refactor(mgb): add TensorND::proxy_to_default_cpu

GitOrigin-RevId: 3ab8525f1c0e04d128632982a7f3ffdb78971a23

src/core/include/megbrain/tensor.h

@@ -101,6 +101,14 @@ class Slice {
         SubTensorSpec apply(TensorLayout layout, int axis) const;
 };
 
+template <class Trait> class TensorStorage;
+
+class DeviceTensorStorageTrait;
+class HostTensorStorageTrait;
+
+using HostTensorStorage = TensorStorage<HostTensorStorageTrait>;
+using DeviceTensorStorage = TensorStorage<DeviceTensorStorageTrait>;
+
 /*!
  * \brief manager for raw tensor memory
  *
@@ -230,6 +238,18 @@ class TensorStorage {
             std::enable_if<!std::is_same<Trait, RTrait>::value>::type>
         static TensorStorage make_proxy(const TensorStorage<RTrait> &src);
 
+        /*!
+         * \brief make a DeviceTensorStorage on default_cpu
+         *      that shares memory with this
+         *
+         * this must be a HostTensorStorage. Alignment not checked.
+         */
+        template<bool x = true, typename = std::enable_if_t<x && std::is_same<Trait, HostTensorStorageTrait>::value>>
+        DeviceTensorStorage proxy_to_default_cpu() const {
+            ptr();
+            return {true, CompNode::default_cpu(), m_size, m_capacity, m_offset, m_data};
+        }
+
         //! shortcut for raw_storage().use_count(), but won't trigger lazy alloc
         size_t use_count() const {
             if (m_size > m_capacity) {
@@ -284,11 +304,12 @@ class TensorStorage {
 
         [[noreturn]] static void on_invalid_comp_node();
 };
-class DeviceTensorStorageTrait;
-class HostTensorStorageTrait;
 
-using HostTensorStorage = TensorStorage<HostTensorStorageTrait>;
-using DeviceTensorStorage = TensorStorage<DeviceTensorStorageTrait>;
+
+template<class TensorStorage> class TensorND;
+
+using HostTensorND = TensorND<HostTensorStorage>;
+using DeviceTensorND = TensorND<DeviceTensorStorage>;
 
 /*!
  * \brief n-dimensional tensor
@@ -519,10 +540,15 @@ class TensorND {
             ret.reset(TensorStorage::make_proxy(src.storage()), src.layout());
             return ret;
         }
-};
 
-using HostTensorND = TensorND<HostTensorStorage>;
-using DeviceTensorND = TensorND<DeviceTensorStorage>;
+        //! similar to HostTensorStorage::proxy_to_default_cpu
+        template<bool x = true, typename = std::enable_if_t<x && std::is_same<TensorStorage, HostTensorStorage>::value>>
+        DeviceTensorND proxy_to_default_cpu() const {
+            DeviceTensorND ret;
+            ret.reset(storage().proxy_to_default_cpu(), layout());
+            return ret;
+        }
+};
 
 /*!
  * \brief call memset in the data of a device tensor

src/core/test/tensor.cpp

@@ -418,4 +418,13 @@ TEST(TestTensor, CpuCudaD2DCopy) {
     }
 }
 
+TEST(TestTensor, ProxyToDefaultCPU) {
+    auto cn = CompNode::load("xpux");
+    auto x = HostTensorND(cn, TensorLayout({1, 2, 3}, dtype::Float32{}));
+    auto y = x.proxy_to_default_cpu();
+    ASSERT_EQ(y.comp_node(), CompNode::default_cpu());
+    ASSERT_EQ(x.layout(), y.layout());
+    ASSERT_EQ(x.raw_ptr(), y.raw_ptr());
+}
+
 // vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}}