diff --git a/main.py b/main.py
index b2ea7c451..b82e7d766 100644
--- a/main.py
+++ b/main.py
@@ -9,34 +9,34 @@
 import tensorflow as tf
 
 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]")
-flags.DEFINE_float("beta1", 0.5, "Momentum term of adam [0.5]")
-flags.DEFINE_float("train_size", np.inf, "The size of train images [np.inf]")
-flags.DEFINE_integer("batch_size", 64, "The size of batch images [64]")
-flags.DEFINE_integer("input_height", 108, "The size of image to use (will be center cropped). [108]")
-flags.DEFINE_integer("input_width", None, "The size of image to use (will be center cropped). If None, same value as input_height [None]")
-flags.DEFINE_integer("output_height", 64, "The size of the output images to produce [64]")
-flags.DEFINE_integer("output_width", None, "The size of the output images to produce. If None, same value as output_height [None]")
-flags.DEFINE_string("dataset", "celebA", "The name of dataset [celebA, mnist, lsun]")
-flags.DEFINE_string("input_fname_pattern", "*.jpg", "Glob pattern of filename of input images [*]")
-flags.DEFINE_string("data_dir", "./data", "path to datasets [e.g. $HOME/data]")
-flags.DEFINE_string("out_dir", "./out", "Root directory for outputs [e.g. $HOME/out]")
-flags.DEFINE_string("out_name", "", "Folder (under out_root_dir) for all outputs. Generated automatically if left blank []")
-flags.DEFINE_string("checkpoint_dir", "checkpoint", "Folder (under out_root_dir/out_name) to save checkpoints [checkpoint]")
-flags.DEFINE_string("sample_dir", "samples", "Folder (under out_root_dir/out_name) to save samples [samples]")
-flags.DEFINE_boolean("train", False, "True for training, False for testing [False]")
-flags.DEFINE_boolean("crop", False, "True for training, False for testing [False]")
-flags.DEFINE_boolean("visualize", False, "True for visualizing, False for nothing [False]")
-flags.DEFINE_boolean("export", False, "True for exporting with new batch size")
-flags.DEFINE_boolean("freeze", False, "True for exporting with new batch size")
-flags.DEFINE_integer("max_to_keep", 1, "maximum number of checkpoints to keep")
-flags.DEFINE_integer("sample_freq", 200, "sample every this many iterations")
-flags.DEFINE_integer("ckpt_freq", 200, "save checkpoint every this many iterations")
-flags.DEFINE_integer("z_dim", 100, "dimensions of z")
-flags.DEFINE_string("z_dist", "uniform_signed", "'normal01' or 'uniform_unsigned' or uniform_signed")
-flags.DEFINE_boolean("G_img_sum", False, "Save generator image summaries in log")
-#flags.DEFINE_integer("generate_test_images", 100, "Number of images to generate during test. [100]")
+flags.DEFINE_integer  ("epoch", 25, "Epoch to train [25]")
+flags.DEFINE_float    ("learning_rate", 0.0002, "Learning rate of for adam [0.0002]")
+flags.DEFINE_float    ("beta1", 0.5, "Momentum term of adam [0.5]")
+flags.DEFINE_float    ("train_size", np.inf, "The size of train images [np.inf]")
+flags.DEFINE_integer  ("batch_size", 64, "The size of batch images [64]")
+flags.DEFINE_integer  ("input_height", 108, "The size of image to use (will be center cropped). [108]")
+flags.DEFINE_integer  ("input_width", None, "The size of image to use (will be center cropped). If None, same value as input_height [None]")
+flags.DEFINE_integer  ("output_height", 64, "The size of the output images to produce [64]")
+flags.DEFINE_integer  ("output_width", None, "The size of the output images to produce. If None, same value as output_height [None]")
+flags.DEFINE_string   ("dataset", "celebA", "The name of dataset [celebA, mnist, lsun]")
+flags.DEFINE_string   ("input_fname_pattern", "*.jpg", "Glob pattern of filename of input images [*]")
+flags.DEFINE_string   ("data_dir", "./data", "path to datasets [e.g. $HOME/data]")
+flags.DEFINE_string   ("out_dir", "./out", "Root directory for outputs [e.g. $HOME/out]")
+flags.DEFINE_string   ("out_name", "", "Folder (under out_root_dir) for all outputs. Generated automatically if left blank []")
+flags.DEFINE_string   ("checkpoint_dir", "checkpoint", "Folder (under out_root_dir/out_name) to save checkpoints [checkpoint]")
+flags.DEFINE_string   ("sample_dir", "samples", "Folder (under out_root_dir/out_name) to save samples [samples]")
+flags.DEFINE_boolean  ("train", False, "True for training, False for testing [False]")
+flags.DEFINE_boolean  ("crop", False, "True for training, False for testing [False]")
+flags.DEFINE_boolean  ("visualize", False, "True for visualizing, False for nothing [False]")
+flags.DEFINE_boolean  ("export", False, "True for exporting with new batch size")
+flags.DEFINE_boolean  ("freeze", False, "True for exporting with new batch size")
+flags.DEFINE_integer  ("max_to_keep", 1, "maximum number of checkpoints to keep")
+flags.DEFINE_integer  ("sample_freq", 200, "sample every this many iterations")
+flags.DEFINE_integer  ("ckpt_freq", 200, "save checkpoint every this many iterations")
+flags.DEFINE_integer  ("z_dim", 100, "dimensions of z")
+flags.DEFINE_string   ("z_dist", "uniform_signed", "'normal01' or 'uniform_unsigned' or uniform_signed")
+flags.DEFINE_boolean  ("G_img_sum", False, "Save generator image summaries in log")
+#flags.DEFINE_integer ("generate_test_images", 100, "Number of images to generate during test. [100]")
 FLAGS = flags.FLAGS
 
 def main(_):