:00:57 +0000 |
|---|---|---|
| committer | Vasil Zlatanov <v@skozl.com> | 2019-03-04 17:00:57 +0000 |
| commit | 802f52a2410ed20cea55e8c097b3875111a80824 (patch) | |
| tree | 2ffe7adee2842ff9c1ae1f2d998d054dff4c6fb3 /dcgan.py | |
| parent | 06228fb5afde4180c697ce244b7465b7533d3cbc (diff) | |
| download | e4-gan-802f52a2410ed20cea55e8c097b3875111a80824.tar.gz e4-gan-802f52a2410ed20cea55e8c097b3875111a80824.tar.bz2 e4-gan-802f52a2410ed20cea55e8c097b3875111a80824.zip | |
Use tqdm in dcgan
Diffstat (limited to 'dcgan.py')
| -rw-r--r-- | dcgan.py | 6 |
1 files changed, 3 insertions, 3 deletions
@@ -10,6 +10,8 @@ from keras.optimizers import Adam import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec +from tqdm import tqdm + import sys import numpy as np @@ -125,7 +127,7 @@ class DCGAN(): xaxis = np.arange(epochs) loss = np.zeros((2,epochs)) - for epoch in range(epochs): + for epoch in tqdm(range(epochs)): # --------------------- # Train Discriminator @@ -153,8 +155,6 @@ class DCGAN(): # Plot the progress #print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss)) - if epoch % 500 == 0: - print(epoch) loss[0][epoch] = d_loss[0] loss[1][epoch] = g_loss # If at save interval => save generated image samples |