Use friend not to expose tensor's `type/place`

paddle/framework/tensor.h

@@ -24,6 +24,12 @@ limitations under the License. */
 #include "paddle/platform/place.h"
 
 namespace paddle {
+namespace pybind {
+namespace details {  // forward declare
+template <bool less, size_t i, typename... args>
+struct CastToPyBufferImpl;
+}  // namespace details
+}  // namespace pybind
 namespace framework {
 
 class Tensor {
@@ -128,10 +134,6 @@ class Tensor {
 
   DDim dims() const { return dims_; }
 
-  platform::Place place() const { return holder_->place(); }
-
-  std::type_index type() const { return holder_->type(); }
-
  private:
   // Placeholder hides type T, so it doesn't appear as a template
   // parameter of Variable.
@@ -186,7 +188,9 @@ class Tensor {
   DDim dims_;
   size_t numel_;   // cache of `product(dims_)`
   size_t offset_;  // marks the begin of tensor data area.
-};                 // namespace framework
+  template <bool less, size_t i, typename... args>
+  friend struct paddle::pybind::details::CastToPyBufferImpl;
+};  // namespace framework
 
 }  // namespace framework
 }  // namespace paddle

paddle/pybind/pybind.cc

@@ -15,7 +15,7 @@ limitations under the License. */
 #include <Python.h>
 #include <paddle/framework/op_registry.h>
 #include <paddle/framework/scope.h>
-#include <paddle/pybind/tensor.h>
+#include <paddle/pybind/tensor_bind.h>
 #include <pybind11/numpy.h>
 #include <pybind11/pybind11.h>
 #include <pybind11/stl.h>
@@ -32,8 +32,6 @@ PYBIND11_PLUGIN(core) {
 
   py::class_<pd::Tensor>(m, "Tensor", py::buffer_protocol())
       .def_buffer([](pd::Tensor& self) -> py::buffer_info {
-        PADDLE_ENFORCE(paddle::platform::is_cpu_place(self.place()),
-                       "Only CPU tensor can cast to numpy array");
         return paddle::pybind::CastToPyBuffer(self);
       })
       .def("get_dims",

paddle/pybind/tensor.h → paddle/pybind/tensor_bind.h

@@ -40,7 +40,10 @@ template <size_t I, typename... ARGS>
 struct CastToPyBufferImpl<true, I, ARGS...> {
   using CUR_TYPE = typename std::tuple_element<I, std::tuple<ARGS...>>::type;
   py::buffer_info operator()(framework::Tensor &tensor) {
-    if (std::type_index(typeid(CUR_TYPE)) == tensor.type()) {
+    PADDLE_ENFORCE(paddle::platform::is_cpu_place(tensor.holder_->place()),
+                   "Only CPU tensor can cast to numpy array");
+
+    if (std::type_index(typeid(CUR_TYPE)) == tensor.holder_->type()) {
       auto dim_vec = framework::vectorize(tensor.dims());
       std::vector<size_t> dims_outside;
       std::vector<size_t> strides;
@@ -54,12 +57,13 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
         prod *= dims_outside[i - 1];
       }
 
-      return py::buffer_info(tensor.mutable_data<CUR_TYPE>(tensor.place()),
-                             sizeof(CUR_TYPE),
-                             py::format_descriptor<CUR_TYPE>::format(),
-                             (size_t)framework::arity(tensor.dims()),
-                             dims_outside,
-                             strides);
+      return py::buffer_info(
+          tensor.mutable_data<CUR_TYPE>(tensor.holder_->place()),
+          sizeof(CUR_TYPE),
+          py::format_descriptor<CUR_TYPE>::format(),
+          (size_t)framework::arity(tensor.dims()),
+          dims_outside,
+          strides);
     } else {
       constexpr bool less = I + 1 < std::tuple_size<std::tuple<ARGS...>>::value;
       return CastToPyBufferImpl<less, I + 1, ARGS...>()(tensor);