diff --git a/mindspore/explainer/_image_classification_runner.py b/mindspore/explainer/_image_classification_runner.py
index 704362145f8..c3121006f8f 100644
--- a/mindspore/explainer/_image_classification_runner.py
+++ b/mindspore/explainer/_image_classification_runner.py
@@ -259,7 +259,9 @@ class ImageClassificationRunner(_Verifier):
         >>> from mindspore.explainer.benchmark import Faithfulness
         >>> from mindspore.nn import Softmax
         >>> from mindspore.train.serialization import load_checkpoint, load_param_into_net
+        >>> from mindspore import context
         >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of AlexNet is shown in model_zoo.official.cv.alexnet.src.alexnet.py
         >>> net = AlexNet(10)
         >>> # Load the checkpoint
diff --git a/mindspore/explainer/benchmark/_attribution/class_sensitivity.py b/mindspore/explainer/benchmark/_attribution/class_sensitivity.py
index ed6df564901..698006b6e35 100644
--- a/mindspore/explainer/benchmark/_attribution/class_sensitivity.py
+++ b/mindspore/explainer/benchmark/_attribution/class_sensitivity.py
@@ -55,7 +55,9 @@ class ClassSensitivity(LabelAgnosticMetric):
             >>> import mindspore as ms
             >>> from mindspore.explainer.benchmark import ClassSensitivity
             >>> from mindspore.explainer.explanation import Gradient
+            >>> from mindspore import context
             >>>
+            >>> context.set_context(mode=context.PYNATIVE_MODE)
             >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
             >>> net = LeNet5(10, num_channel=3)
             >>> # prepare your explainer to be evaluated, e.g., Gradient.
diff --git a/mindspore/explainer/benchmark/_attribution/faithfulness.py b/mindspore/explainer/benchmark/_attribution/faithfulness.py
index 70db586dec0..5e640df286e 100644
--- a/mindspore/explainer/benchmark/_attribution/faithfulness.py
+++ b/mindspore/explainer/benchmark/_attribution/faithfulness.py
@@ -423,7 +423,9 @@ class Faithfulness(LabelSensitiveMetric):
             >>> from mindspore import nn
             >>> from mindspore.explainer.benchmark import Faithfulness
             >>> from mindspore.explainer.explanation import Gradient
+            >>> from mindspore import context
             >>>
+            >>> context.set_context(mode=context.PYNATIVE_MODE)
             >>> # init a `Faithfulness` object
             >>> num_labels = 10
             >>> metric = "InsertionAUC"
diff --git a/mindspore/explainer/benchmark/_attribution/localization.py b/mindspore/explainer/benchmark/_attribution/localization.py
index ea7f001b553..2e9bf643168 100644
--- a/mindspore/explainer/benchmark/_attribution/localization.py
+++ b/mindspore/explainer/benchmark/_attribution/localization.py
@@ -117,7 +117,9 @@ class Localization(LabelSensitiveMetric):
             >>> import mindspore as ms
             >>> from mindspore.explainer.explanation import Gradient
             >>> from mindspore.explainer.benchmark import Localization
+            >>> from mindspore import context
             >>>
+            >>> context.set_context(mode=context.PYNATIVE_MODE)
             >>> num_labels = 10
             >>> localization = Localization(num_labels, "PointingGame")
             >>>
diff --git a/mindspore/explainer/benchmark/_attribution/robustness.py b/mindspore/explainer/benchmark/_attribution/robustness.py
index f0c9b1b0e7c..e723e601d0a 100644
--- a/mindspore/explainer/benchmark/_attribution/robustness.py
+++ b/mindspore/explainer/benchmark/_attribution/robustness.py
@@ -79,7 +79,9 @@ class Robustness(LabelSensitiveMetric):
             >>> from mindspore import nn
             >>> from mindspore.explainer.explanation import Gradient
             >>> from mindspore.explainer.benchmark import Robustness
+            >>> from mindspore import context
             >>>
+            >>> context.set_context(mode=context.PYNATIVE_MODE)
             >>> # Initialize a Robustness benchmarker passing num_labels of the dataset.
             >>> num_labels = 10
             >>> activation_fn = nn.Softmax()
diff --git a/mindspore/explainer/explanation/_attribution/_backprop/gradcam.py b/mindspore/explainer/explanation/_attribution/_backprop/gradcam.py
index d587bba19d4..49e3e4edd69 100644
--- a/mindspore/explainer/explanation/_attribution/_backprop/gradcam.py
+++ b/mindspore/explainer/explanation/_attribution/_backprop/gradcam.py
@@ -83,7 +83,9 @@ class GradCAM(IntermediateLayerAttribution):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import GradCAM
+        >>> from mindspore import context
         >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> # specify a layer name to generate explanation, usually the layer can be set as the last conv layer.
diff --git a/mindspore/explainer/explanation/_attribution/_backprop/gradient.py b/mindspore/explainer/explanation/_attribution/_backprop/gradient.py
index 7c86bcb40cb..b010b90060c 100644
--- a/mindspore/explainer/explanation/_attribution/_backprop/gradient.py
+++ b/mindspore/explainer/explanation/_attribution/_backprop/gradient.py
@@ -61,7 +61,9 @@ class Gradient(Attribution):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import Gradient
+        >>> from mindspore import context
         >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> gradient = Gradient(net)
diff --git a/mindspore/explainer/explanation/_attribution/_backprop/modified_relu.py b/mindspore/explainer/explanation/_attribution/_backprop/modified_relu.py
index 919cd332743..c10494a6f4d 100644
--- a/mindspore/explainer/explanation/_attribution/_backprop/modified_relu.py
+++ b/mindspore/explainer/explanation/_attribution/_backprop/modified_relu.py
@@ -116,6 +116,9 @@ class Deconvolution(ModifiedReLU):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import Deconvolution
+        >>> from mindspore import context
+        >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> deconvolution = Deconvolution(net)
@@ -168,6 +171,9 @@ class GuidedBackprop(ModifiedReLU):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import GuidedBackprop
+        >>> from mindspore import context
+        >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> gbp = GuidedBackprop(net)
diff --git a/mindspore/explainer/explanation/_attribution/_perturbation/occlusion.py b/mindspore/explainer/explanation/_attribution/_perturbation/occlusion.py
index 71dc083edc0..58dadde0f96 100644
--- a/mindspore/explainer/explanation/_attribution/_perturbation/occlusion.py
+++ b/mindspore/explainer/explanation/_attribution/_perturbation/occlusion.py
@@ -78,6 +78,9 @@ class Occlusion(PerturbationAttribution):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import Occlusion
+        >>> from mindspore import context
+        >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> # initialize Occlusion explainer with the pretrained model and activation function
diff --git a/mindspore/explainer/explanation/_attribution/_perturbation/rise.py b/mindspore/explainer/explanation/_attribution/_perturbation/rise.py
index 8924b93f4ca..17f670eb42a 100644
--- a/mindspore/explainer/explanation/_attribution/_perturbation/rise.py
+++ b/mindspore/explainer/explanation/_attribution/_perturbation/rise.py
@@ -70,7 +70,9 @@ class RISE(PerturbationAttribution):
         >>> import numpy as np
         >>> import mindspore as ms
         >>> from mindspore.explainer.explanation import RISE
+        >>> from mindspore import context
         >>>
+        >>> context.set_context(mode=context.PYNATIVE_MODE)
         >>> # The detail of LeNet5 is shown in model_zoo.official.cv.lenet.src.lenet.py
         >>> net = LeNet5(10, num_channel=3)
         >>> # initialize RISE explainer with the pretrained model and activation function