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- # Copyright 2019 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.
- """
- different Privacy test.
- """
- import pytest
-
- from mindspore import context
- from mindarmour.diff_privacy import GaussianRandom
- from mindarmour.diff_privacy import AdaGaussianRandom
- from mindarmour.diff_privacy import MechanismsFactory
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_ascend_training
- @pytest.mark.env_onecard
- @pytest.mark.component_mindarmour
- def test_gaussian():
- context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
- shape = (3, 2, 4)
- norm_bound = 1.0
- initial_noise_multiplier = 0.1
- net = GaussianRandom(norm_bound, initial_noise_multiplier)
- res = net(shape)
- print(res)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_ascend_training
- @pytest.mark.env_onecard
- @pytest.mark.component_mindarmour
- def test_ada_gaussian():
- context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
- shape = (3, 2, 4)
- norm_bound = 1.0
- initial_noise_multiplier = 0.1
- noise_decay_rate = 0.5
- decay_policy = "Step"
- net = AdaGaussianRandom(norm_bound, initial_noise_multiplier,
- noise_decay_rate, decay_policy)
- res = net(shape)
- print(res)
-
-
- def test_factory():
- context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
- shape = (3, 2, 4)
- norm_bound = 1.0
- initial_noise_multiplier = 0.1
- noise_decay_rate = 0.5
- decay_policy = "Step"
- noise_mechanism = MechanismsFactory()
- noise_construct = noise_mechanism.create('Gaussian',
- norm_bound,
- initial_noise_multiplier)
- noise = noise_construct(shape)
- print('Gaussian noise: ', noise)
- ada_mechanism = MechanismsFactory()
- ada_noise_construct = ada_mechanism.create('AdaGaussian',
- norm_bound,
- initial_noise_multiplier,
- noise_decay_rate,
- decay_policy)
- ada_noise = ada_noise_construct(shape)
- print('ada noise: ', ada_noise)
-
-
- if __name__ == '__main__':
- # device_target can be "CPU", "GPU" or "Ascend"
- context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
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