Use tqdm in cgan

1 files changed, 2 insertions, 4 deletions

diff --git a/cgan.py b/cgan.py
index 68256f3..5ab0c10 100755
--- a/cgan.py
+++ b/cgan.py
@@ -10,6 +10,7 @@ from keras.models import Sequential, Model
 from keras.optimizers import Adam
 import matplotlib.pyplot as plt
 from IPython.display import clear_output
+from tqdm import tqdm
 
 import numpy as np
 
@@ -122,7 +123,7 @@ class CGAN():
         
         xaxis = np.arange(epochs)
         loss = np.zeros((2,epochs))
-        for epoch in range(epochs):
+        for epoch in tqdm(range(epochs)):
 
             # ---------------------
             #  Train Discriminator
@@ -154,9 +155,6 @@ class CGAN():
 
             # 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:
-              clear_output() 
-              print(epoch)
             loss[0][epoch] = d_loss[0]
             loss[1][epoch] = g_loss