test.py

# -*- coding: utf-8 -*-
"""
@author: Abderrahmen Amich
@email:  aamich@umich.edu
"""

import warnings

from absl import app, flags
from mtd import test
from sys import argv, exit, stderr




if __name__ == "__main__":
    
    #### User configuration ####
                                                                                                                                                                                            
    if len(argv) < 8 or len(argv) > 18:
        print('Use: {} [data_name] [attack] [p] [n]  [Q_max] [lamda] [version] [batch_size=100] [epsilon=0.3] [ssd_training_mode=SIMCLR] [arch =resnet50] [ckpt=./models_ssd]  [data_dir = data directory path] [data-mode = for SSD {base,ssl,org}] [normalize = normalise data for SSD] [batch_number=b1]  [size = ssd_getDatasets resize param ]'.format(argv[0]), file=stderr)
        exit(1)
    elif len(argv) >= 8:
        
        flags.DEFINE_string("data", argv[1], "used dataset.")
        flags.DEFINE_string("attack", argv[2], "evasion attack.")
        flags.DEFINE_integer("n", argv[4], "Number of student models.")
        flags.DEFINE_integer("p", argv[3], "Number of adv-trained student models.")
        flags.DEFINE_integer("Q_max", argv[5], "maximum number of queries for pool renewal.")
        flags.DEFINE_float("lamda", argv[6], "Noise scale.")
        flags.DEFINE_string("version", argv[7], "Morphence version 1 or 2.")
        flags.DEFINE_integer("test_set", 5000, "test set size.")
        flags.DEFINE_integer("class_nb", 10, "Number of labels.")
        if len(argv) == 8:
            flags.DEFINE_integer("batch", 32, "batch size.")
            flags.DEFINE_float("eps", 0.3, "Total epsilon for attacks.")
            flags.DEFINE_string("models_batch", 'b1', "the starting batch of student models.")
            
        elif len(argv) == 9:
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", 0.3, "Total epsilon for attacks.")
            flags.DEFINE_string("models_batch", 'b1', "the starting batch of student models.")
            
        elif len(argv) == 10:
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("models_batch", 'b1', "the starting batch of student models.")
            
        elif len(argv) == 11:
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("training_mode",argv[10],"pretrained model for ssd, traingin type")
        elif len(argv)==12 :
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("training_mode",argv[10],"pretrained model for ssd, traingin type")
            flags.DEFINE_string("models_batch", argv[11], "the starting batch of student models.")
        elif len(argv)==13 :
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("training_mode",argv[10],"pretrained model for ssd, traingin type")
            flags.DEFINE_string("arch",argv[11],"pretrained model for ssd, architeture")
            flags.DEFINE_string("models_batch", argv[12], "the starting batch of student models.")
        elif len(argv)==14 :
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("training_mode",argv[10],"pretrained model for ssd, traingin type")
            flags.DEFINE_string("arch",argv[11],"pretrained model for ssd, architeture")
            flags.DEFINE_string("ckpt",argv[12],"checkpoint to pretraiend model")
            flags.DEFINE_string("models_batch", argv[13], "the starting batch of student models.")
        elif len(argv)==18 :
            flags.DEFINE_integer("batch",argv[8] , "batch size.")
            flags.DEFINE_float("eps", argv[9], "Total epsilon for attacks.")
            flags.DEFINE_string("training_mode",argv[10],"pretrained model for ssd, traingin type")
            flags.DEFINE_string("arch",argv[11],"pretrained model for ssd, architeture")
            flags.DEFINE_string("ckpt",argv[12],"checkpoint to pretraiend model")
            flags.DEFINE_string("data_dir",argv[13],"directory to data")
            flags.DEFINE_string("data_mode",argv[14]," data mode = {org,vase,ssl}")
            flags.DEFINE_boolean("normalize",argv[15]," Normalize inpur dara")
            flags.DEFINE_string("models_batch", argv[16], "the starting batch of student models.")
            flags.DEFINE_integer("size",argv[17] , "")
            



    warnings.filterwarnings('ignore', '.*do not.*', )
    app.run(test)