diff --git a/paddle/operators/elementwise_max_op.cc b/paddle/operators/elementwise_max_op.cc
new file mode 100644
index 0000000000000000000000000000000000000000..b5c6b11ba3b8d76330acc8d76fc88fa51bd98dc7
--- /dev/null
+++ b/paddle/operators/elementwise_max_op.cc
@@ -0,0 +1,45 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#include "paddle/operators/elementwise_max_op.h"
+#include "paddle/operators/elementwise_op.h"
+
+namespace paddle {
+namespace operators {
+class ElementwiseMaxOpMaker : public ElementwiseOpMaker {
+ public:
+  ElementwiseMaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : ElementwiseOpMaker(proto, op_checker) {
+    SetComment("Max", "Out = max(X, Y)");
+    AddComment(comment_);
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP(elementwise_max, ops::ElementwiseOp, ops::ElementwiseMaxOpMaker,
+            elementwise_max_grad, ops::ElementwiseOpGrad);
+REGISTER_OP_CPU_KERNEL(
+    elementwise_max,
+    ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, int64_t>);
+REGISTER_OP_CPU_KERNEL(
+    elementwise_max_grad,
+    ops::ElementwiseMaxGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ElementwiseMaxGradKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ElementwiseMaxGradKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::ElementwiseMaxGradKernel<paddle::platform::CPUDeviceContext, int64_t>);
\ No newline at end of file
diff --git a/paddle/operators/elementwise_max_op.h b/paddle/operators/elementwise_max_op.h
new file mode 100644
index 0000000000000000000000000000000000000000..5c685b75e508fcf4605dd61114a48876821b1582
--- /dev/null
+++ b/paddle/operators/elementwise_max_op.h
@@ -0,0 +1,107 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#pragma once
+
+#include "paddle/operators/elementwise_op_function.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct MaxFunctor {
+  inline HOSTDEVICE T operator()(T a, T b) const { return a > b ? a : b; }
+};
+
+template <typename DeviceContext, typename T>
+class ElementwiseMaxKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    using Tensor = framework::Tensor;
+
+    auto* x = ctx.Input<Tensor>("X");
+    auto* y = ctx.Input<Tensor>("Y");
+    auto* z = ctx.Output<Tensor>("Out");
+    z->mutable_data<T>(ctx.GetPlace());
+    TransformFunctor<MaxFunctor<T>, T, DeviceContext> functor(
+        x, y, z, ctx.template device_context<DeviceContext>(), MaxFunctor<T>());
+
+    auto x_dims = x->dims();
+    auto y_dims = y->dims();
+    PADDLE_ENFORCE_GE(x_dims.size(), y_dims.size(),
+                      "Rank of first input must >= rank of second input.");
+
+    if (x_dims == y_dims) {
+      functor.Run();
+      return;
+    }
+
+    int axis = ctx.Attr<int>("axis");
+    axis = (axis == -1 ? x_dims.size() - y_dims.size() : axis);
+    PADDLE_ENFORCE(axis >= 0 && axis < x_dims.size(),
+                   "Axis should be in range [0, x_dims)");
+
+    int pre, n, post;
+    get_mid_dims(x_dims, y_dims, axis, pre, n, post);
+    if (post == 1) {
+      functor.RunRowWise(n, pre);
+      return;
+    } else {
+      functor.RunMidWise(n, pre, post);
+      return;
+    }
+  }
+};
+
+template <typename T>
+struct ElementwiseSubGradFunctor {
+  template <typename Device, typename X, typename Y, typename Z, typename dX,
+            typename dY, typename dZ>
+  void operator()(Device d, X x, Y y, Z z, dX dx, dY dy, dZ dz) {
+    auto dz_e = framework::EigenVector<T>::Flatten(*dz);
+    auto x_e = framework::EigenVector<T>::Flatten(*x);
+    auto y_e = framework::EigenVector<T>::Flatten(*y);
+
+    if (dx) {
+      auto dx_e = framework::EigenVector<T>::Flatten(*dx);
+      dx_e.device(d) = (x_e > y_e) * dz_e;
+    }
+    if (dy) {
+      auto dy_e = framework::EigenVector<T>::Flatten(*dy);
+      dy_e.device(d) = (y_e >= x_e) * dz_e;
+    }
+  }
+};
+
+template <typename T>
+struct ElementwiseSubOneGradFunctor {
+  template <typename Device, typename X, typename Y, typename Z, typename dX,
+            typename dY, typename dZ>
+  void operator()(Device d, X x, Y y, Z z, dX dx, dY dy, dZ dz) {
+    auto dz_e = framework::EigenVector<T>::Flatten(*dz);
+    auto x_e = framework::EigenVector<T>::Flatten(*x);
+    auto y_e = framework::EigenVector<T>::Flatten(*y);
+    if (dx) {
+      auto dx_e = framework::EigenVector<T>::Flatten(*dx);
+      dx_e.device(d) = dz_e;
+    }
+    if (dy) {
+      auto dy_e = framework::EigenVector<T>::Flatten(*dy);
+      dy_e.device(d) = (-1.0) * dz_e.sum();
+    }
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
diff --git a/paddle/operators/elementwise_min_op.cc b/paddle/operators/elementwise_min_op.cc
new file mode 100644
index 0000000000000000000000000000000000000000..b78846f17ae773126fb6aef8c70c79235976c47b
--- /dev/null
+++ b/paddle/operators/elementwise_min_op.cc
@@ -0,0 +1,45 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#include "paddle/operators/elementwise_min_op.h"
+#include "paddle/operators/elementwise_op.h"
+
+namespace paddle {
+namespace operators {
+class ElementwiseMinOpMaker : public ElementwiseOpMaker {
+ public:
+  ElementwiseMinOpMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : ElementwiseOpMaker(proto, op_checker) {
+    SetComment("Max", "Out = min(X, Y)");
+    AddComment(comment_);
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP(elementwise_min, ops::ElementwiseOp, ops::ElementwiseMinOpMaker,
+            elementwise_min_grad, ops::ElementwiseOpGrad);
+REGISTER_OP_CPU_KERNEL(
+    elementwise_min,
+    ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, int64_t>);
+REGISTER_OP_CPU_KERNEL(
+    elementwise_min_grad,
+    ops::ElementwiseMinGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::ElementwiseMinGradKernel<paddle::platform::CPUDeviceContext, double>,
+    ops::ElementwiseMinGradKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::ElementwiseMinGradKernel<paddle::platform::CPUDeviceContext, int64_t>);
\ No newline at end of file