Use tqdm in dcgan

1 files changed, 3 insertions, 3 deletions

diff --git a/dcgan.py b/dcgan.py
index a0a26c9..bc7e14e 100644
--- a/dcgan.py
+++ b/dcgan.py
@@ -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