dataset_logics = node_to_logics[node_name]
sparse_thred_filter, sparse_nonzero_filter = logic_plot_hist_save(
dataset_logics,
filter_count,
)
thred_filter_all[node_name] = sparse_thred_filter
nonzero_filter_all[node_name] = sparse_nonzero_filter
print(f"all")
print_logic_per_class(thred_filter_all)
def count_logics_exp():
count_logics()
if __name__ == "__main__":
mode.debug()
# mode.local()
# ray_init("gpu")
ray_init(log_to_driver=False,
# num_cpus = 10,
)
tf.set_random_seed(3)
np.random.seed(3)
random.seed(3)
count_logics_exp()
def random_targeted(attack_fn, class_start: int, class_end: int):
return partial(
attack_fn,
criterion=TargetClass(
target_class=random.randint(class_start, class_end)),
)
if __name__ == "__main__":
# mode.debug()
mode.distributed()
# mode.local()
# ray_init("gpu")
ray_init()
threshold = 0.5
# threshold = 1
# threshold = 0.8
attacks = {
"FGSM": [FGSM],
"BIM": [IterativeGradientSignAttack],
"JSMA": [SaliencyMapAttack],
"DeepFool": [DeepFoolAttack],
# "DeepFool_full": [DeepFoolAttack, dict(subsample=None)],
"CWL2": [CarliniL2],
}
label = "early"
# label = "best_in_10"
# label = "worst_in_10"
data_format="channels_first",
num_gpus = num_gpus,
cache=False
)
generate_examples(
example_fn=example_fn,
class_ids=class_ids,
image_ids=image_ids,
attack_name=attack_name,
attack_fn=attack_fn,
generate_adversarial_fn=generate_adversarial_fn,
transforms = transforms,
transform_name = transform_name,
**arch_args,
)
if __name__ == "__main__":
mode.debug()
# mode.local()
ray_init(
log_to_driver=False
)
tf.set_random_seed(3)
np.random.seed(3)
random.seed(3)
generate_mnist_examples()
global debug
parser = argparse.ArgumentParser(description='Save traces')
# Required arguments
parser.add_argument('--debug', action='store_true', default=False)
args = parser.parse_args()
debug = args.debug
if debug:
mode.debug()
train_images_per_class = 10
test_images_per_class = 5
chunksize = 1
else:
mode.local()
# ray_init("gpu")
ray_init(
log_to_driver=False,
num_cpus=1,
# num_gpus=0,
)
compute_logics(
logic_name="unary",
logic_fn=mask_to_logic_fn,
trace_key=TraceKey.WEIGHT
)
