diff --git a/api_examples/paddle/fluid/prune_with_input.py b/api_examples/paddle/fluid/prune_with_input.py
new file mode 100644
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+++ b/api_examples/paddle/fluid/prune_with_input.py
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+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved
+#
+# 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
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# 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.
+
+# api: paddle.fluid.framework.Program._prune_with_input()
+# env: local
+# device: cpu
+# text：prune-with-input
+
+import paddle.fluid as fluid
+import paddle.fluid.optimizer as optimizer
+import numpy as np
+
+def sample_data():
+   res = []
+   for i in range(2):
+       data = np.random.normal(size=(2,))
+       label = np.random.randint(2, size=(1,))
+       res.append((data, label))
+   return res
+
+x = fluid.layers.data(name='x', shape=[2], dtype='float32')
+label = fluid.layers.data(name="label", shape=[1], dtype="int64")
+
+# define net here
+y = fluid.layers.fc(input=[x], size=2, act="softmax")
+loss = fluid.layers.cross_entropy(input=y, label=label)
+loss = fluid.layers.mean(x=loss)
+
+sgd = fluid.optimizer.SGD(learning_rate=0.01)
+sgd.minimize(loss)
+
+with open("original_program", "w") as f:
+    f.write(str(fluid.default_main_program()))
+
+pruned_program = fluid.default_main_program()._prune_with_input(
+                        feeded_var_names=[y.name, label.name],
+                        targets = [loss])
+
+with open("pruned_program", "w") as f:
+    f.write(str(pruned_program))