update

src/deepcover.py

@@ -23,9 +23,9 @@ def main():
   parser.add_argument("--outputs", dest="outputs", default="outs",
                     help="the outputput test data directory", metavar="DIR")
   parser.add_argument("--measures", dest="measures", default=['tarantula', 'zoltar', 'ochiai', 'wong-ii'],
-                    help="the measures", metavar="zoltar, tarantula ...", nargs='+')
+                    help="the SFL measures (tarantula, zoltar, ochiai, wong-ii)", metavar="" , nargs='+')
   parser.add_argument("--measure", dest="measure", default="None",
-                    help="the measure", metavar="zoltar, tarantula ...")
+                    help="the SFL measure", metavar="MEASURE")
   parser.add_argument("--mnist-dataset", dest="mnist", help="MNIST dataset", action="store_true")
   parser.add_argument("--normalized-input", dest="normalized", help="To normalize the input", action="store_true")
   parser.add_argument("--cifar10-dataset", dest="cifar10", help="CIFAR-10 dataset", action="store_true")
@@ -42,6 +42,8 @@ def main():
                     help="input cols", metavar="INT")
   parser.add_argument("--input-channels", dest="img_channels", default="3",
                     help="input channels", metavar="INT")
+  parser.add_argument("--x-verbosity", dest="x_verbosity", default="0",
+                    help="the verbosity level of explanation output", metavar="INT")
   parser.add_argument("--top-classes", dest="top_classes", default="1",
                     help="check the top-xx classifications", metavar="INT")
   parser.add_argument("--adversarial-ub", dest="adv_ub", default="1.",
@@ -126,6 +128,7 @@ def main():
   eobj.attack=args.attack
   eobj.text_only=args.text_only
   eobj.normalized=args.normalized
+  eobj.x_verbosity=int(args.x_verbosity)
   eobj.fnames=fnames
   measures = []
   if not args.measure=='None':

src/to_explain.py

@@ -1,3 +1,4 @@
+import time
 import numpy as np
 from spectra_gen import *
 from to_rank import *
@@ -27,6 +28,7 @@ def to_explain(eobj):
     reasonable_advs=False
     while ite<eobj.testgen_iter:
       print ('  #### [Start generating SFL spectra...]')
+      start=time.time()
       ite+=1
 
       passing, failing=spectra_sym_gen(eobj, x, y[-1:], adv_value=eobj.adv_value, testgen_factor=eobj.testgen_factor, testgen_size=eobj.testgen_size)
@@ -44,7 +46,8 @@ def to_explain(eobj):
 
       adv_part=num_advs*1./tot
       #print ('###### adv_percentage:', adv_part, num_advs, tot)
-      print ('  #### [SFL spectra generation DONE: passing {0} / failing {1}, total {2}]'.format(1-adv_part, adv_part, tot))
+      end=time.time()
+      print ('  #### [SFL spectra generation DONE: passing {0:.2f} / failing {1:.2f}, total {2}; time: {3:.2f} seconds]'.format(1-adv_part, adv_part, tot, end-start))
 
       if adv_part<=eobj.adv_lb:
         print ('  #### [too few failing tests: SFL explanation aborts]') 

src/utils.py

@@ -34,6 +34,7 @@ def __init__(self, model, inputs):
     self.text_only=None
     self.measures=None
     self.normalized=None
+    self.x_verbosity=None
     self.fnames=[]
 
 
@@ -113,5 +114,6 @@ def top_plot(sbfl_element, ind, di, metric='', eobj=None, bg=128, online=False,
         if y==sbfl_element.y and not found_exp: 
           save_an_image(im_o, 'explanation-found-{1}-{0}'.format(int(count/base), metric), di)
           found_exp = True
+          if eobj.x_verbosity>0: return
     pos-=1