# Source code for mindarmour.detectors.detector

# 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
#
#
# 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.
"""
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)