tiny_dnn 1.0.0
A header only, dependency-free deep learning framework in C++11
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deserialization_helper.h
1/*
2 Copyright (c) 2016, Taiga Nomi
3 All rights reserved.
4
5 Redistribution and use in source and binary forms, with or without
6 modification, are permitted provided that the following conditions are met:
7 * Redistributions of source code must retain the above copyright
8 notice, this list of conditions and the following disclaimer.
9 * Redistributions in binary form must reproduce the above copyright
10 notice, this list of conditions and the following disclaimer in the
11 documentation and/or other materials provided with the distribution.
12 * Neither the name of the tiny-dnn nor the
13 names of its contributors may be used to endorse or promote products
14 derived from this software without specific prior written permission.
15
16 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
17 EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
18 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
19 DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
20 DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
21 (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
22 LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
23 ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
24 (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
25 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
26*/
27#pragma once
28#include <typeindex>
29#include <map>
30#include <functional>
31#include <memory>
32#include <string>
33#include <cereal/archives/json.hpp>
34#include <cereal/types/memory.hpp>
35#include "tiny_dnn/util/nn_error.h"
36#include "tiny_dnn/util/macro.h"
37#include "tiny_dnn/layers/layers.h"
38
39namespace tiny_dnn {
40
41template <typename InputArchive>
43public:
44 void register_loader(const std::string& name, std::function<std::shared_ptr<layer>(InputArchive&)> func) {
45 loaders_[name] = [=](void* ar) {
46 return func(*reinterpret_cast<InputArchive*>(ar));
47 };
48 }
49
50 template <typename T>
51 void register_type(const std::string& name) {
52 type_names_[typeid(T)] = name;
53 }
54
55 std::shared_ptr<layer> load(const std::string& layer_name, InputArchive& ar) {
56 check_if_enabled();
57
58 if (loaders_.find(layer_name) == loaders_.end()) {
59 throw nn_error("Failed to generate layer. Generator for " + layer_name + " is not found.\n"
60 "Please use CNN_REGISTER_LAYER_DESERIALIZER macro to register appropriate generator");
61 }
62
63 return loaders_[layer_name](reinterpret_cast<void*>(&ar));
64 }
65
66 const std::string& type_name(std::type_index index) const {
67 if (type_names_.find(index) == type_names_.end()) {
68 throw nn_error("Typename is not registered");
69 }
70 return type_names_.at(index);
71 }
72
73 static deserialization_helper& get_instance() {
75 return instance;
76 }
77
78private:
79 void check_if_enabled() const {
80#ifdef CNN_NO_SERIALIZATION
81 static_assert(sizeof(InputArchive)==0,
82 "You are using load functions, but deserialization function is disabled in current configuration.\n\n"
83 "You need to undef CNN_NO_SERIALIZATION to enable these functions.\n"
84 "If you are using cmake, you can use -DUSE_SERIALIZER=ON option.\n\n");
85#endif
86 }
87
89 std::map<std::string, std::function<std::shared_ptr<layer>(void*)>> loaders_;
90
91 std::map<std::type_index, std::string> type_names_;
92
93 template <typename T>
94 static std::shared_ptr<layer> load_layer_impl(InputArchive& ia);
95
96#define CNN_REGISTER_LAYER_BODY(layer_type, layer_name) \
97 register_loader(layer_name, load_layer_impl<layer_type>);\
98 register_type<layer_type>(layer_name);
99
100#define CNN_REGISTER_LAYER(layer_type, layer_name) CNN_REGISTER_LAYER_BODY(layer_type, #layer_name)
101
102#define CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, activation_type, layer_name) \
103CNN_REGISTER_LAYER_BODY(layer_type<activation::activation_type>, #layer_name "<" #activation_type ">")
104
105#define CNN_REGISTER_LAYER_WITH_ACTIVATIONS(layer_type, layer_name) \
106CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, tan_h, layer_name); \
107CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, softmax, layer_name); \
108CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, identity, layer_name); \
109CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, sigmoid, layer_name); \
110CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, relu, layer_name); \
111CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, leaky_relu, layer_name); \
112CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, elu, layer_name); \
113CNN_REGISTER_LAYER_WITH_ACTIVATION(layer_type, tan_hp1m2, layer_name)
114
116#include "serialization_layer_list.h"
117 }
118
119#undef CNN_REGISTER_LAYER_BODY
120#undef CNN_REGISTER_LAYER
121#undef CNN_REGISTER_LAYER_WITH_ACTIVATION
122#undef CNN_REGISTER_LAYER_WITH_ACTIVATIONS
123
124}; // class deserialization_helper
125
126template <typename InputArchive>
127template <typename T>
129
130 using ST = typename std::aligned_storage<sizeof(T), CNN_ALIGNOF(T)>::type;
131
132 std::unique_ptr<ST> bn(new ST());
133
134 cereal::memory_detail::LoadAndConstructLoadWrapper<InputArchive, T> wrapper(reinterpret_cast<T*>(bn.get()));
135
136 wrapper.CEREAL_SERIALIZE_FUNCTION_NAME(ia);
137
138 std::shared_ptr<layer> t;
139 t.reset(reinterpret_cast<T*>(bn.get()));
140 bn.release();
141
142 return t;
143}
144
145template <typename T>
146void start_loading_layer(T & ar) {}
147
148template <typename T>
149void finish_loading_layer(T & ar) {}
150
151inline void start_loading_layer(cereal::JSONInputArchive & ia) { ia.startNode(); }
152
153inline void finish_loading_layer(cereal::JSONInputArchive & ia) { ia.finishNode(); }
154
158template <typename InputArchive>
159std::shared_ptr<layer> layer::load_layer(InputArchive & ia) {
160 start_loading_layer(ia);
161
162 std::string p;
163 ia(cereal::make_nvp("type", p));
165
166 finish_loading_layer(ia);
167
168 return l;
169}
170
171} // namespace tiny_dnn
Definition deserialization_helper.h:42
Simple image utility class.
Definition image.h:94
static std::shared_ptr< layer > load_layer(InputArchive &ia)
generate layer from cereal's Archive
Definition deserialization_helper.h:159
error exception class for tiny-dnn
Definition nn_error.h:37