# points = res + points # values = [v] * len(res) + values print 'Added ', (x, v), 'to points' def add_mismatched(x): res = [(x, randint(0, LAST), randint(0, LAST))] tmp = x for i in xrange(8): point = (x, tmp % 256, 0) res.append(point) tmp /= 256 return res if __name__ == "__main__": random.seed(0) Config.TRAINING = True # p = proxy.make_train(8, ["tfold"]) # p = proxy.make_train(15, ["tfold"]) p = proxy.make_train(12, ["tfold"]) inc_solve(p)
if status == "error": print 'Error!, proceeding to another guess' h_gen.next() if status == "mismatch": x, y, my = map(from_hex, data["values"]) xs.append(x) ys.append(y) h_current, delta = find_first_good2(h_gen, xs, ys) index += delta if __name__ == "__main__": seed(0) Config.TRAINING = True p = proxy.make_train(42) solve2(p) exit() OPS = ["not", "and", "or", "xor", "shr1", "shr4", "shr16", "plus", "shl1", "if0"] OPS = ["and","if0","or","plus","shr16","shr4"] AR = tuple([randint(0, LAST) for i in xrange(1)]) g = gen_tree_values(12, OPS, AR, tuple(map(f, AR))) print len(g[-1]), tuple(map(f, AR)) in g[-1] h = find_all_trees_with_values(g, AR, tuple(map(f, AR)), OPS) for a in h: print a.dump()#, map(lambda x: a.getx(x), AR) print len(h)
if status == "error": print 'Error!, proceeding to another guess' h_gen.next() if status == "mismatch": x, y, my = map(from_hex, data["values"]) xs.append(x) ys.append(y) h_current, delta = find_first_good2(h_gen, xs, ys) index += delta if __name__ == "__main__": seed(0) Config.TRAINING = True p = proxy.make_train(15) solve2(p) exit() OPS = ["not", "and", "or", "xor", "shr1", "shr4", "shr16", "plus", "shl1", "if0"] OPS = ["and","if0","or","plus","shr16","shr4"] AR = tuple([randint(0, LAST) for i in xrange(1)]) g = gen_tree_values(12, OPS, AR, tuple(map(f, AR))) print len(g[-1]), tuple(map(f, AR)) in g[-1] h = find_all_trees_with_values(g, AR, tuple(map(f, AR)), OPS) for a in h: print a.dump()#, map(lambda x: a.getx(x), AR) print len(h)
h_gen.next() if status == "mismatch": x, y, my = map(from_hex, data["values"]) xs.append(x) ys.append(y) h_current, delta = find_first_good2(h_gen, xs, ys) if h_current == None: print ":(" return index += delta if __name__ == "__main__": seed(0) Config.TRAINING = True p = proxy.make_train(137) solve2(p) exit() OPS = ["not", "and", "or", "xor", "shr1", "shr4", "shr16", "plus", "shl1", "if0"] OPS = ["and","if0","or","plus","shr16","shr4"] AR = tuple([randint(0, LAST) for i in xrange(1)]) g = gen_tree_values(12, OPS, AR, tuple(map(f, AR))) print len(g[-1]), tuple(map(f, AR)) in g[-1] h = find_all_trees_with_values(g, AR, tuple(map(f, AR)), OPS) for a in h: print a.dump()#, map(lambda x: a.getx(x), AR) print len(h)