is_trained_with_pytorch = file_extension == ".pyt" is_saved_tf_model = file_extension == ".meta" is_pb_file = file_extension == ".pb" is_tensorflow = file_extension == ".tf" is_onnx = file_extension == ".onnx" assert is_trained_with_pytorch or is_saved_tf_model or is_pb_file or is_tensorflow or is_onnx, "file extension not supported" epsilon = config.epsilon assert (epsilon >= 0) and (epsilon <= 1), "epsilon can only be between 0 and 1" zonotope_file = config.zonotope zonotope = None zonotope_bool = (zonotope_file != None) if zonotope_bool: zonotope = read_zonotope(zonotope_file) domain = config.domain if zonotope_bool: assert domain in ['deepzono', 'refinezono' ], "domain name can be either deepzono or refinezono" elif not config.geometric: assert domain in [ 'deepzono', 'refinezono', 'deeppoly', 'refinepoly' ], "domain name can be either deepzono, refinezono, deeppoly or refinepoly" dataset = config.dataset if zonotope_bool == False: assert dataset in [
is_saved_tf_model = False if(file_extension==".pyt"): is_trained_with_pytorch = True elif(file_extension==".meta"): is_saved_tf_model = True elif(file_extension!= ".tf"): print("file extension not supported") exit(1) epsilon = args.epsilon assert (epsilon >= 0) and (epsilon <= 1), "epsilon can only be between 0 and 1" zonotope_bool = args.zonotope if zonotope_bool: zonotope = read_zonotope(filename + ZONOTOPE_EXTENSION) domain = args.domain assert domain in ['deepzono', 'refinezono', 'deeppoly', 'refinepoly'], "domain name can be either deepzono, refinezono, deeppoly or refinepoly" dataset = args.dataset if((dataset!='mnist') and (dataset!='cifar10') and (dataset!='acasxu')): print("only mnist, cifar10, and acasxu datasets are supported") exit(1) specnumber = 9 if(dataset=='acasxu' and (specnumber!=9)): print("currently we only support property 9 for acasxu") exit(1)