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)
