/* Copyright 2017 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ #ifndef TENSORFLOW_CORE_UTIL_PTR_UTIL_H_ #define TENSORFLOW_CORE_UTIL_PTR_UTIL_H_ // Utility functions for pointers. #include #include #include #include namespace tensorflow { namespace helper { // Trait to select overloads and return types for MakeUnique. template struct MakeUniqueResult { using scalar = std::unique_ptr; }; template struct MakeUniqueResult { using array = std::unique_ptr; }; template struct MakeUniqueResult { using invalid = void; }; } // namespace helper // Transfers ownership of a raw pointer to a std::unique_ptr of deduced type. // Example: // X* NewX(int, int); // auto x = WrapUnique(NewX(1, 2)); // 'x' is std::unique_ptr. // // WrapUnique is useful for capturing the output of a raw pointer factory. // However, prefer 'MakeUnique(args...) over 'WrapUnique(new T(args...))'. // auto x = WrapUnique(new X(1, 2)); // works, but nonideal. // auto x = MakeUnique(1, 2); // safer, standard, avoids raw 'new'. // // Note: Cannot wrap pointers to array of unknown bound (i.e. U(*)[]). template std::unique_ptr WrapUnique(T* ptr) { static_assert(!std::is_array::value || std::extent::value != 0, "types T[0] or T[] are unsupported"); return std::unique_ptr(ptr); } template typename helper::MakeUniqueResult::scalar MakeUnique(Args&&... args) { return std::unique_ptr(new T(std::forward(args)...)); } // Overload for array of unknown bound. // The allocation of arrays needs to use the array form of new, // and cannot take element constructor arguments. template typename helper::MakeUniqueResult::array MakeUnique(size_t n) { return std::unique_ptr(new typename std::remove_extent::type[n]()); } } // namespace tensorflow #endif // TENSORFLOW_CORE_UTIL_PTR_UTIL_H_