add is dense tensor method (#38424)

paddle/pten/api/include/tensor.h

@@ -204,6 +204,14 @@ class PADDLE_API Tensor final {
    */
   DataLayout layout() const;
 
+  /**
+   * @brief Determine whether tensor is DenseTensor
+   *
+   * @return true
+   * @return false
+   */
+  bool is_dense_tensor() const;
+
   /* Part 3: Device and Backend methods */
 
   /**

paddle/pten/api/lib/tensor.cc

@@ -58,15 +58,6 @@ limitations under the License. */
 namespace paddle {
 namespace experimental {
 
-namespace detail {
-
-inline bool IsDenseTensor(
-    const std::shared_ptr<pten::TensorBase> &tensor_impl) {
-  return tensor_impl->type_info().name() == "DenseTensor";
-}
-
-}  // namespace detail
-
 // declare cast api
 Tensor cast(const Tensor &x, DataType out_dtype);
 
@@ -118,7 +109,7 @@ void Tensor::reshape(const std::vector<int64_t> &shape) {
                   "reason: `reshape` means changing the tensor shape without "
                   "touching underlying data, this requires the total size of "
                   "the tensor to remain constant.";
-  if (detail::IsDenseTensor(impl_)) {
+  if (is_dense_tensor()) {
     std::dynamic_pointer_cast<pten::DenseTensor>(impl_)->set_meta(
         pten::DenseTensorMeta(dtype(), framework::make_ddim(shape)));
   } else {
@@ -133,6 +124,10 @@ DataType Tensor::type() const { return impl_->dtype(); }
 
 DataLayout Tensor::layout() const { return impl_->layout(); }
 
+bool Tensor::is_dense_tensor() const {
+  return pten::DenseTensor::classof(impl_.get());
+}
+
 /* Part 3: Device and Backend methods */
 
 PlaceType Tensor::place() const {
@@ -153,7 +148,7 @@ bool Tensor::is_cuda() const {
 
 template <typename T>
 T *Tensor::mutable_data() {
-  if (detail::IsDenseTensor(impl_)) {
+  if (is_dense_tensor()) {
     return std::dynamic_pointer_cast<pten::DenseTensor>(impl_)
         ->mutable_data<T>();
   }
@@ -209,7 +204,7 @@ Tensor::mutable_data<paddle::platform::float16>(const PlaceType &place);
 
 template <typename T>
 const T *Tensor::data() const {
-  if (detail::IsDenseTensor(impl_)) {
+  if (is_dense_tensor()) {
     return std::dynamic_pointer_cast<pten::DenseTensor>(impl_)->data<T>();
   }
   return nullptr;
@@ -259,7 +254,7 @@ Tensor::data<paddle::platform::float16>();
 
 // TODO(chenweihang): replace slice impl by API
 Tensor Tensor::slice(const int64_t begin_idx, const int64_t end_idx) const {
-  if (detail::IsDenseTensor(impl_)) {
+  if (is_dense_tensor()) {
     return Tensor(std::make_shared<pten::DenseTensor>(
         std::move(pten::CompatibleDenseTensorUtils::Slice(
             std::dynamic_pointer_cast<pten::DenseTensor>(impl_).get(),

paddle/pten/tests/api/test_pten_tensor.cc

@@ -205,6 +205,11 @@ void TestInitilized() {
   }
 }
 
+void TestJudgeTensorType() {
+  experimental::Tensor test_tensor(paddle::PlaceType::kCPU, {1, 1});
+  CHECK(test_tensor.is_dense_tensor() == true);
+}
+
 TEST(PtenTensor, All) {
   VLOG(2) << "TestCopy";
   GroupTestCopy();
@@ -220,6 +225,8 @@ TEST(PtenTensor, All) {
   GroupTestCast();
   VLOG(2) << "TestInitilized";
   TestInitilized();
+  VLOG(2) << "TestJudgeTensorType";
+  TestJudgeTensorType();
 }
 
 }  // namespace tests