[Cherry-Pick 2.0][Dynamic Inplace] Support ShareInplaceVersionCounterWith for...

[Cherry-Pick 2.0][Dynamic Inplace] Support ShareInplaceVersionCounterWith for C++ Tensor (#29842) (#30105)

Before this PR, SharePlaceHolderWith share Tensor between different C++ Variable, which meas sharing the data, shape, and inplace_version_counter_ of Tensor.
But in some cases, Sharing data and inplace_version_counter_ but not sharing shape is needed. For example, inplace op reshape, can't share shape.

This PR, discard SharePlaceHolderWith, and expose ShareInplaceVersionCounterWith for C++ Tensor.
This reverts commit b10ecd9d.

* Support ShareInplaceVersionCounterWith to share the same inplace version counter for VarBase

paddle/fluid/framework/tensor.cc

@@ -39,7 +39,10 @@ void Tensor::check_memory_size() const {
           numel() * SizeOfType(type()), memory_size()));
 }
 
-Tensor::Tensor(const proto::VarType::Type& dtype) : type_(dtype), offset_(0) {}
+Tensor::Tensor(const proto::VarType::Type& dtype)
+    : type_(dtype),
+      offset_(0),
+      inplace_version_counter_(std::make_shared<TensorInplaceVersion>(0)) {}
 
 size_t Tensor::memory_size() const {
   return holder_ == nullptr ? 0UL : holder_->size() - offset_;
@@ -89,6 +92,15 @@ Tensor& Tensor::ShareDataWith(const Tensor& src) {
   *this = src;
   return *this;
 }
+Tensor& Tensor::ShareInplaceVersionCounterWith(const Tensor& src) {
+  PADDLE_ENFORCE_NOT_NULL(
+      inplace_version_counter_,
+      platform::errors::PreconditionNotMet(
+          "Tensor does not hold inplace_version_counter_."));
+
+  inplace_version_counter_ = src.inplace_version_counter_;
+  return *this;
+}
 
 Tensor Tensor::Slice(int64_t begin_idx, int64_t end_idx) const {
   check_memory_size();

paddle/fluid/framework/tensor.h

@@ -120,7 +120,10 @@ class Tensor {
   friend struct EigenVector;
 
  public:
-  Tensor() : type_(proto::VarType::FP32), offset_(0) {}
+  Tensor()
+      : type_(proto::VarType::FP32),
+        offset_(0),
+        inplace_version_counter_(std::make_shared<TensorInplaceVersion>(0)) {}
 
   explicit Tensor(const proto::VarType::Type&);
 
@@ -171,6 +174,9 @@ class Tensor {
   /*! The internal of two tensors share the same memory block. */
   Tensor& ShareDataWith(const Tensor& src);
 
+  /*! The internal of two tensors share the same inplace version counter. */
+  Tensor& ShareInplaceVersionCounterWith(const Tensor& src);
+
   /**
    * @brief  Return a sub-tensor of the given tensor.
    *
@@ -252,7 +258,7 @@ class Tensor {
                            const proto::VarType::Type type);
 
   TensorInplaceVersion& InplaceVersionCounter() {
-    return inplace_version_counter_;
+    return *inplace_version_counter_;
   }
 
  private:
@@ -290,7 +296,7 @@ class Tensor {
    *          PlaceHolder::ptr_ and where the tensor data really begins.
    */
   size_t offset_;
-  TensorInplaceVersion inplace_version_counter_;
+  std::shared_ptr<TensorInplaceVersion> inplace_version_counter_;
 };
 
 }  // namespace framework

paddle/fluid/framework/variable.h

@@ -69,16 +69,6 @@ class Variable {
     return holder_->Type();
   }
 
-  /**
-   * The internal of two Variables share the same Placeholder whose type can be
-   * Tensor, LoDTensor, SelectedRows, LoDTensorArray, etc.
-   *
-   * NOTE(liym27): In dynamic mode, sharing the same Placeholder also means
-   * share the same TensorInplaceVersion, which is very important for inplace
-   * operations.
-   */
-  void SharePlaceholderWith(const Variable& var);
-
  private:
   // This method hides type T, so it doesn't appear as a template parameter of
   // Variable.
@@ -123,14 +113,6 @@ class Variable {
   std::shared_ptr<Placeholder> holder_;
 };
 
-inline void Variable::SharePlaceholderWith(const Variable& var) {
-  PADDLE_ENFORCE_EQ(var.IsInitialized(), true,
-                    platform::errors::PreconditionNotMet(
-                        "Variable holds no memory. "
-                        "Call Variable::GetMutable() firstly."));
-  holder_ = var.holder_;
-}
-
 inline framework::TensorInplaceVersion* Variable::InplaceVersionCounter() {
   framework::TensorInplaceVersion* version_counter_ptr(nullptr);
   if (IsType<framework::LoDTensor>()) {

paddle/fluid/pybind/imperative.cc

@@ -696,44 +696,69 @@ void BindImperative(py::module *m_ptr) {
                 x = linear(data)
                 print(x.numpy())
        )DOC")
-      .def(
-          "detach",
-          [](const imperative::VarBase &self)
-              -> std::shared_ptr<imperative::VarBase> {
-                PADDLE_ENFORCE_EQ(
-                    self.Var().IsInitialized(), true,
-                    platform::errors::InvalidArgument(
-                        "Tensor %s has not been initialized!", self.Name()));
-
-                PADDLE_ENFORCE_EQ(
-                    self.Var().IsType<framework::LoDTensor>() ||
-                        self.Var().IsType<framework::SelectedRows>(),
-                    true,
-                    platform::errors::InvalidArgument(
-                        "Type of Tensor[%s] must be LoDTensor or SelectedRows!",
-                        self.Name()));
-
-                auto detach_var = std::make_shared<imperative::VarBase>(
-                    true, "detach_" + self.Name());
-
-                detach_var->SetPersistable(self.Persistable());
-                detach_var->SetType(self.Type());
-                detach_var->SetDataType(self.DataType());
-
-                // NOTE(liym27):
-                // Call Variable::SharePlaceholderWith but not
-                // Tensor::ShareDataWith or Tensor::ShareBufferWith, because
-                // `detach_var` should share the same TensorInplaceVersion with
-                // `self`, and only SharePlaceholderWith can also share the same
-                // TensorInplaceVersion, which is used to check whether inplace
-                // operations are correct.
-                detach_var->MutableVar()->SharePlaceholderWith(self.Var());
-
-                VLOG(3) << "The detached Tensor(" << detach_var->Name()
-                        << ") share data with " << self.Name();
-                return detach_var;
-              },
-          py::return_value_policy::take_ownership, R"DOC(
+      .def("detach",
+           [](const imperative::VarBase
+                  &self) -> std::shared_ptr<imperative::VarBase> {
+             PADDLE_ENFORCE_EQ(
+                 self.Var().IsInitialized(), true,
+                 platform::errors::InvalidArgument(
+                     "Tensor %s has not been initialized!", self.Name()));
+
+             PADDLE_ENFORCE_EQ(
+                 self.Var().IsType<framework::LoDTensor>() ||
+                     self.Var().IsType<framework::SelectedRows>(),
+                 true,
+                 platform::errors::InvalidArgument(
+                     "Type of Tensor[%s] must be LoDTensor or SelectedRows!",
+                     self.Name()));
+
+             auto detach_var = std::make_shared<imperative::VarBase>(
+                 true, "detach_" + self.Name());
+
+             detach_var->SetPersistable(self.Persistable());
+             detach_var->SetType(self.Type());
+             detach_var->SetDataType(self.DataType());
+
+             if (self.Var().IsType<framework::LoDTensor>()) {
+               const auto &origin_tensor =
+                   self.Var().Get<framework::LoDTensor>();
+               PADDLE_ENFORCE_EQ(
+                   origin_tensor.IsInitialized(), true,
+                   platform::errors::InvalidArgument(
+                       "Tensor %s has not been initialized!", self.Name()));
+
+               auto *detach_tensor =
+                   detach_var->MutableVar()->GetMutable<framework::LoDTensor>();
+               detach_tensor->ShareDataWith(origin_tensor);
+               // NOTE(liym27): Call ShareInplaceVersionCounterWith to share the
+               // same TensorInplaceVersion, which is used to check whether
+               // inplace
+               // operations are correct.
+               detach_tensor->ShareInplaceVersionCounterWith(origin_tensor);
+             } else {
+               const auto &origin_selected_rows =
+                   self.Var().Get<framework::SelectedRows>();
+               PADDLE_ENFORCE_EQ(
+                   origin_selected_rows.value().IsInitialized(), true,
+                   platform::errors::InvalidArgument(
+                       "Tensor %s has not been initialized!", self.Name()));
+
+               auto *detach_selected_rows =
+                   detach_var->MutableVar()
+                       ->GetMutable<framework::SelectedRows>();
+               detach_selected_rows->set_height(origin_selected_rows.height());
+               detach_selected_rows->set_rows(origin_selected_rows.rows());
+               detach_selected_rows->mutable_value()->ShareDataWith(
+                   origin_selected_rows.value());
+               detach_selected_rows->mutable_value()
+                   ->ShareInplaceVersionCounterWith(
+                       origin_selected_rows.value());
+             }
+             VLOG(3) << "The detached Tensor(" << detach_var->Name()
+                     << ") share data with " << self.Name();
+             return detach_var;
+           },
+           py::return_value_policy::take_ownership, R"DOC(
 
         Returns a new Tensor, detached from the current graph.
         It will share data with origin Tensor and always doesn't have a Tensor copy.