1/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15
16#ifndef TENSORFLOW_CORE_FRAMEWORK_TYPED_ALLOCATOR_H_
17#define TENSORFLOW_CORE_FRAMEWORK_TYPED_ALLOCATOR_H_
18
19#include <limits>
20
21#include "tensorflow/core/framework/allocator.h"
22#include "tensorflow/core/framework/resource_handle.h"
23#include "tensorflow/core/framework/type_traits.h"
24#include "tensorflow/core/platform/types.h"
25
26namespace tensorflow {
27
28class Variant;
29
30// Convenience functions to do typed allocation. C++ constructors
31// and destructors are invoked for complex types if necessary.
32class TypedAllocator {
33 public:
34 // May return NULL if the tensor has too many elements to represent in a
35 // single allocation.
36 template <typename T>
37 static T* Allocate(Allocator* raw_allocator, size_t num_elements,
38 const AllocationAttributes& allocation_attr) {
39 // TODO(jeff): Do we need to allow clients to pass in alignment
40 // requirements?
41
42 if (num_elements > (std::numeric_limits<size_t>::max() / sizeof(T))) {
43 return nullptr;
44 }
45
46 void* p =
47 raw_allocator->AllocateRaw(Allocator::kAllocatorAlignment,
48 sizeof(T) * num_elements, allocation_attr);
49 T* typed_p = reinterpret_cast<T*>(p);
50 if (typed_p) RunCtor<T>(raw_allocator, typed_p, num_elements);
51 return typed_p;
52 }
53
54 template <typename T>
55 static void Deallocate(Allocator* raw_allocator, T* ptr,
56 size_t num_elements) {
57 if (ptr) {
58 RunDtor<T>(raw_allocator, ptr, num_elements);
59 raw_allocator->DeallocateRaw(ptr);
60 }
61 }
62
63 private:
64 // No constructors or destructors are run for simple types
65 template <typename T>
66 static void RunCtor(Allocator* raw_allocator, T* p, size_t n) {
67 static_assert(is_simple_type<T>::value, "T is not a simple type.");
68 }
69
70 template <typename T>
71 static void RunDtor(Allocator* raw_allocator, T* p, size_t n) {}
72
73 static void RunVariantCtor(Variant* p, size_t n);
74
75 static void RunVariantDtor(Variant* p, size_t n);
76};
77
78template <>
79/* static */
80inline void TypedAllocator::RunCtor(Allocator* raw_allocator, tstring* p,
81 size_t n) {
82 if (!raw_allocator->AllocatesOpaqueHandle()) {
83 for (size_t i = 0; i < n; ++p, ++i) new (p) tstring();
84 }
85}
86
87template <>
88/* static */
89inline void TypedAllocator::RunDtor(Allocator* raw_allocator, tstring* p,
90 size_t n) {
91 if (!raw_allocator->AllocatesOpaqueHandle()) {
92 for (size_t i = 0; i < n; ++p, ++i) p->~tstring();
93 }
94}
95
96template <>
97/* static */
98inline void TypedAllocator::RunCtor(Allocator* raw_allocator, ResourceHandle* p,
99 size_t n) {
100 if (!raw_allocator->AllocatesOpaqueHandle()) {
101 for (size_t i = 0; i < n; ++p, ++i) new (p) ResourceHandle();
102 }
103}
104
105template <>
106/* static */
107inline void TypedAllocator::RunDtor(Allocator* raw_allocator, ResourceHandle* p,
108 size_t n) {
109 if (!raw_allocator->AllocatesOpaqueHandle()) {
110 for (size_t i = 0; i < n; ++p, ++i) p->~ResourceHandle();
111 }
112}
113
114template <>
115/* static */
116inline void TypedAllocator::RunCtor(Allocator* raw_allocator, Variant* p,
117 size_t n) {
118 if (!raw_allocator->AllocatesOpaqueHandle()) {
119 RunVariantCtor(p, n);
120 }
121}
122
123template <>
124/* static */
125inline void TypedAllocator::RunDtor(Allocator* raw_allocator, Variant* p,
126 size_t n) {
127 if (!raw_allocator->AllocatesOpaqueHandle()) {
128 RunVariantDtor(p, n);
129 }
130}
131
132} // namespace tensorflow
133
134#endif // TENSORFLOW_CORE_FRAMEWORK_TYPED_ALLOCATOR_H_
135