"remove alias to more operators"

paddle/operators/CMakeLists.txt

@@ -59,6 +59,7 @@ op_library(cross_entropy_op SRCS cross_entropy_op.cc cross_entropy_op.cu)
 op_library(fill_zeros_like_op SRCS fill_zeros_like_op.cc fill_zeros_like_op.cu)
 
 op_library(sgd_op SRCS sgd_op.cc sgd_op.cu)
+cc_test(sgd_op_test SRCS sgd_op_test.cc DEPS sgd_op)
 
 op_library(fc_op
     SRCS fc_op.cc

paddle/operators/mean_op.cc

@@ -17,9 +17,9 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
-class MeanOp : public OperatorWithKernel {
+class MeanOp : public framework::OperatorWithKernel {
  protected:
-  void InferShape(const InferShapeContext &ctx) const override {
+  void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(ctx.InputSize() == 1, "Input size of AddOp must be one");
     PADDLE_ENFORCE(ctx.OutputSize() == 1, "Output size of AddOp must be one");
     PADDLE_ENFORCE(ctx.InputVar(0) != nullptr && ctx.OutputVar(0) != nullptr,
@@ -28,9 +28,9 @@ class MeanOp : public OperatorWithKernel {
   }
 };
 
-class MeanOpMaker : public OpProtoAndCheckerMaker {
+class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MeanOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+  MeanOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of mean op");
     AddOutput("Out", "The output of mean op").IgnoreGradient();
@@ -38,9 +38,9 @@ class MeanOpMaker : public OpProtoAndCheckerMaker {
   }
 };
 
-class MeanGradOp : public OperatorWithKernel {
+class MeanGradOp : public framework::OperatorWithKernel {
  protected:
-  void InferShape(const InferShapeContext &ctx) const override {
+  void InferShape(const framework::InferShapeContext &ctx) const override {
     ctx.Output<Tensor>("X" + framework::kGradVarSuffix)
         ->Resize(ctx.Input<Tensor>("X")->dims());
   }
@@ -49,7 +49,10 @@ class MeanGradOp : public OperatorWithKernel {
 }  // namespace operators
 }  // namespace paddle
 
+namespace ops = paddle::operators;
 REGISTER_OP(mean, ops::MeanOp, ops::MeanOpMaker);
-REGISTER_OP_CPU_KERNEL(mean, ops::MeanKernel<ops::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(mean,
+                       ops::MeanKernel<paddle::platform::CPUPlace, float>);
 REGISTER_GRADIENT_OP(mean, mean_grad, ops::MeanGradOp);
-REGISTER_OP_CPU_KERNEL(mean_grad, ops::MeanGradKernel<ops::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(mean_grad,
+                       ops::MeanGradKernel<paddle::platform::CPUPlace, float>);

paddle/operators/mean_op.cu

@@ -16,5 +16,8 @@
 
 #include "paddle/operators/mean_op.h"
 
-REGISTER_OP_GPU_KERNEL(mean, ops::MeanKernel<ops::GPUPlace, float>);
-REGISTER_OP_GPU_KERNEL(mean_grad, ops::MeanGradKernel<ops::GPUPlace, float>);
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(mean,
+                       ops::MeanKernel<paddle::platform::GPUPlace, float>);
+REGISTER_OP_GPU_KERNEL(mean_grad,
+                       ops::MeanGradKernel<paddle::platform::GPUPlace, float>);

paddle/operators/mean_op.h

@@ -13,15 +13,24 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
-#include "paddle/operators/type_alias.h"
+#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 EigenScalar = framework::EigenScalar<T, MajorType, IndexType>;
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
+
 template <typename Place, typename T>
-class MeanKernel : public OpKernel {
+class MeanKernel : public framework::OpKernel {
  public:
-  void Compute(const ExecutionContext& context) const override {
+  void Compute(const framework::ExecutionContext& context) const override {
     auto input = context.Input<Tensor>(0);
     auto output = context.Output<Tensor>(0);
 
@@ -36,9 +45,9 @@ class MeanKernel : public OpKernel {
 };
 
 template <typename Place, typename T>
-class MeanGradKernel : public OpKernel {
+class MeanGradKernel : public framework::OpKernel {
  public:
-  void Compute(const ExecutionContext& context) const override {
+  void Compute(const framework::ExecutionContext& context) const override {
     auto OG = context.Input<Tensor>("Out" + framework::kGradVarSuffix);
     PADDLE_ENFORCE(framework::product(OG->dims()) == 1,
                    "Mean Gradient should be scalar");

paddle/operators/mul_op.cc

@@ -17,9 +17,9 @@
 namespace paddle {
 namespace operators {
 
-class MulOp : public OperatorWithKernel {
+class MulOp : public framework::OperatorWithKernel {
  protected:
-  void InferShape(const InferShapeContext &ctx) const override {
+  void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(ctx.InputSize() == 2, "The mul op must take two inputs");
     auto dim0 = ctx.Input<Tensor>(0)->dims();
     auto dim1 = ctx.Input<Tensor>(1)->dims();
@@ -37,9 +37,9 @@ class MulOp : public OperatorWithKernel {
   }
 };
 
-class MulOpMaker : public OpProtoAndCheckerMaker {
+class MulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MulOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+  MulOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The first input of mul op");
     AddInput("Y", "The second input of mul op");
@@ -52,9 +52,9 @@ The equation is: Out = X * Y
   }
 };
 
-class MulOpGrad : public OperatorWithKernel {
+class MulOpGrad : public framework::OperatorWithKernel {
  protected:
-  void InferShape(const InferShapeContext &ctx) const override {}
+  void InferShape(const framework::InferShapeContext &ctx) const override {}
   std::string DebugString() const override {
     LOG(INFO) << "MulGrad";
     return "";
@@ -64,7 +64,7 @@ class MulOpGrad : public OperatorWithKernel {
 }  // namespace operators
 }  // namespace paddle
 
+namespace ops = paddle::operators;
 REGISTER_OP(mul, ops::MulOp, ops::MulOpMaker);
 REGISTER_GRADIENT_OP(mul, mul_grad, ops::MulOpGrad);
-
-REGISTER_OP_CPU_KERNEL(mul, ops::MulKernel<ops::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(mul, ops::MulKernel<paddle::platform::CPUPlace, float>);

paddle/operators/mul_op.cu

@@ -15,4 +15,5 @@
 #define EIGEN_USE_GPU
 #include "paddle/operators/mul_op.h"
 
-REGISTER_OP_GPU_KERNEL(mul, ops::MulKernel<ops::GPUPlace, float>);
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(mul, ops::MulKernel<paddle::framework::GPUPlace, float>);

paddle/operators/mul_op.h

@@ -13,16 +13,21 @@
    limitations under the License. */
 
 #pragma once
-
-#include "paddle/operators/type_alias.h"
+#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 MulKernel : public OpKernel {
+class MulKernel : public framework::OpKernel {
  public:
-  void Compute(const ExecutionContext& context) const override {
+  void Compute(const framework::ExecutionContext& context) const override {
     Eigen::array<Eigen::IndexPair<Eigen::DenseIndex>, 1> dim_pair = {
         {Eigen::IndexPair<Eigen::DenseIndex>(1, 0)}};
 

paddle/operators/sgd_op.cc

@@ -17,9 +17,9 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
-class SGDOp : public OperatorWithKernel {
+class SGDOp : public framework::OperatorWithKernel {
  protected:
-  void InferShape(const InferShapeContext &ctx) const override {
+  void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(ctx.InputSize() == 2, "Input size of SGDOp must be two");
     PADDLE_ENFORCE(ctx.OutputSize() == 1, "Output size of SGDOp must be one");
     PADDLE_ENFORCE(ctx.InputVar(0) != nullptr, "inputs[0] mast be set");
@@ -31,9 +31,9 @@ class SGDOp : public OperatorWithKernel {
   }
 };
 
-class SGDOpMaker : public OpProtoAndCheckerMaker {
+class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SGDOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+  SGDOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("param", "input parameter");
     AddInput("grad", "input gradient");
@@ -51,5 +51,7 @@ param_out = param - learning_rate * grad;
 }  // namespace operators
 }  // namespace paddle
 
+namespace ops = paddle::operators;
 REGISTER_OP(sgd, ops::SGDOp, ops::SGDOpMaker);
-REGISTER_OP_CPU_KERNEL(sgd, ops::SGDOpKernel<ops::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(sgd,
+                       ops::SGDOpKernel<paddle::platform::CPUPlace, float>);

paddle/operators/sgd_op.cu

@@ -15,4 +15,6 @@
 #define EIGEN_USE_GPU
 #include "paddle/operators/sgd_op.h"
 
-REGISTER_OP_GPU_KERNEL(sgd, ops::SGDOpKernel<ops::GPUPlace, float>);
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(sgd,
+                       ops::SGDOpKernel<paddle::platform::GPUPlace, float>);

paddle/operators/sgd_op.h

@@ -13,15 +13,21 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
-#include "paddle/operators/type_alias.h"
+#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 SGDOpKernel : public OpKernel {
+class SGDOpKernel : public framework::OpKernel {
  public:
-  void Compute(const ExecutionContext& ctx) const override {
+  void Compute(const framework::ExecutionContext& ctx) const override {
     auto param = ctx.Input<Tensor>("param");
     auto grad = ctx.Input<Tensor>("grad");
     auto param_out = ctx.Output<Tensor>(0);