|
- # Copyright 2021 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- """
- Inversion attack test
- """
- import pytest
-
- import numpy as np
-
- import mindspore.context as context
-
- from mindarmour.privacy.evaluation.inversion_attack import ImageInversionAttack
-
- from tests.ut.python.utils.mock_net import Net
-
-
- context.set_context(mode=context.GRAPH_MODE)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_ascend_training
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.env_onecard
- @pytest.mark.component_mindarmour
- def test_inversion_attack():
- net = Net()
- target_features = np.random.random((2, 10)).astype(np.float32)
- inversion_attack = ImageInversionAttack(net, input_shape=(1, 32, 32), input_bound=(0, 1), loss_weights=[1, 0.2, 5])
- inversion_images = inversion_attack.generate(target_features, iters=10)
- assert target_features.shape[0] == inversion_images.shape[0]
|