# Source code for mindarmour.detectors.detector

# Copyright 2019 Huawei Technologies Co., Ltd
#
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#
# Unless required by applicable law or agreed to in writing, software
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
"""
Base Class of Detector.
"""
from abc import abstractmethod

from mindarmour.utils.logger import LogUtil

LOGGER = LogUtil.get_instance()
TAG = 'Detector'

[docs]class Detector: """ The abstract base class for all adversarial example detectors. """ def __init__(self): pass
[docs] @abstractmethod def fit(self, inputs, labels=None): """ Fit a threshold and refuse adversarial examples whose difference from their denoised versions are larger than the threshold. The threshold is determined by a certain false positive rate when applying to normal samples. Args: inputs (numpy.ndarray): The input samples to calculate the threshold. labels (numpy.ndarray): Labels of training data. Raises: NotImplementedError: It is an abstract method. """ msg = 'The function fit() is an abstract function in class ' \ 'Detector and should be implemented in child class.' LOGGER.error(TAG, msg) raise NotImplementedError(msg)
[docs] @abstractmethod def detect(self, inputs): """ Detect adversarial examples from input samples. Args: inputs (Union[numpy.ndarray, list, tuple]): The input samples to be detected. Raises: NotImplementedError: It is an abstract method. """ msg = 'The function detect() is an abstract function in class ' \ 'Detector and should be implemented in child class.' LOGGER.error(TAG, msg) raise NotImplementedError(msg)
[docs] @abstractmethod def detect_diff(self, inputs): """ Calculate the difference between the input samples and de-noised samples. Args: inputs (Union[numpy.ndarray, list, tuple]): The input samples to be detected. Raises: NotImplementedError: It is an abstract method. """ msg = 'The function detect_diff() is an abstract function in class ' \ 'Detector and should be implemented in child class.' LOGGER.error(TAG, msg) raise NotImplementedError(msg)
[docs] @abstractmethod def transform(self, inputs): """ Filter adversarial noises in input samples. Args: inputs (Union[numpy.ndarray, list, tuple]): The input samples to be transformed. Raises: NotImplementedError: It is an abstract method. """ msg = 'The function transform() is an abstract function in class ' \ 'Detector and should be implemented in child class.' LOGGER.error(TAG, msg) raise NotImplementedError(msg)