fix problems in review comments

mindarmour/fuzz_testing/fuzzing.py

@@ -254,6 +254,10 @@ class Fuzzer:
             raise ValueError(msg)
         for seed in initial_seeds:
             check_param_type('seed', seed, list)
+            if len(seed) != 2:
+                msg = 'seed in initial seeds must have two element image and ' \
+                      'label, but got {} element.'.format(len(seed))
+                raise ValueError(msg)
             check_numpy_param('seed[0]', seed[0])
             check_numpy_param('seed[1]', seed[1])
             seed.append(0)
@@ -321,16 +325,16 @@ class Fuzzer:
         """Mutate a seed using strategies random selected from mutate_config."""
         mutate_samples = []
         mutate_strategies = []
-        only_pixel_trans = seed[2]
         for _ in range(mutate_num_per_seed):
-            strage = choice(mutate_config)
+            only_pixel_trans = seed[2]
+            strategy = choice(mutate_config)
             # Choose a pixel value based transform method
             if only_pixel_trans:
-                while strage['method'] not in self._pixel_value_trans_list:
-                    strage = choice(mutate_config)
-            transform = mutates[strage['method']]
-            params = strage['params']
-            method = strage['method']
+                while strategy['method'] not in self._pixel_value_trans_list:
+                    strategy = choice(mutate_config)
+            transform = mutates[strategy['method']]
+            params = strategy['params']
+            method = strategy['method']
             selected_param = {}
             for p in params:
                 selected_param[p] = choice(params[p])
@@ -367,10 +371,10 @@ class Fuzzer:
         for config in mutate_config:
             check_param_type("config", config, dict)
             if set(config.keys()) != {'method', 'params'}:
-                msg = "Config must contain 'method' and 'params', but got {}." \
-                    .format(set(config.keys()))
+                msg = "The key of each config must be in ('method', 'params'), " \
+                      "but got {}.".format(set(config.keys()))
                 LOGGER.error(TAG, msg)
-                raise TypeError(msg)
+                raise KeyError(msg)
 
             method = config['method']
             params = config['params']
@@ -380,7 +384,7 @@ class Fuzzer:
                 msg = "Config methods must be in {}, but got {}." \
                     .format(self._strategies.keys(), method)
                 LOGGER.error(TAG, msg)
-                raise TypeError(msg)
+                raise ValueError(msg)
 
             if config['method'] in self._pixel_value_trans_list:
                 has_pixel_trans = True
@@ -415,7 +419,9 @@ class Fuzzer:
                 if param_name == 'bounds':
                     bounds = check_param_multi_types('bounds', param_value, [tuple])
                     if len(bounds) != 2:
-                        msg = 'bounds must be format (lower_bound, upper_bound)'
+                        msg = 'The format of bounds must be format (lower_bound, upper_bound),' \
+                              'but got its length as{}'.format(len(bounds))
+                        raise ValueError(msg)
                     for bound_value in bounds:
                         _ = check_param_multi_types('bound', bound_value,
                                                     [int, float])
@@ -458,7 +464,7 @@ class Fuzzer:
         Args:
             fuzz_samples ([numpy.ndarray, list]): Generated fuzz_testing samples
                 according to seeds.
-            true_labels ([numpy.ndarray, list]): Ground Truth labels of seeds.
+            true_labels ([numpy.ndarray, list]): Ground truth labels of seeds.
             fuzz_preds ([numpy.ndarray, list]): Predictions of generated fuzz samples.
             fuzz_strategies ([numpy.ndarray, list]): Mutate strategies of fuzz samples.
             metrics (Union[list, tuple, str]): evaluation metrics.

mindarmour/fuzz_testing/image_transform.py

@@ -23,7 +23,7 @@ from mindarmour.utils._check_param import check_param_multi_types
 from mindarmour.utils.logger import LogUtil
 
 LOGGER = LogUtil.get_instance()
-TAG = 'ModelCoverageMetrics'
+TAG = 'Image Transformation'
 
 
 def chw_to_hwc(img):
@@ -38,7 +38,7 @@ def chw_to_hwc(img):
     """
     if is_numpy(img):
         return img.transpose(1, 2, 0).copy()
-    raise TypeError('img should be Numpy array. Got {}'.format(type(img)))
+    raise TypeError('img should be numpy.ndarray. Got {}'.format(type(img)))
 
 
 def is_hwc(img):
@@ -56,7 +56,7 @@ def is_hwc(img):
         if img_shape[2] == 3 and img_shape[1] > 3 and img_shape[0] > 3:
             return True
         return False
-    raise TypeError('img should be Numpy array. Got {}'.format(type(img)))
+    raise TypeError('img should be numpy.ndarray. Got {}'.format(type(img)))
 
 
 def is_chw(img):
@@ -74,7 +74,7 @@ def is_chw(img):
         if img_shape[0] == 3 and img_shape[1] > 3 and img_shape[2] > 3:
             return True
         return False
-    raise TypeError('img should be Numpy array. Got {}'.format(type(img)))
+    raise TypeError('img should be numpy.ndarray. Got {}'.format(type(img)))
 
 
 def is_rgb(img):
@@ -92,7 +92,7 @@ def is_rgb(img):
         if len(np.shape(img)) == 3 and (img_shape[0] == 3 or img_shape[2] == 3):
             return True
         return False
-    raise TypeError('img should be Numpy array. Got {}'.format(type(img)))
+    raise TypeError('img should be numpy.ndarray. Got {}'.format(type(img)))
 
 
 def is_normalized(img):
@@ -167,8 +167,8 @@ class Contrast(ImageTransform):
     Contrast of an image.
 
     Args:
-        factor ([float, int]): Control the contrast of an image. If 1.0 gives the
-            original image. If 0 gives a gray image. Default: 1.
+        factor (Union[float, int]): Control the contrast of an image. If 1.0,
+            gives the original image. If 0, gives a gray image. Default: 1.
     """
 
     def __init__(self, factor=1):
@@ -180,8 +180,8 @@ class Contrast(ImageTransform):
         Set contrast parameters.
 
         Args:
-            factor ([float, int]): Control the contrast of an image. If 1.0 gives
-                the original image. If 0 gives a gray image. Default: 1.
+            factor (Union[float, int]): Control the contrast of an image. If 1.0
+                gives the original image. If 0 gives a gray image. Default: 1.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
         if auto_param:
@@ -214,8 +214,8 @@ class Brightness(ImageTransform):
     Brightness of an image.
 
     Args:
-        factor ([float, int]): Control the brightness of an image. If 1.0 gives
-            the original image. If 0 gives a black image. Default: 1.
+        factor (Union[float, int]): Control the brightness of an image. If 1.0
+            gives the original image. If 0 gives a black image. Default: 1.
     """
 
     def __init__(self, factor=1):
@@ -227,7 +227,7 @@ class Brightness(ImageTransform):
         Set brightness parameters.
 
         Args:
-            factor ([float, int]): Control the brightness of an image. If 1
+            factor (Union[float, int]): Control the brightness of an image. If 1
                 gives the original image. If 0 gives a black image. Default: 1.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
@@ -260,7 +260,7 @@ class Blur(ImageTransform):
     Blurs the image using Gaussian blur filter.
 
     Args:
-        radius([float, int]): Blur radius, 0 means no blur. Default: 0.
+        radius(Union[float, int]): Blur radius, 0 means no blur. Default: 0.
     """
 
     def __init__(self, radius=0):
@@ -272,7 +272,7 @@ class Blur(ImageTransform):
         Set blur parameters.
 
         Args:
-            radius ([float, int]): Blur radius, 0 means no blur. Default: 0.
+            radius (Union[float, int]): Blur radius, 0 means no blur. Default: 0.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
         if auto_param:
@@ -316,8 +316,8 @@ class Noise(ImageTransform):
         Set noise parameters.
 
         Args:
-            factor ([float, int]): 1 - factor is the ratio of pixels to add noise.
-                If 0 gives the original image. Default 0.
+            factor (Union[float, int]): 1 - factor is the ratio of pixels to
+                add noise. If 0 gives the original image. Default 0.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
         if auto_param:
@@ -407,8 +407,10 @@ class Scale(ImageTransform):
     Scale an image in the middle.
 
     Args:
-        factor_x ([float, int]): Rescale in X-direction, x=factor_x*x. Default: 1.
-        factor_y ([float, int]): Rescale in Y-direction, y=factor_y*y. Default: 1.
+        factor_x (Union[float, int]): Rescale in X-direction, x=factor_x*x.
+            Default: 1.
+        factor_y (Union[float, int]): Rescale in Y-direction, y=factor_y*y.
+            Default: 1.
     """
 
     def __init__(self, factor_x=1, factor_y=1):
@@ -421,9 +423,9 @@ class Scale(ImageTransform):
         Set scale parameters.
 
         Args:
-            factor_x ([float, int]): Rescale in X-direction, x=factor_x*x.
+            factor_x (Union[float, int]): Rescale in X-direction, x=factor_x*x.
                 Default: 1.
-            factor_y ([float, int]): Rescale in Y-direction, y=factor_y*y.
+            factor_y (Union[float, int]): Rescale in Y-direction, y=factor_y*y.
                 Default: 1.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
@@ -469,8 +471,10 @@ class Shear(ImageTransform):
     the sheared image will be rescaled to fit original size.
 
     Args:
-        factor_x ([float, int]): Shear factor of horizontal direction. Default: 0.
-        factor_y ([float, int]): Shear factor of vertical direction. Default: 0.
+        factor_x (Union[float, int]): Shear factor of horizontal direction.
+            Default: 0.
+        factor_y (Union[float, int]): Shear factor of vertical direction.
+            Default: 0.
 
     """
 
@@ -483,9 +487,9 @@ class Shear(ImageTransform):
         Set shear parameters.
 
         Args:
-            factor_x ([float, int]): Shear factor of horizontal direction.
+            factor_x (Union[float, int]): Shear factor of horizontal direction.
                 Default: 0.
-            factor_y ([float, int]): Shear factor of vertical direction.
+            factor_y (Union[float, int]): Shear factor of vertical direction.
                 Default: 0.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
@@ -549,7 +553,7 @@ class Rotate(ImageTransform):
     Rotate an image of degrees counter clockwise around its center.
 
     Args:
-        angle([float, int]): Degrees counter clockwise. Default: 0.
+        angle(Union[float, int]): Degrees counter clockwise. Default: 0.
     """
 
     def __init__(self, angle=0):
@@ -561,7 +565,7 @@ class Rotate(ImageTransform):
         Set rotate parameters.
 
         Args:
-            angle([float, int]): Degrees counter clockwise. Default: 0.
+            angle(Union[float, int]): Degrees counter clockwise. Default: 0.
             auto_param (bool): True if auto generate parameters. Default: False.
         """
         if auto_param:

mindarmour/privacy/evaluation/membership_inference.py

@@ -148,10 +148,10 @@ class MembershipInference:
                 The support methods are knn, lr, mlp and rf, and the params of each method
                 must within the range of changeable parameters. Tips of params implement
                 can be found below:
-                `KNN<https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html>`_,
-                `LR<https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html>`_,
-                `RF<https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html>`_,
-                `MLP<https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html>`_.
+                `KNN <https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html>`_,
+                `LR <https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html>`_,
+                `RF <https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html>`_,
+                `MLP <https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html>`_.
 
         Raises:
             KeyError: If any config in attack_config doesn't have keys {"method", "params"}.