Revert "Refactor dygraph to eager (#37318)" (#37386)

paddle/fluid/CMakeLists.txt

@@ -11,6 +11,6 @@ add_subdirectory(imperative)
 add_subdirectory(operators)
 add_subdirectory(string)
 add_subdirectory(pybind)
-add_subdirectory(eager)
+
 # NOTE: please add subdirectory inference at last.
 add_subdirectory(inference)

paddle/fluid/eager/CMakeLists.txt

-add_subdirectory(tests)

paddle/fluid/eager/eager_tensor.h

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// 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 <Python.h>
-// framework deps
-#include "paddle/fluid/framework/data_layout_transform.h"
-#include "paddle/fluid/framework/pten_utils.h"
-#include "paddle/fluid/framework/tensor.h"
-#include "paddle/fluid/framework/variable.h"
-// pten deps
-#include "paddle/pten/all.h"
-#include "paddle/pten/api/all.h"
-#include "paddle/pten/api/lib/utils/tensor_utils.h"
-/**
- * This class is used by Eager mode for now. It's painful to do this in Eager
- * Mode, the better
- * choice is to use paddle::experimental::Tensor directly. However, we have a
- * punch of nested kernel code, and
- * they use paddle::framework::Variable in inner logic code. So, we have to
- * provide variable in
- * paddle::framework::ExecutionContext to support it. We should remove this as
- * soon as we finish our latest
- * Pten Lib, and use paddle::experimental::Tensor instead.
- *
- * Note: Keep this class as clean as possible.
- * This class should only support method declared in
- * paddle::experimental::Tensor with access method of
- * paddle::framework::Variable no more members are acceptable.
- * **/
-
-namespace egr {
-class EagerTensor final {
- public:
-  /* Part 1: Constructors */
-  EagerTensor()
-      : tensor_(std::make_shared<paddle::experimental::Tensor>()),
-        var_(paddle::framework::Variable()) {}
-  explicit EagerTensor(const std::string& name)
-      : tensor_(std::make_shared<paddle::experimental::Tensor>(name)),
-        var_(paddle::framework::Variable()) {}
-  /**
-   * @description: Use a TensorImpl pointer to construct a Tensor
-   * @param {shared_ptr<TensorBase>} tensor_impl
-   * @return {Tensor}
-   */
-  explicit EagerTensor(const std::shared_ptr<pten::TensorBase>& tensor_impl)
-      : tensor_(std::make_shared<paddle::experimental::Tensor>(tensor_impl)),
-        var_(paddle::framework::Variable()) {}
-  EagerTensor(const EagerTensor&) = default;
-  EagerTensor(EagerTensor&&) = default;
-
-  /* Part 2: Name access methods */
-  /**
-   * @description: Return the name of current Tensor.
-   * @param None
-   * @return {const std::string&}
-   */
-  const std::string& name() const { return tensor_->name(); }
-  /**
-   * @description: Set the name of current Tensor.
-   * @param {const std::string& name}
-   * @return None
-   */
-  void set_name(const std::string& name) { tensor_->set_name(name); }
-
-  /* Part 3: Dimension, DataType and DataLayout methods */
-  /**
-   * @description: Return the number of elements of current Tensor.
-   * @param None
-   * @return {int64_t}
-   */
-  int64_t numel() const { return tensor_->numel(); }
-  /**
-   * @description: Return the shape (dimensions) of current Tensor.
-   * @param None
-   * @return {DDim}
-   */
-  paddle::framework::DDim shape() const { return tensor_->dims(); }
-
-  /**
-   * @description: Return the data type of current Tensor.
-   * @param None
-   * @return {DataType}
-   */
-  paddle::experimental::DataType type() const { return tensor_->type(); }
-
-  /**
-   * @description: Return the layout of current Tensor.
-   * @param None
-   * @return {DataLayout}
-   */
-  paddle::experimental::DataLayout layout() const { return tensor_->layout(); }
-
-  /* Part 3: Device and Backend methods */
-  /**
-   * @description: Return the place (device) of current Tensor.
-   * @param None
-   * @return {Place}
-   */
-  paddle::platform::Place place() const { return tensor_->inner_place(); }
-
-  /**
-   * Backend judgment APIs, shield the concept of Backend.
-   */
-  bool is_cpu() const { return paddle::platform::is_cpu_place(place()); }
-  bool is_cuda() const { return paddle::platform::is_gpu_place(place()); }
-
-  /* Part 4: Data Access methods */
-  /**
-   * @description: Return the implemention of current Tensor.
-   * @param None
-   * @return {std::shared_ptr<TensorBase>}
-   */
-  std::shared_ptr<pten::TensorBase> impl() const { return tensor_->impl(); }
-
-  /**
-   * @description: Set the implemention of current Tensor.
-   * @param {std::shared_ptr<TensorBase>}
-   * @return None
-   */
-  void set_impl(const std::shared_ptr<pten::TensorBase>& impl) {
-    tensor_->set_impl(impl);
-  }
-
-  // TODO(chenweihang): Whether API Tensor need `data` and `mutable_data`?
-
-  // TODO(chenweihang): slice and split methods use kernels?
-
-  /* Part 5: Status utils methods */
-  /**
-   * @description: Determine whether it is a meaningful Tensor
-   * @param None
-   * @return {bool}
-   */
-  bool defined() const { return tensor_->defined(); }
-
-  /**
-   * @description: Determine whether Tensor is initialized
-   * @param None
-   * @return {bool}
-   */
-  bool initialized() const { return tensor_->initialized(); }
-
-  /**
-   * @description: Reset the Tensor implementation
-   * @param None
-   * @return {void}
-   */
-  void reset() { tensor_->reset(); }
-
-  /* Part 6: Operator overloading */
-  EagerTensor& operator=(const EagerTensor& x) & {
-    tensor_ = x.tensor_;
-    var_ = x.var_;
-    return *this;
-  }
-  EagerTensor& operator=(EagerTensor&& x) & {
-    tensor_ = std::move(x.tensor_);
-    var_ = std::move(x.var_);
-    return *this;
-  }
-
-  /* Part 7: Autograd methods */
-  paddle::experimental::AbstractAutogradMeta* get_autograd_meta() const {
-    return tensor_->get_autograd_meta();
-  }
-  void set_autograd_meta(
-      std::shared_ptr<paddle::experimental::AbstractAutogradMeta>
-          autograd_meta) {
-    tensor_->set_autograd_meta(autograd_meta);
-  }
-
-  /** Part 9: Get framework::Variable from EagerTensor **/
-  const paddle::framework::Variable& Var() const { return var_; }
-
-  paddle::framework::Variable* MutableVar() { return &var_; }
-
-  /** Part 10: Sync paddle::framework::Variable with pten::Tensor **/
-  void SyncToVar(paddle::framework::proto::VarType_Type type =
-                     paddle::framework::proto::VarType::LOD_TENSOR) {
-    // Synchronize allocation only once.
-    if (!var_.IsInitialized()) {
-      // TODO(jiabin): Support selected rows later.
-      if (this->initialized()) {
-        if (type == paddle::framework::proto::VarType::LOD_TENSOR) {
-          auto* framework_tensor =
-              var_.GetMutable<paddle::framework::LoDTensor>();
-          framework_tensor->Resize(tensor_->dims());
-          framework_tensor->set_layout(
-              pten::TransToFluidDataLayout(tensor_->layout()));
-          // Contruct framework::Tensor from egr::EagerTensor
-          auto tensor_dense =
-              std::dynamic_pointer_cast<pten::DenseTensor>(tensor_->impl());
-          if (tensor_dense) {
-            paddle::experimental::MovesStorage(tensor_dense.get(),
-                                               framework_tensor);
-          } else {
-            PADDLE_THROW(paddle::platform::errors::Fatal(
-                "Unrecognized egr::EagerTensor type, only "
-                "DenseTensor is supported for now."));
-          }
-        }
-      } else {
-        PADDLE_THROW(paddle::platform::errors::Fatal(
-            "Can not Sync EagerTensor %s whose "
-            "pten::DenseTensor is not initialized!",
-            name()));
-      }
-    }
-  }
-  /** Part 11: Sync paddle::framework::Variable with pten::Tensor **/
-  void SyncToTensor() {
-    // Synchronize allocation only once.
-    if (!this->defined() || !this->initialized()) {
-      // TODO(jiabin): Support selected rows later.
-      if (var_.IsInitialized()) {
-        if (var_.IsType<paddle::framework::LoDTensor>()) {
-          SetImplWithLegacyTensor<paddle::framework::LoDTensor,
-                                  pten::DenseTensor>();
-        } else if (var_.IsType<paddle::framework::Tensor>()) {
-          SetImplWithLegacyTensor<paddle::framework::Tensor,
-                                  pten::DenseTensor>();
-        } else {
-          PADDLE_THROW(paddle::platform::errors::Fatal(
-              "Unable to fetch underlying tensor "
-              "from VarBase, only LoDTensor and "
-              "Tensor are supported for now"));
-        }
-      } else {
-        PADDLE_THROW(paddle::platform::errors::Fatal(
-            "Can not Sync EagerTensor %s whose paddle::framework::Variable is "
-            "not initialized!",
-            name()));
-      }
-    }
-  }
-
-  void ResetVar(const paddle::framework::Variable& src) { var_ = src; }
-
- private:
-  template <typename LEGACY_TYPE, typename TYPE>
-  void SetImplWithLegacyTensor() {
-    const auto& framework_tensor = var_.Get<LEGACY_TYPE>();
-    this->set_impl(
-        std::move(paddle::experimental::MakePtenDenseTensor(framework_tensor)));
-    var_.Clear();
-  }
-
- private:
-  std::shared_ptr<paddle::experimental::Tensor> tensor_ = nullptr;
-  paddle::framework::Variable var_;
-};
-}  // namespace egr

paddle/fluid/eager/tests/CMakeLists.txt

-set(eager_deps pten pten_api python)
-add_subdirectory(data_structure_tests)

paddle/fluid/eager/tests/data_structure_tests/CMakeLists.txt

-cc_test(test_egr_ds_eager_tensor SRCS eager_tensor_test.cc DEPS ${eager_deps})

paddle/fluid/eager/tests/data_structure_tests/eager_tensor_test.cc

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// 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 "glog/logging.h"
-#include "gtest/gtest.h"
-
-#include "paddle/fluid/eager/eager_tensor.h"
-#include "paddle/pten/api/lib/utils/allocator.h"
-
-// TODO(jiabin): remove nolint here!!!
-using namespace egr;  // NOLINT
-
-namespace eager_test {
-using AbstractAutogradMeta = paddle::experimental::AbstractAutogradMeta;
-class AutogradMetaTest : public AbstractAutogradMeta {
- public:
-  explicit AutogradMetaTest(int val) : val_(val) {}
-  int val_ = 0;
-};
-}
-TEST(EagerTensor, Constructor) {
-  EagerTensor et1 = EagerTensor();
-  EagerTensor et2 = EagerTensor("et2");
-
-  CHECK_EQ(et1.defined(), false);
-  CHECK_EQ(et2.name(), "et2");
-
-  pten::DenseTensorMeta meta = pten::DenseTensorMeta(
-      pten::DataType::FLOAT32, paddle::framework::make_ddim({1, 2}));
-  std::shared_ptr<pten::DenseTensor> dt = std::make_shared<pten::DenseTensor>(
-      std::make_shared<paddle::experimental::DefaultAllocator>(
-          paddle::platform::CPUPlace()),
-      meta);
-  auto* dt_ptr = dt->mutable_data<float>();
-  dt_ptr[0] = 5.0f;
-  dt_ptr[1] = 10.0f;
-  EagerTensor et3 = EagerTensor(dt);
-  auto* et3_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et3.impl())->data<float>();
-  CHECK_EQ(et3_ptr[0], 5.0f);
-  CHECK_EQ(et3_ptr[1], 10.0f);
-  // copy constructor
-  EagerTensor et4(et3);
-  auto* et4_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et4.impl())->data<float>();
-  CHECK_EQ(et4_ptr[0], 5.0f);
-  CHECK_EQ(et4_ptr[1], 10.0f);
-  EagerTensor et5(std::move(et4));
-  auto* et5_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et5.impl())->data<float>();
-  CHECK_EQ(et5_ptr[0], 5.0f);
-  CHECK_EQ(et5_ptr[1], 10.0f);
-}
-
-TEST(EagerTensor, MemberFunction) {
-  EagerTensor et3;
-  pten::DenseTensorMeta meta = pten::DenseTensorMeta(
-      pten::DataType::FLOAT32, paddle::framework::make_ddim({1, 2}));
-  std::shared_ptr<pten::DenseTensor> dt = std::make_shared<pten::DenseTensor>(
-      std::make_shared<paddle::experimental::DefaultAllocator>(
-          paddle::platform::CPUPlace()),
-      meta);
-  auto* dt_ptr = dt->mutable_data<float>();
-  dt_ptr[0] = 5.0f;
-  dt_ptr[1] = 10.0f;
-  VLOG(6) << "Make Dense Tensor";
-  et3.set_name("et3");
-  VLOG(6) << "Set Name";
-  CHECK_EQ(et3.name(), "et3");
-  CHECK_EQ(et3.defined(), false);
-  et3.set_impl(dt);
-  VLOG(6) << "Set impl";
-  CHECK_EQ(et3.initialized(), true);
-  CHECK_EQ(et3.is_cpu(), true);
-  CHECK_EQ(et3.is_cuda(), false);
-  CHECK_EQ(et3.numel(), 2);
-  auto expected_dim = paddle::framework::make_ddim({1, 2});
-  CHECK_EQ(et3.shape(), expected_dim);
-  CHECK_EQ(et3.type(), paddle::experimental::DataType::FLOAT32);
-  CHECK_EQ(et3.layout(), paddle::experimental::DataLayout::NCHW);
-  CHECK(paddle::platform::is_cpu_place(et3.place()));
-  VLOG(6) << "Get impl";
-  auto* dt3_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et3.impl())->data<float>();
-  CHECK_EQ(dt3_ptr[0], 5.0f);
-  CHECK_EQ(dt3_ptr[1], 10.0f);
-  EagerTensor et4 = et3;
-  VLOG(6) << "copy =";
-  CHECK(et4.initialized() == true);
-  auto* dt4_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et4.impl())->data<float>();
-  CHECK_EQ(dt4_ptr[0], 5.0f);
-  CHECK_EQ(dt4_ptr[1], 10.0f);
-  VLOG(6) << "move =";
-  EagerTensor et5 = std::move(et4);
-  auto* dt5_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et5.impl())->data<float>();
-  CHECK_EQ(dt5_ptr[0], 5.0f);
-  CHECK_EQ(dt5_ptr[1], 10.0f);
-  VLOG(6) << "AutogradMeta";
-  auto autograd_meta_test = std::make_shared<eager_test::AutogradMetaTest>(2);
-  et3.set_autograd_meta(autograd_meta_test);
-  auto* tmp_autograd_meta_test =
-      static_cast<eager_test::AutogradMetaTest*>(et3.get_autograd_meta());
-  CHECK_EQ(tmp_autograd_meta_test->val_, 2);
-  VLOG(6) << "SyncToVar";
-  et3.SyncToVar();
-  CHECK_EQ(et3.Var().Get<paddle::framework::LoDTensor>().data<float>()[0],
-           5.0f);
-  CHECK_EQ(et3.Var().Get<paddle::framework::LoDTensor>().data<float>()[1],
-           10.0f);
-  VLOG(6) << "SyncToTensor";
-  CHECK(et3.initialized() == false);
-  et3.SyncToTensor();
-  CHECK(et3.initialized() == true);
-  VLOG(6) << "Check Tensor";
-  auto* dt3_tmp_ptr =
-      std::dynamic_pointer_cast<pten::DenseTensor>(et3.impl())->data<float>();
-  CHECK_EQ(dt3_tmp_ptr[0], 5.0f);
-  CHECK_EQ(dt3_tmp_ptr[1], 10.0f);
-  et3.reset();
-  CHECK(et3.defined() == false);
-  VLOG(6) << "Finish";
-}

paddle/pten/api/include/tensor.h

@@ -86,16 +86,13 @@ class AbstractAutogradMeta {
 
 class PD_DLL_DECL Tensor final {
  public:
+  /* Part 1: Construction and destruction methods */
+
   /**
    * @brief Construct a new Tensor object
    */
   Tensor() = default;
 
-  /**
-   * @brief Construct a new Tensor object with name
-   * */
-  explicit Tensor(const std::string& name) { name_ = name; }
-
   /**
    * @brief Construct a new Tensor object by copy
    */
@@ -131,19 +128,7 @@ class PD_DLL_DECL Tensor final {
    */
   Tensor(const PlaceType& place, const std::vector<int64_t>& shape);
 
-  /**
-   * @brief Return the name of Tensor.
-   *
-   * @return const std::string&
-   */
-  const std::string& name() const { return name_; }
-
-  /**
-   * @brief Set name of Tensor.
-   *
-   * @param const std::string& name
-   */
-  void set_name(const std::string& name) { name_ = name; }
+  /* Part 2: Dimension, DataType and DataLayout methods */
 
   /**
    * @brief Return the number of elements of Tensor.