[Unify Tensors PR #3]Port framework::Tensor members & interfaces to p…

…ten::DenseTensor, test=allcases (#38473)

* Added shared_ptr<Allocation> member & corresponding interfaces to Storage

* Removed original pten::Allocation from Storage and adjusted the interfaces accordingly

* Fixed issues with storage offset

* Used place to malloc allocation for TensorStorage

* [Unify Tensors PR #3]Ported framework::Tensor interfaces to pten::DenseTensor

* Fixed issues with place

* Added comments

* Moved mutable_data with stream argument to DenseTensor

* Added set_offset interface

* Fixed CI issues,test=allcases

* [Unify Tensors PR #4] Port LoDTensor interfaces to DenseTensor

* Reverted changes too pten_layout() interface

* Removed friend classes

paddle/fluid/framework/CMakeLists.txt

@@ -68,15 +68,15 @@ cc_test(data_type_test SRCS data_type_test.cc DEPS data_type place tensor)
 if(WITH_GPU)
   if (WIN32)
     windows_symbolic(tensor_util SRCS tensor_util.cu)
-    nv_library(tensor SRCS tensor.cc .tensor_util.cu DEPS place memory data_type device_context)
+    nv_library(tensor SRCS tensor.cc .tensor_util.cu DEPS place memory data_type device_context dense_tensor)
     add_dependencies(tensor tensor_util)
   else()
-    nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context profiler)
+    nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context profiler dense_tensor)
   endif(WIN32)
 elseif(WITH_ROCM)
-  hip_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context profiler)
+  hip_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context profiler dense_tensor)
 else()
-  cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context profiler)
+  cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context profiler dense_tensor)
 endif()
 
 cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)

paddle/fluid/framework/tensor.h

@@ -120,6 +120,8 @@ class Tensor {
   explicit Tensor(const proto::VarType::Type&);
 
   /*! Return a pointer to mutable memory block. */
+  const void* data() const;
+
   template <typename T>
   T* data();
 

paddle/fluid/framework/tensor_impl.h

@@ -54,6 +54,12 @@ inline T* Tensor::data() {
                               offset_);
 }
 
+inline const void* Tensor::data() const {
+  check_memory_size();
+  return reinterpret_cast<void*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
+                                 offset_);
+}
+
 template <typename T>
 inline T* Tensor::mutable_data(const DDim& dims, const platform::Place& place,
                                size_t requested_size) {

paddle/fluid/framework/tensor_util.cc

@@ -23,18 +23,22 @@ limitations under the License. */
 #include "paddle/fluid/framework/tensor_util.h"
 #include "paddle/fluid/platform/complex.h"
 #include "paddle/fluid/platform/profiler.h"
+
+#include "paddle/pten/core/dense_tensor.h"
+
 #ifdef PADDLE_WITH_MKLDNN
 #include "dnnl_debug.h"  // NOLINT
 #endif
 
 namespace paddle {
 namespace framework {
 
-void TensorCopy(const Tensor& src, const platform::Place& dst_place,
-                const platform::DeviceContext& ctx, Tensor* dst) {
+template <typename TENSOR>
+void TensorCopyImpl(const TENSOR& src, const platform::Place& dst_place,
+                    const platform::DeviceContext& ctx, TENSOR* dst) {
   if (&src == dst) {
     auto src_copy = src;
-    TensorCopy(src_copy, dst_place, ctx, dst);
+    TensorCopyImpl(src_copy, dst_place, ctx, dst);
     return;
   }
 
@@ -45,7 +49,7 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
   dst->Resize(src.dims());
   dst->set_layout(src.layout());
   auto src_place = src.place();
-  auto src_ptr = src.data<void>();
+  auto src_ptr = src.data();
 #ifdef PADDLE_WITH_MKLDNN
   dst->set_format(src.format());
   // oneDNN tensors due to padding may be of bigger size
@@ -389,16 +393,34 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
 #endif
 }
 
-void TensorCopy(const Tensor& src, const platform::Place& dst_place,
-                Tensor* dst) {
+template <typename TENSOR>
+void TensorCopyImpl(const TENSOR& src, const platform::Place& dst_place,
+                    TENSOR* dst) {
   platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
   const platform::DeviceContext* dev_ctx;
   if (platform::is_gpu_place(dst_place) || platform::is_npu_place(dst_place)) {
     dev_ctx = pool.Get(dst_place);
   } else {
     dev_ctx = pool.Get(src.place());
   }
-  TensorCopy(src, dst_place, *dev_ctx, dst);
+  TensorCopyImpl(src, dst_place, *dev_ctx, dst);
+}
+
+void TensorCopy(const Tensor& src, const platform::Place& dst_place,
+                Tensor* dst) {
+  TensorCopyImpl<Tensor>(src, dst_place, dst);
+}
+void TensorCopy(const pten::DenseTensor& src, const platform::Place& dst_place,
+                pten::DenseTensor* dst) {
+  TensorCopyImpl<pten::DenseTensor>(src, dst_place, dst);
+}
+void TensorCopy(const Tensor& src, const platform::Place& dst_place,
+                const platform::DeviceContext& ctx, Tensor* dst) {
+  TensorCopyImpl<Tensor>(src, dst_place, ctx, dst);
+}
+void TensorCopy(const pten::DenseTensor& src, const platform::Place& dst_place,
+                const platform::DeviceContext& ctx, pten::DenseTensor* dst) {
+  TensorCopyImpl<pten::DenseTensor>(src, dst_place, ctx, dst);
 }
 
 void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
@@ -418,7 +440,7 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
   dst->set_format(src.format());
 #endif
   auto src_place = src.place();
-  auto src_ptr = src.data<void>();
+  auto src_ptr = src.data();
   auto dst_ptr = dst->mutable_data(dst_place, src.type());
 
   if (src_ptr == dst_ptr && src_place == dst_place) {
@@ -971,7 +993,7 @@ void TensorToStream(std::ostream& os, const Tensor& tensor,
   {  // the 3rd field, tensor data
     uint64_t size = tensor.numel() * framework::SizeOfType(tensor.type());
 
-    auto* data_ptr = tensor.data<void>();
+    auto* data_ptr = tensor.data();
     PADDLE_ENFORCE_LT(size, (std::numeric_limits<std::streamsize>::max)(),
                       platform::errors::ResourceExhausted(
                           "tensor size %d overflow when writing tensor", size));

paddle/fluid/framework/tensor_util.h

@@ -34,6 +34,8 @@ limitations under the License. */
 #include "paddle/fluid/platform/device/mlu/device_context.h"
 #endif
 
+#include "paddle/pten/core/dense_tensor.h"
+
 namespace paddle {
 namespace framework {
 
@@ -75,6 +77,8 @@ class Tensor;
 
 void TensorCopy(const Tensor& src, const platform::Place& dst_place,
                 const platform::DeviceContext& ctx, Tensor* dst);
+void TensorCopy(const pten::DenseTensor& src, const platform::Place& dst_place,
+                const platform::DeviceContext& ctx, pten::DenseTensor* dst);
 
 // NOTE(zcd): If the src.place() and dst_place are two different GPU,
 // the copy operation is carried out on the dst_place's stream. This is
@@ -85,6 +89,8 @@ void TensorCopy(const Tensor& src, const platform::Place& dst_place,
 // not completed.
 void TensorCopy(const Tensor& src, const platform::Place& dst_place,
                 Tensor* dst);
+void TensorCopy(const pten::DenseTensor& src, const platform::Place& dst_place,
+                pten::DenseTensor* dst);
 
 void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
                     Tensor* dst);

paddle/pten/core/CMakeLists.txt

@@ -9,6 +9,11 @@ endif()
 cc_library(kernel_factory SRCS kernel_factory.cc DEPS enforce convert_utils)
 cc_library(kernel_context SRCS kernel_context.cc DEPS enforce pten_context)
 cc_library(tensor_base SRCS tensor_base.cc allocator.cc storage.cc DEPS enforce)
+
 cc_library(tensor_meta SRCS tensor_meta.cc DEPS enforce mixed_vector)
+cc_library(dense_tensor SRCS dense_tensor.cc DEPS convert_utils tensor_meta tensor_base)
 
-cc_library(dense_tensor SRCS dense_tensor.cc DEPS tensor_meta tensor_base)
+# Will remove once we implemented MKLDNN_Tensor
+if(WITH_MKLDNN)
+    add_dependencies(dense_tensor mkldnn)
+endif()