1IKCU

fix [MA][diff_privacy][Doc] the tutorials of diff_privacy has problem

example/mnist_demo/lenet5_dp_model_train.py

@@ -92,15 +92,15 @@ if __name__ == "__main__":
     parser.add_argument('--data_path', type=str, default="./MNIST_unzip",
                         help='path where the dataset is saved')
     parser.add_argument('--dataset_sink_mode', type=bool, default=False, help='dataset_sink_mode is False or True')
-    parser.add_argument('--micro_batches', type=float, default=None,
+    parser.add_argument('--micro_batches', type=int, default=None,
                         help='optional, if use differential privacy, need to set micro_batches')
-    parser.add_argument('--l2_norm_bound', type=float, default=1,
+    parser.add_argument('--l2_norm_bound', type=float, default=0.1,
                         help='optional, if use differential privacy, need to set l2_norm_bound')
     parser.add_argument('--initial_noise_multiplier', type=float, default=0.001,
                         help='optional, if use differential privacy, need to set initial_noise_multiplier')
     args = parser.parse_args()
 
-    context.set_context(mode=context.PYNATIVE_MODE, device_target=args.device_target, enable_mem_reuse=False)
+    context.set_context(mode=context.PYNATIVE_MODE, device_target=args.device_target)
 
     network = LeNet5()
     net_loss = nn.SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True, reduction="mean")

example/mnist_demo/mnist_train.py

@@ -61,6 +61,5 @@ def mnist_train(epoch_size, batch_size, lr, momentum):
 
 
 if __name__ == '__main__':
-    context.set_context(mode=context.GRAPH_MODE, device_target="CPU",
-                        enable_mem_reuse=False)
+    context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
     mnist_train(10, 32, 0.01, 0.9)