simplify

download.py

@@ -6,16 +6,8 @@
 - LSUN dataset
 - MNIST dataset
 """
-
 from __future__ import print_function
-import os
-import sys
-import gzip
-import json
-import shutil
-import zipfile
-import argparse
-import subprocess
+import os, sys, gzip, json, shutil, zipfile, argparse, subprocess
 from six.moves import urllib
 
 parser = argparse.ArgumentParser(description='Download dataset for DCGAN.')
@@ -49,7 +41,7 @@ def download(url, dirpath):
  f.close()
  return filepath
 
-def download_file_from_google_drive(id, destination): 
+def download_file_from_google_drive(id, destination):
  URL = "https://docs.google.com/uc?export=download"
  session = requests.Session()
 

main.py

@@ -1,9 +1,6 @@
-import os
-import sys
+import os, sys, pprint, time
 import scipy.misc
-import pprint
 import numpy as np
-import time
 import tensorflow as tf
 import tensorlayer as tl
 from tensorlayer.layers import *
@@ -19,7 +16,6 @@
 
 Usage : see README.md
 """
-
 flags = tf.app.flags
 flags.DEFINE_integer("epoch", 25, "Epoch to train [25]")
 flags.DEFINE_float("learning_rate", 0.0002, "Learning rate of for adam [0.0002]")
@@ -172,6 +168,5 @@ def main(_):
  tl.files.save_npz(net_d.all_params, name=net_d_iter_name, sess=sess)
  print("[*] Saving checkpoints SUCCESS!")
 
-
 if __name__ == '__main__':
  tf.app.run()

model.py

@@ -3,12 +3,9 @@
 import tensorlayer as tl
 from tensorlayer.layers import *
 
-
 flags = tf.app.flags
 FLAGS = flags.FLAGS
 
-
-
 def generator_simplified_api(inputs, is_train=True, reuse=False):
  image_size = 64
  s2, s4, s8, s16 = int(image_size/2), int(image_size/4), int(image_size/8), int(image_size/16)