clean up code base

configs/alp_mix_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/alp_nat_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": true,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/alp_rob_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": true,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/at_rob_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": true,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/kl_mix_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 8
   },

configs/kl_nat_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": true,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 8
   },

configs/kl_rob_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": true,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 8
   },

configs/klc_mix_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 8
   },

configs/klc_nat_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": true,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 8
   },

configs/l2_mix_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/l2_nat_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": true,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/l2_rob_wo_10.json

@@ -30,7 +30,6 @@
       "adversarial_ce": true,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/std.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

configs/std_star.json

@@ -30,7 +30,6 @@
       "adversarial_ce": false,
       "nat_ce": false,
       "data_augmentation": true,
-      "data_augmentation_reg": false,
       "group_size": 2,
       "lambda_": 1
   },

train.py

@@ -273,11 +273,6 @@ def train(config='configs/std.json',
     tf.summary.scalar('learning_rate', learning_rate, collections=['nat'])
     nat_summaries = tf.summary.merge_all('nat')
 
-    # data augmentation used if config.training.data_augmentation_reg is True
-    x_input_placeholder = tf.placeholder(tf.float32, shape=[None, 32, 32, 3])
-    flipped = tf.map_fn(lambda img: tf.image.random_flip_left_right(img),
-                        x_input_placeholder)
-
     with tf.Session() as sess:
         # initialize standard data augmentation
         if config.training.data_augmentation:
@@ -338,12 +333,7 @@ def train(config='configs/std.json',
                 id_batch_adv = np.arange(0, num_grouped_ids, 1, dtype="int32")
 
                 for _ in range(config.training.group_size-1):
-                    if config.training.data_augmentation_reg:
-                        x_batch_reg = sess.run(flipped,
-                                               feed_dict={x_input_placeholder:
-                                               x_batch[0:num_grouped_ids, :, :, :]})
-                    else:
-                        x_batch_reg = x_batch[0:num_grouped_ids, :, :, :]
+                    x_batch_reg = x_batch[0:num_grouped_ids, :, :, :]
 
                     # create rotated examples w.r.t regularizer
                     x_batch_adv, trans_adv = attack.perturb(