diff --git a/paddle/operators/dropout_op.cc b/paddle/operators/dropout_op.cc
new file mode 100644
index 0000000000000000000000000000000000000000..a9950a48e0f42ce46ffd27ecc972c35d82a98fdb
--- /dev/null
+++ b/paddle/operators/dropout_op.cc
@@ -0,0 +1,81 @@
+/* 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/dropout_op.h"
+
+namespace paddle {
+namespace operators {
+
+using framework::Tensor;
+
+class DropoutOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(const framework::InferShapeContext &ctx) const override {
+    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
+    auto dims = ctx.Input<Tensor>("X")->dims();
+    ctx.Output<Tensor>("Out")->Resize(dims);
+    ctx.Output<Tensor>("Mask")->Resize(dims);
+  }
+};
+
+class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  DropoutOpMaker(framework::OpProto *proto,
+                 framework::OpAttrChecker *op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("X", "The input of dropout op.");
+    AddOutput("Out", "The output of dropout op.");
+    AddOutput("Mask", "The dropout mask.").AsIntermediate();
+
+    AddComment(R"DOC(Dropout Operator.)DOC");
+  }
+};
+
+class DropoutOpGrad : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(const framework::InferShapeContext &ctx) const override {
+    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
+    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Mask"), "Mask must not be null.");
+    PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
+                            "Input(Out@GRAD) must not be null.");
+
+    auto x_dims = ctx.Input<Tensor>("X")->dims();
+    auto mask_dims = ctx.Input<Tensor>("Mask")->dims();
+    auto out_dims = ctx.Input<Tensor>(framework::GradVarName("Out"))->dims();
+    PADDLE_ENFORCE_EQ(x_dims, out_dims,
+                      "Dimensions of Input(X) and Out must be the same.");
+    PADDLE_ENFORCE_EQ(x_dims, mask_dims,
+                      "Dimensions of Input(X) and Mask must be the same.");
+
+    auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
+    x_grad->Resize(x_dims);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP(dropout, ops::DropoutOp, ops::DropoutOpMaker, dropout_grad,
+            ops::DropoutOpGrad);
+REGISTER_OP_CPU_KERNEL(dropout,
+                       ops::DropoutKernel<paddle::platform::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(
+    dropout_grad, ops::DropoutGradKernel<paddle::platform::CPUPlace, float>);
diff --git a/paddle/operators/dropout_op.cu b/paddle/operators/dropout_op.cu
new file mode 100644
index 0000000000000000000000000000000000000000..9e9efaa3b1af7e6905ea9ed565c7b40433010db7
--- /dev/null
+++ b/paddle/operators/dropout_op.cu
@@ -0,0 +1,22 @@
+/* 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. */
+
+#define EIGEN_USE_GPU
+#include "paddle/operators/dropout_op.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(dropout,
+                       ops::DropoutKernel<paddle::platform::GPUPlace, float>);
+REGISTER_OP_GPU_KERNEL(
+    dropout_grad, ops::DropoutGradKernel<paddle::platform::GPUPlace, float>);
diff --git a/paddle/operators/dropout_op.h b/paddle/operators/dropout_op.h
new file mode 100644
index 0000000000000000000000000000000000000000..d5d32df74b70c9d81b094d4f4ea6d6681b9573ba
--- /dev/null
+++ b/paddle/operators/dropout_op.h
@@ -0,0 +1,70 @@
+/* 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/framework/eigen.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+using EigenMatrix = framework::EigenMatrix<T, MajorType, IndexType>;
+
+template <typename Place, typename T>
+class DropoutKernel : public framework::OpKernel {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* x = context.Input<Tensor>("X");
+    auto* y = context.Output<Tensor>("Out");
+    auto* mask = context.Output<Tensor>("Mask");
+    mask->mutable_data<T>(context.GetPlace());
+    y->mutable_data<T>(context.GetPlace());
+
+    auto dims = x->dims();
+    auto X = EigenMatrix<T>::From(*x);
+    auto Y = EigenMatrix<T>::From(*y);
+    auto M = EigenMatrix<T>::From(*mask);
+
+    auto place = context.GetEigenDevice<Place>();
+    M.device(place).setRandom<UniformRandomGenerator>();
+    float dropout_prob = context.op_.GetAttr<float>("dropout_prob");
+    M.device(place) = (M > dropout_prob).cast<float>();
+    Y.device(place) = X * Y;
+  }
+};
+
+template <typename Place, typename T>
+class DropoutGradKernel : public framework::OpKernel {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* grad_x = context.Output<Tensor>(framework::GradVarName("X"));
+    auto* grad_y = context.Input<Tensor>(framework::GradVarName("Out"));
+    auto* mask = context.Input<Tensor>("Mask");
+    grad_x->mutable_data<T>(context.GetPlace());
+
+    auto dims = grad_x->dims();
+    auto M = EigenMatrix<T>::From(*mask);
+    auto dX = EigenMatrix<T>::From(*grad_x);
+    auto dY = EigenMatrix<T>::From(*grad_y);
+
+    auto place = context.GetEigenDevice<Place>();
+    dX.device(place) = dY * M;
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
diff --git a/paddle/pybind/pybind.cc b/paddle/pybind/pybind.cc
index 3bc150ccb7af2885439cc2344aa0db9ba3b1ca03..42fce51024e1a52a22de1c6f60e5466018f895ad 100644
--- a/paddle/pybind/pybind.cc
+++ b/paddle/pybind/pybind.cc
@@ -46,6 +46,7 @@ USE_OP(lookup_table);
 USE_OP(scale);
 USE_OP_ITSELF(identity);
 USE_OP(minus);
+USE_OP(dropout);
 USE_CPU_ONLY_OP(gather);
 USE_CPU_ONLY_OP(scatter);