Adding the implementation for rmsprop operator

paddle/operators/rmsprop_op.cc

@@ -0,0 +1,93 @@
+/* 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/rmsprop_op.h"
+
+namespace paddle {
+namespace operators {
+
+class RmspropOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(framework::InferShapeContextBase *ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("Param"),
+                   "Input(Param) of RmspropOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("Grad"),
+                   "Input(Grad) of RmspropOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("Moment"),
+                   "Input(Moment) of RmspropOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
+                   "Input(LearningRate) of RmspropOp should not be null.");
+
+    PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
+                   "Output(param_out) of RmspropOp should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("MomentOut"),
+                   "Output(moment_out) of RmspropOp should not be null.");
+
+    auto param_dim = ctx->GetInputDim("Param");
+    PADDLE_ENFORCE_EQ(
+        param_dim, ctx->GetInputDim("Grad"),
+        "Param and grad input of RmspropOp should have the same dimension.");
+    PADDLE_ENFORCE_EQ(
+        param_dim, ctx->GetInputDim("Moment"),
+        "Param and moment input of RmspropOp should have the same dimension.");
+
+    auto lr_dim = ctx->GetInputDim("LearningRate");
+    PADDLE_ENFORCE_EQ(framework::product(lr_dim), 1,
+                      "Learning Rate should be a scalar.");
+
+    ctx->SetOutputDim("ParamOut", param_dim);
+    ctx->SetOutputDim("MomentOut", param_dim);
+  }
+};
+
+class RmspropOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  RmspropOpMaker(framework::OpProto *proto,
+                 framework::OpAttrChecker *op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("Param", "Input parameter");
+    AddInput("Grad", "Input gradient");
+    AddInput("Moment", "Second moment");
+    AddInput("LearningRate", "Learning Rate");
+
+    AddOutput("ParamOut", "Output parameter");
+    AddOutput("MomentOut", "Output second moment");
+
+    AddAttr<float>("epsilon", "Constant for numerical stability");
+    AddAttr<float>("decayRate", "Decay rate for moving average of gradients");
+    AddComment(R"DOC(
+
+RMSprop
+
+MomentOut = decayRate * Moment + (1 - decayRate) * Grad * Grad
+ParamOut = Param - LearningRate * Grad / (sqrt(MomentOut) + epsilon)
+
+The original slide(Slide 29 of
+http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf)
+does not have the epsilon attribute. It is added here for numerical stability
+to avoid division by zero.
+
+)DOC");
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(rmsprop, ops::RmspropOp, ops::RmspropOpMaker);
+REGISTER_OP_CPU_KERNEL(rmsprop,
+                       ops::RmspropOpKernel<paddle::platform::CPUPlace, float>);

paddle/operators/rmsprop_op.cu

@@ -0,0 +1,20 @@
+/* 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/rmsprop_op.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(rmsprop,
+                       ops::RmspropOpKernel<paddle::platform::GPUPlace, float>);

paddle/operators/rmsprop_op.h

@@ -0,0 +1,54 @@
+/* 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 EigenVector = framework::EigenVector<T, MajorType, IndexType>;
+
+template <typename Place, typename T>
+class RmspropOpKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto param_out = ctx.Output<Tensor>("ParamOut");
+    auto moment_out = ctx.Output<Tensor>("MomentOut");
+
+    param_out->mutable_data<T>(ctx.GetPlace());
+    moment_out->mutable_data<T>(ctx.GetPlace());
+
+    float epsilon = ctx.Attr<float>("epsilon");
+    float decay = ctx.Attr<float>("decayRate");
+
+    auto p = EigenVector<T>::Flatten(*ctx.Input<Tensor>("Param"));
+    auto g = EigenVector<T>::Flatten(*ctx.Input<Tensor>("Grad"));
+    auto m = EigenVector<T>::Flatten(*ctx.Input<Tensor>("Moment"));
+    float lr = ctx.Input<Tensor>("LearningRate")->data<float>()[0];
+    auto p_out = EigenVector<T>::Flatten(*param_out);
+    auto m_out = EigenVector<T>::Flatten(*moment_out);
+    auto place = ctx.GetEigenDevice<Place>();
+
+    m_out.device(place) = decay * m + (1 - decay) * g * g;
+    p_out.device(place) = p - lr * g / (m_out.sqrt() + epsilon);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/v2/framework/tests/test_rmsprop_op.py

@@ -0,0 +1,38 @@
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestRmspropOp(OpTest):
+    def setUp(self):
+        self.op_type = "rmsprop"
+
+        param = np.random.random((123, 321)).astype("float32")
+        grad = np.random.random((123, 321)).astype("float32")
+        moment = np.zeros((123, 321)).astype("float32")
+        learning_rate = np.array([0.01]).astype("float32")
+
+        epsilon = 1e-6
+        decay_rate = 0.9
+
+        self.inputs = {
+            'Param': param,
+            'Grad': grad,
+            'Moment': moment,
+            'LearningRate': learning_rate
+        }
+
+        self.attrs = {'epsilon': epsilon, 'decayRate': decay_rate}
+
+        moment_out = decay_rate * moment + (1 - decay_rate) * grad * grad
+        param_out = param - learning_rate * grad / (np.sqrt(moment_out) +
+                                                    epsilon)
+
+        self.outputs = {'ParamOut': param_out, 'MomentOut': moment_out}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+if __name__ == "__main__":
+    unittest.main()