fix issue.

mindarmour/diff_privacy/mechanisms/mechanisms.py

@@ -26,6 +26,7 @@ from mindspore.common import dtype as mstype
 from mindarmour.utils._check_param import check_param_type
 from mindarmour.utils._check_param import check_value_positive
 from mindarmour.utils._check_param import check_param_in_range
+from mindarmour.utils._check_param import check_value_non_negative
 from mindarmour.utils.logger import LogUtil
 
 LOGGER = LogUtil.get_instance()
@@ -204,8 +205,10 @@ class NoiseGaussianRandom(_Mechanisms):
 
     def __init__(self, norm_bound=1.0, initial_noise_multiplier=1.0, seed=0, decay_policy=None):
         super(NoiseGaussianRandom, self).__init__()
+        norm_bound = check_param_type('norm_bound', norm_bound, float)
         self._norm_bound = check_value_positive('norm_bound', norm_bound)
         self._norm_bound = Tensor(norm_bound, mstype.float32)
+        initial_noise_multiplier = check_param_type('initial_noise_multiplier', initial_noise_multiplier, float)
         self._initial_noise_multiplier = check_value_positive('initial_noise_multiplier',
                                                               initial_noise_multiplier)
         self._initial_noise_multiplier = Tensor(initial_noise_multiplier, mstype.float32)
@@ -213,7 +216,8 @@ class NoiseGaussianRandom(_Mechanisms):
         if decay_policy is not None:
             raise ValueError('decay_policy must be None in GaussianRandom class, but got {}.'.format(decay_policy))
         self._decay_policy = decay_policy
-        self._seed = seed
+        seed = check_param_type('seed', seed, int)
+        self._seed = check_value_non_negative('seed', seed)
 
     def construct(self, gradients):
         """
@@ -400,7 +404,8 @@ class AdaClippingWithGaussianRandom(Cell):
         self._sub = P.Sub()
         self._mul = P.Mul()
         self._exp = P.Exp()
-        self._seed = seed
+        seed = check_param_type('seed', seed, int)
+        self._seed = check_value_non_negative('seed', seed)
 
     def construct(self, empirical_fraction, norm_bound):
         """

mindarmour/diff_privacy/train/model.py

@@ -50,8 +50,7 @@ from mindspore import ParameterTuple
 from mindarmour.utils.logger import LogUtil
 from mindarmour.diff_privacy.mechanisms.mechanisms import \
     _MechanismsParamsUpdater
-from mindarmour.utils._check_param import check_param_type
-from mindarmour.utils._check_param import check_value_positive
+from mindarmour.utils._check_param import check_value_positive, check_param_type
 from mindarmour.utils._check_param import check_int_positive
 
 LOGGER = LogUtil.get_instance()