Merge pull request #2953 from wangkuiyi/tensor_type_to_eigen

Refactorize Tensor to Eigen convesion

paddle/framework/CMakeLists.txt

@@ -4,8 +4,11 @@ cc_test(enforce_test SRCS enforce_test.cc DEPS enforce)
 cc_library(ddim SRCS ddim.cc DEPS eigen3)
 cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
 nv_test(dim_test SRCS dim_test.cu DEPS ddim)
+
 cc_library(tensor SRCS tensor.cc DEPS ddim place enforce paddle_memory)
 cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)
+cc_test(eigen_test SRCS eigen_test.cc DEPS tensor)
+
 cc_test(variable_test SRCS variable_test.cc)
 cc_test(scope_test SRCS scope_test.cc)
 proto_library(attr_type SRCS attr_type.proto)

paddle/framework/ddim.h

@@ -119,17 +119,6 @@ int arity(const DDim& ddim);
 
 std::ostream& operator<<(std::ostream&, const DDim&);
 
-template <int NDIMS>
-Eigen::DSizes<Eigen::DenseIndex, NDIMS> ToEigenDSizes(const DDim& dims) {
-  int rank = arity(dims);
-  PADDLE_ENFORCE(rank == NDIMS, "DDim and NDIMS must be same");
-  Eigen::DSizes<Eigen::DenseIndex, NDIMS> dsizes;
-  for (int d = 0; d < rank; d++) {
-    dsizes[d] = dims[d];
-  }
-  return dsizes;
-}
-
 }  // namespace framework
 }  // namespace paddle
 

paddle/framework/eigen.h

+/* 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/tensor.h"
+#include "unsupported/Eigen/CXX11/Tensor"
+
+namespace paddle {
+namespace framework {
+
+// EigenDim converts paddle::platform::DDim into Eigen::DSizes.
+template <int D>
+struct EigenDim {
+  using Type = Eigen::DSizes<Eigen::DenseIndex, D>;
+
+  static Type From(const DDim& dims) {
+    PADDLE_ENFORCE(arity(dims) == D, "D must match arity(DDim)");
+    Type ret;
+    for (int d = 0; d < arity(dims); d++) {
+      ret[d] = dims[d];
+    }
+    return ret;
+  }
+};
+
+// Interpret paddle::platform::Tensor as EigenTensor and EigenConstTensor.
+template <typename T, size_t D, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+struct EigenTensor {
+  // TODO(qijun) Now, default type in unaligned, and we will make a benchmark on
+  // the speed of aligned and unaligned version in future.
+  using Type = Eigen::TensorMap<Eigen::Tensor<T, D, MajorType, IndexType>>;
+
+  using ConstType =
+      Eigen::TensorMap<Eigen::Tensor<const T, D, MajorType, IndexType>>;
+
+  static Type From(Tensor& tensor, DDim dims) {
+    return Type(tensor.data<T>(), EigenDim<D>::From(dims));
+  }
+
+  static Type From(Tensor& tensor) { return From(tensor, tensor.dims_); }
+
+  static ConstType From(const Tensor& tensor, DDim dims) {
+    return ConstType(tensor.data<T>(), EigenDim<D>::From(dims));
+  }
+
+  static ConstType From(const Tensor& tensor) {
+    return From(tensor, tensor.dims_);
+  }
+};
+
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+struct EigenVector : public EigenTensor<T, 1, MajorType, IndexType> {
+  // Flatten is to reshape a Tensor into a one dimension EigenVector
+  static typename EigenTensor<T, 1>::Type Flatten(Tensor& tensor) {
+    return EigenTensor<T, 1>::From(
+        tensor, make_ddim({static_cast<int>(product(tensor.dims_))}));
+  }
+
+  static typename EigenTensor<T, 1>::ConstType Flatten(const Tensor& tensor) {
+    return EigenTensor<T, 1>::From(
+        tensor, make_ddim({static_cast<int>(product(tensor.dims_))}));
+  }
+};
+
+template <typename T, int MajorType = Eigen::RowMajor,
+          typename IndexType = Eigen::DenseIndex>
+using EigenMatrix = EigenTensor<T, 2, MajorType, IndexType>;
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/eigen_test.cc

+/*
+  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/framework/eigen.h"
+#include <gtest/gtest.h>
+
+namespace paddle {
+namespace framework {
+
+TEST(EigenDim, From) {
+  EigenDim<3>::Type ed = EigenDim<3>::From(make_ddim({1, 2, 3}));
+  ASSERT_EQ(1, ed[0]);
+  ASSERT_EQ(2, ed[1]);
+  ASSERT_EQ(3, ed[2]);
+}
+
+TEST(Eigen, Tensor) {
+  Tensor t;
+  float* p = t.mutable_data<float>(make_ddim({1, 2, 3}), platform::CPUPlace());
+  for (int i = 0; i < 1 * 2 * 3; i++) {
+    p[i] = static_cast<float>(i);
+  }
+
+  EigenTensor<float, 3>::Type et = EigenTensor<float, 3>::From(t);
+
+  ASSERT_EQ(1, et.dimension(0));
+  ASSERT_EQ(2, et.dimension(1));
+  ASSERT_EQ(3, et.dimension(2));
+
+  for (int i = 0; i < 1; i++) {
+    for (int j = 0; j < 2; j++) {
+      for (int k = 0; k < 3; k++) {
+        ASSERT_NEAR((i * 2 + j) * 3 + k, et(i, j, k), 1e-6f);
+      }
+    }
+  }
+}
+
+TEST(Eigen, VectorFrom) {
+  Tensor t;
+  float* p = t.mutable_data<float>(make_ddim({6}), platform::CPUPlace());
+  for (int i = 0; i < 6; i++) {
+    p[i] = static_cast<float>(i);
+  }
+
+  EigenVector<float>::Type ev = EigenVector<float>::From(t);
+
+  ASSERT_EQ(6, ev.dimension(0));
+
+  for (int i = 0; i < 6; i++) {
+    ASSERT_NEAR(i, ev(i), 1e-6f);
+  }
+}
+
+TEST(Eigen, VectorFlatten) {
+  Tensor t;
+  float* p = t.mutable_data<float>(make_ddim({1, 2, 3}), platform::CPUPlace());
+  for (int i = 0; i < 1 * 2 * 3; i++) {
+    p[i] = static_cast<float>(i);
+  }
+
+  EigenVector<float>::Type ev = EigenVector<float>::Flatten(t);
+
+  ASSERT_EQ(1 * 2 * 3, ev.dimension(0));
+
+  for (int i = 0; i < 1 * 2 * 3; i++) {
+    ASSERT_NEAR(i, ev(i), 1e-6f);
+  }
+}
+
+TEST(Eigen, Matrix) {
+  Tensor t;
+  float* p = t.mutable_data<float>(make_ddim({2, 3}), platform::CPUPlace());
+  for (int i = 0; i < 2 * 3; i++) {
+    p[i] = static_cast<float>(i);
+  }
+
+  EigenMatrix<float>::Type em = EigenMatrix<float>::From(t);
+
+  ASSERT_EQ(2, em.dimension(0));
+  ASSERT_EQ(3, em.dimension(1));
+
+  for (int i = 0; i < 2; i++) {
+    for (int j = 0; j < 3; j++) {
+      ASSERT_NEAR(i * 3 + j, em(i, j), 1e-6f);
+    }
+  }
+}
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/tensor.h

@@ -20,7 +20,6 @@ limitations under the License. */
 #include <typeindex>
 #include "paddle/framework/ddim.h"
 #include "paddle/framework/enforce.h"
-#include "paddle/framework/tensor_types.h"
 #include "paddle/memory/memory.h"
 #include "paddle/platform/place.h"
 #include "unsupported/Eigen/CXX11/Tensor"
@@ -35,6 +34,15 @@ struct CastToPyBufferImpl;
 namespace framework {
 
 class Tensor {
+  template <bool less, size_t i, typename... args>
+  friend struct paddle::pybind::details::CastToPyBufferImpl;
+
+  template <typename T, size_t D, int MajorType, typename IndexType>
+  friend struct EigenTensor;
+
+  template <typename T, int MajorType, typename IndexType>
+  friend struct EigenVector;
+
  public:
   Tensor() : offset_(0) {}
 
@@ -46,7 +54,7 @@ class Tensor {
   }
 
   template <typename T>
-  T* raw_data() const {
+  T* data() {
     CheckDims<T>();
     return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
                                 offset_);
@@ -86,66 +94,6 @@ class Tensor {
                                 offset_);
   }
 
-  template <typename T, size_t NDIMS>
-  typename TTypes<T, NDIMS>::Tensor shaped(DDim new_dims) {
-    Eigen::array<Eigen::DenseIndex, NDIMS> dims =
-        paddle::framework::ToEigenDSizes<NDIMS>(new_dims);
-    return typename TTypes<T, NDIMS>::Tensor(raw_data<T>(), dims);
-  }
-
-  template <typename T, size_t NDIMS>
-  typename TTypes<T, NDIMS>::Tensor tensor() {
-    return typename TTypes<T, NDIMS>::Tensor(
-        raw_data<T>(), paddle::framework::ToEigenDSizes<NDIMS>(dims_));
-  }
-
-  // flat to rank = 1
-  template <typename T>
-  typename TTypes<T>::Flat flat() {
-    return shaped<T, 1>(make_ddim({static_cast<int>(product(dims_))}));
-  }
-
-  // to TensorType Vec
-  template <typename T>
-  typename TTypes<T>::Vec vec() {
-    return tensor<T, 1>();
-  }
-
-  // to TensorType Matrix
-  template <typename T>
-  typename TTypes<T>::Matrix matrix() {
-    return tensor<T, 2>();
-  }
-
-  // const versions of all the methods above.
-  template <typename T, size_t NDIMS>
-  typename TTypes<T, NDIMS>::Tensor shaped(DDim new_dims) const {
-    Eigen::array<Eigen::DenseIndex, NDIMS> dims =
-        paddle::framework::ToEigenDSizes<NDIMS>(new_dims);
-    return typename TTypes<T, NDIMS>::Tensor(data<T>(), dims);
-  }
-
-  template <typename T, size_t NDIMS>
-  typename TTypes<T, NDIMS>::ConstantTensor tensor() const {
-    return typename TTypes<T, NDIMS>::Tensor(
-        data<T>(), paddle::framework::ToEigenDSizes<NDIMS>(dims_));
-  }
-
-  template <typename T>
-  typename TTypes<T>::ConstFlat flat() const {
-    return shaped<T, 1>(make_ddim({static_cast<int>(product(dims_))}));
-  }
-
-  template <typename T>
-  typename TTypes<T>::ConstVec vec() const {
-    return tensor<T, 1>();
-  }
-
-  template <typename T>
-  typename TTypes<T>::ConstMatrix matrix() const {
-    return tensor<T, 2>();
-  }
-
   template <typename T>
   void ShareDataFrom(const Tensor& src) {
     src.CheckDims<T>();
@@ -251,8 +199,6 @@ class Tensor {
   std::shared_ptr<Placeholder> holder_;  // holds the memory block if allocated.
   DDim dims_;
   size_t offset_;  // marks the begin of tensor data area.
-  template <bool less, size_t i, typename... args>
-  friend struct paddle::pybind::details::CastToPyBufferImpl;
 };
 
 }  // namespace framework

paddle/framework/tensor_types.h

-/* 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 "unsupported/Eigen/CXX11/Tensor"
-
-namespace paddle {
-namespace framework {
-
-// Helper to define Tensor types given that the scalar is of type T.
-template <typename T, int NDIMS = 1, typename IndexType = Eigen::DenseIndex>
-struct TTypes {
-  // Rank-<NDIMS> tensor of scalar type T.
-  typedef Eigen::TensorMap<Eigen::Tensor<T, NDIMS, Eigen::RowMajor, IndexType>,
-                           Eigen::Aligned>
-      Tensor;
-  typedef Eigen::TensorMap<
-      Eigen::Tensor<const T, NDIMS, Eigen::RowMajor, IndexType>, Eigen::Aligned>
-      ConstTensor;
-
-  // Scalar tensor (implemented as a rank-0 tensor) of scalar type T.
-  typedef Eigen::TensorMap<
-      Eigen::TensorFixedSize<T, Eigen::Sizes<>, Eigen::RowMajor, IndexType>,
-      Eigen::Aligned>
-      Scalar;
-  typedef Eigen::TensorMap<Eigen::TensorFixedSize<const T, Eigen::Sizes<>,
-                                                  Eigen::RowMajor, IndexType>,
-                           Eigen::Aligned>
-      ConstScalar;
-
-  // Rank-1 tensor (vector) of scalar type T.
-  typedef Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, IndexType>,
-                           Eigen::Aligned>
-      Flat;
-  typedef Eigen::TensorMap<
-      Eigen::Tensor<const T, 1, Eigen::RowMajor, IndexType>, Eigen::Aligned>
-      ConstFlat;
-  typedef Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, IndexType>,
-                           Eigen::Aligned>
-      Vec;
-  typedef Eigen::TensorMap<
-      Eigen::Tensor<const T, 1, Eigen::RowMajor, IndexType>, Eigen::Aligned>
-      ConstVec;
-
-  // Rank-2 tensor (matrix) of scalar type T.
-  typedef Eigen::TensorMap<Eigen::Tensor<T, 2, Eigen::RowMajor, IndexType>,
-                           Eigen::Aligned>
-      Matrix;
-  typedef Eigen::TensorMap<
-      Eigen::Tensor<const T, 2, Eigen::RowMajor, IndexType>, Eigen::Aligned>
-      ConstMatrix;
-};
-
-}  // namespace framework
-}  // namespace paddle

paddle/operators/add_op.h

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #pragma once
 #include "glog/logging.h"
+#include "paddle/framework/eigen.h"
 #include "paddle/framework/operator.h"
 
 namespace paddle {
@@ -29,8 +30,10 @@ public:
 
     output->mutable_data<T>(context.GetPlace());
 
-    output->flat<T>().device(*(context.GetEigenDevice<Place>())) =
-        input0.flat<T>() + input1.flat<T>();
+    framework::EigenVector<T>::Flatten(*output).device(
+        *(context.GetEigenDevice<Place>())) =
+        framework::EigenVector<T>::Flatten(input0) +
+        framework::EigenVector<T>::Flatten(input1);
   }
 };