├── .gitattributes
├── .idea
├── Reinforcement_CPP.iml
├── customTargets.xml
├── misc.xml
├── modules.xml
├── vcs.xml
└── workspace.xml
├── CMakeLists.txt
├── ExperienceReplay.cpp
├── ExperienceReplay.h
├── PrioritizedExperienceReplay.cpp
├── PrioritizedExperienceReplay.h
├── README.md
├── Trainer.cpp
├── Trainer.h
├── assets
├── dqn_pong_results.png
└── pong_dqn.gif
├── atari_roms
├── adventure.bin
├── air_raid.bin
├── alien.bin
├── amidar.bin
├── assault.bin
├── asterix.bin
├── asteroids.bin
├── atlantis.bin
├── bank_heist.bin
├── battle_zone.bin
├── beam_rider.bin
├── berzerk.bin
├── bowling.bin
├── boxing.bin
├── breakout.bin
├── carnival.bin
├── centipede.bin
├── chopper_command.bin
├── crazy_climber.bin
├── defender.bin
├── demon_attack.bin
├── double_dunk.bin
├── elevator_action.bin
├── enduro.bin
├── fishing_derby.bin
├── freeway.bin
├── frostbite.bin
├── gopher.bin
├── gravitar.bin
├── hero.bin
├── ice_hockey.bin
├── jamesbond.bin
├── journey_escape.bin
├── kaboom.bin
├── kangaroo.bin
├── krull.bin
├── kung_fu_master.bin
├── montezuma_revenge.bin
├── ms_pacman.bin
├── name_this_game.bin
├── phoenix.bin
├── pitfall.bin
├── pong.bin
├── pooyan.bin
├── private_eye.bin
├── qbert.bin
├── riverraid.bin
├── road_runner.bin
├── robotank.bin
├── seaquest.bin
├── skiing.bin
├── solaris.bin
├── space_invaders.bin
├── star_gunner.bin
├── tennis.bin
├── time_pilot.bin
├── tutankham.bin
├── up_n_down.bin
├── venture.bin
├── video_pinball.bin
├── wizard_of_wor.bin
├── yars_revenge.bin
└── zaxxon.bin
├── build
├── .DS_Store
├── CMakeCache.txt
├── CMakeFiles
│ ├── 3.14.5
│ │ ├── CMakeCXXCompiler.cmake
│ │ ├── CMakeDetermineCompilerABI_CXX.bin
│ │ ├── CMakeSystem.cmake
│ │ └── CompilerIdCXX
│ │ │ ├── CMakeCXXCompilerId.cpp
│ │ │ └── a.out
│ ├── CMakeDirectoryInformation.cmake
│ ├── CMakeOutput.log
│ ├── Makefile.cmake
│ ├── Makefile2
│ ├── Reinforcement_CPP.dir
│ │ ├── CXX.includecache
│ │ ├── DependInfo.cmake
│ │ ├── ExperienceReplay.cpp.o
│ │ ├── Trainer.cpp.o
│ │ ├── build.make
│ │ ├── cmake_clean.cmake
│ │ ├── depend.internal
│ │ ├── depend.make
│ │ ├── dqn.cpp.o
│ │ ├── flags.make
│ │ ├── link.txt
│ │ ├── main.cpp.o
│ │ ├── progress.make
│ │ └── test_network.cpp.o
│ ├── TargetDirectories.txt
│ ├── cmake.check_cache
│ ├── feature_tests.bin
│ ├── feature_tests.cxx
│ └── progress.marks
├── Makefile
├── Reinforcement_CPP
├── cmake_install.cmake
├── game_screen.png
├── lib.macosx-10.6-x86_64-3.5
│ └── dqn.cpython-35m-darwin.so
└── temp.macosx-10.6-x86_64-3.5
│ └── Trainer.o
├── categorical_dqn.h
├── dqn.cpp
├── dqn.h
├── main.cpp
└── noisy.h
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/CMakeLists.txt:
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1 | cmake_minimum_required(VERSION 3.14)
2 | project(Reinforcement_CPP
3 | LANGUAGES CXX
4 | VERSION 1.0.0
5 | DESCRIPTION "Reinforcement learning in C++ using PyTorch"
6 | )
7 |
8 | set(CMAKE_CXX_STANDARD 17)
9 |
10 | set(Torch_DIR /Users/navneetmadhukumar/Downloads/libtorch/share/cmake/Torch)
11 |
12 |
13 | set(CPPRL_INCLUDE_DIRS
14 | include
15 | src
16 | )
17 |
18 | find_package(Torch REQUIRED)
19 |
20 | add_executable(Reinforcement_CPP main.cpp ExperienceReplay.cpp ExperienceReplay.h dqn.cpp Trainer.cpp dqn.h Trainer.h PrioritizedExperienceReplay.cpp PrioritizedExperienceReplay.h noisy.h categorical_dqn.h)
21 |
22 |
23 | include_directories(${CPPRL_INCLUDE_DIRS})
24 |
25 | find_library(LIBALE libale.so /Users/navneetmadhukumar/Downloads/Arcade-Learning-Environment-master/)
26 | target_link_libraries(Reinforcement_CPP ${LIBALE} ${TORCH_LIBRARIES} )
27 |
--------------------------------------------------------------------------------
/ExperienceReplay.cpp:
--------------------------------------------------------------------------------
1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-08.
3 | //
4 |
5 | #include "ExperienceReplay.h"
6 | #include
7 | #include
8 | #include
9 |
10 | #include
11 | #include
12 |
13 |
14 | #include
15 | #include
16 | #include
17 |
18 |
19 | ExperienceReplay::ExperienceReplay(int64_t size) {
20 |
21 | capacity = size;
22 | }
23 |
24 | void ExperienceReplay::push(torch::Tensor state,torch::Tensor new_state,torch::
25 | Tensor action,torch::Tensor done,torch::Tensor reward){
26 |
27 | std::tuple sample (state, new_state, action, reward, done);
28 | if (buffer.size() < capacity){
29 | buffer.push_back(sample);
30 | }
31 | else {
32 | while (buffer.size() >= capacity) {
33 | buffer.pop_front();
34 | }
35 | buffer.push_back(sample);
36 | }
37 | }
38 |
39 | std::vector> ExperienceReplay::sample_queue(
40 | int64_t batch_size){
41 | std::vector> b(batch_size);
42 | std::sample(buffer.begin(), buffer.end(),
43 | b.begin(), b.size(),
44 | std::mt19937{std::random_device{}()});
45 | return b;
46 | }
47 |
48 | int64_t ExperienceReplay::size_buffer(){
49 |
50 | return buffer.size();
51 | }
52 |
--------------------------------------------------------------------------------
/ExperienceReplay.h:
--------------------------------------------------------------------------------
1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-08.
3 | //
4 | #pragma once
5 |
6 | #include
7 | #include
8 | #include
9 | #include
10 |
11 |
12 | #include
13 | #include
14 | #include
15 |
16 | class ExperienceReplay{
17 |
18 | private: int64_t capacity;
19 | public: std::deque> buffer;
20 |
21 | public:
22 | ExperienceReplay (int64_t capacity);
23 | void push(torch::Tensor state,torch::Tensor new_state,torch::
24 | Tensor action,torch::Tensor done,torch::Tensor reward);
25 | int64_t size_buffer();
26 | std::vector> sample_queue(int64_t batch_size);
27 |
28 |
29 | };
--------------------------------------------------------------------------------
/PrioritizedExperienceReplay.cpp:
--------------------------------------------------------------------------------
1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-18.
3 | //
4 |
5 |
6 |
7 | //
8 | // Created by Navneet Madhu Kumar on 2019-07-08.
9 | //
10 | #include "PrioritizedExperienceReplay.h"
11 | #include
12 | #include
13 | #include
14 |
15 | #include
16 | #include
17 |
18 |
19 | #include
20 | #include
21 | #include
22 |
23 |
24 | PrioritizedExperienceReplay::PrioritizedExperienceReplay(int64_t size) {
25 | capacity = size;
26 | }
27 |
28 | void PrioritizedExperienceReplay::push(torch::Tensor state,torch::Tensor new_state,torch::
29 | Tensor action,torch::Tensor done,torch::Tensor reward, float_t td_error, int64_t ind){
30 | float_t error(td_error);
31 | int64_t index(ind);
32 | std::tuple sample (state, new_state, action, reward, done);
33 | element sample_struct(error, index, sample);
34 |
35 | if (buffer.size() < capacity){
36 | buffer.push(sample_struct);
37 | }
38 | else {
39 | while (buffer.size() >= capacity) {
40 | buffer.pop();
41 | }
42 | buffer.push(sample_struct);
43 | }
44 | }
45 |
46 | std::vector>
47 | PrioritizedExperienceReplay::sample_queue(
48 | int64_t batch_size){
49 | std::vector> b(batch_size);
50 | while (batch_size > 0 and buffer.size() > 0){
51 | element s = buffer.top();
52 | buffer.pop();
53 | std::tuple sample = s.transition;
54 | b.push_back(sample);
55 | }
56 | return b;
57 | }
58 |
59 | int64_t PrioritizedExperienceReplay::size_buffer(){
60 |
61 | return buffer.size();
62 | }
63 |
--------------------------------------------------------------------------------
/PrioritizedExperienceReplay.h:
--------------------------------------------------------------------------------
1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-18.
3 | //
4 |
5 |
6 | #pragma once
7 |
8 | #include
9 | #include
10 | #include
11 | #include
12 |
13 |
14 | #include
15 | #include
16 | #include
17 |
18 | struct element{
19 | float_t td_error;
20 | int64_t index;
21 | std::tuple transition;
22 |
23 | element(float_t error, int64_t ind,
24 | std::tuple trans):
25 | td_error(error),
26 | index(ind),
27 | transition(trans)
28 | {}
29 |
30 | bool operator<(const struct element& other) const{
31 | if (td_error != other.td_error){
32 | return td_error < other.td_error;
33 | }else{
34 | return index < other.index;
35 | }
36 | }
37 | };
38 |
39 | class PrioritizedExperienceReplay{
40 |
41 | private: int64_t capacity;
42 |
43 | public: std::priority_queue buffer;
44 |
45 | public:
46 | PrioritizedExperienceReplay (int64_t capacity);
47 | void push(torch::Tensor state,torch::Tensor new_state,torch::
48 | Tensor action,torch::Tensor done,torch::Tensor reward, float_t td_error, int64_t index);
49 | int64_t size_buffer();
50 | std::vector> sample_queue(int64_t batch_size);
51 |
52 |
53 | };
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Pytorch-RL-CPP
2 |
3 |
4 | A Repository with C++ implementations of Reinforcement Learning Algorithms (Pytorch)
5 |
6 |
7 |
8 |
9 | **RlCpp is a reinforcement learning framework, written using the [PyTorch C++ frontend](https://pytorch.org/cppdocs/frontend.html).**
10 |
11 | RlCpp aims to be an extensible, reasonably optimized, production-ready framework for using reinforcement learning in projects where Python isn't viable. It should be ready to use in desktop applications on
12 | user's computers with minimal setup required on the user's side.
13 |
14 | The Environment used is the C++ Port of [Arcade Learning Environment](https://github.com/mgbellemare/Arcade-Learning-Environment)
15 |
16 | # Currently Supported Models
17 | The deep reinforcement learning community has made several independent improvements to the DQN algorithm. This repository presents latest extensions to the DQN algorithm:
18 |
19 | 1. Playing Atari with Deep Reinforcement Learning [[arxiv]](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf)
20 | 2. Deep Reinforcement Learning with Double Q-learning [[arxiv]](https://arxiv.org/abs/1509.06461)
21 | 3. Dueling Network Architectures for Deep Reinforcement Learning [[arxiv]](https://arxiv.org/abs/1511.06581)
22 | 4. Prioritized Experience Replay [[arxiv]](https://arxiv.org/abs/1511.05952)
23 | 5. Noisy Networks for Exploration [[arxiv]](https://arxiv.org/abs/1706.10295)
24 | 6. A Distributional Perspective on Reinforcement Learning [[arxiv]](https://arxiv.org/pdf/1707.06887.pdf)
25 | 7. Rainbow: Combining Improvements in Deep Reinforcement Learning [[arxiv]](https://arxiv.org/abs/1710.02298)
26 | 8. Distributional Reinforcement Learning with Quantile Regression [[arxiv]](https://arxiv.org/pdf/1710.10044.pdf)
27 | 9. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation [[arxiv]](https://arxiv.org/abs/1604.06057)
28 | 10. Neural Episodic Control [[arxiv]](https://arxiv.org/pdf/1703.01988.pdf)
29 |
30 | # Results for Pong using Double DQN
31 |
32 |
33 |
34 | # Environments (All Atari Environments)
35 | 1. Breakout
36 | 2. Pong
37 | 3. Montezuma's Revenge (Current Research)
38 | 4. Pitfall
39 | 5. Gravitar
40 | 6. CarRacing
41 |
42 |
43 | # Installing the dependencies
44 |
45 | # Arcade Learning Environment
46 |
47 | Install main dependences:
48 | ```
49 | sudo apt-get install libsdl1.2-dev libsdl-gfx1.2-dev libsdl-image1.2-dev cmake
50 | ```
51 |
52 | Compilation:
53 |
54 | ```
55 | $ mkdir build && cd build
56 | $ cmake -DUSE_SDL=ON -DUSE_RLGLUE=OFF -DBUILD_EXAMPLES=ON ..
57 | $ make -j 4
58 | ```
59 |
60 | To install python module:
61 |
62 | ```
63 | $ pip install .
64 | or
65 | $ pip install --user .
66 | ```
67 |
68 | Getting the ALE to work on Visual Studio requires a bit of extra wrangling. You may wish to use IslandMan93's [Visual Studio port of the ALE.](https://github.com/Islandman93/Arcade-Learning-Environment)
69 |
70 | To ask questions and discuss, please join the [ALE-users group](https://groups.google.com/forum/#!forum/arcade-learning-environment).
71 |
72 | # Libtorch
73 |
74 | ## Building
75 | CMake is used for the build system.
76 | Most dependencies are included as submodules (run `git submodule update --init --recursive` to get them).
77 | Libtorch has to be [installed seperately](https://pytorch.org/cppdocs/installing.html).
78 |
79 | ```bash
80 | cd Reinforcement_CPP
81 | cd build
82 | cmake ..
83 | make -j4
84 | ```
85 |
86 | Before running, make sure to add `libtorch/lib` to your `PATH` environment variable.
87 |
88 | ## Changes to cmake file
89 |
90 | The CMake file requires some changes for things to run smoothly.
91 | 1. After building ALE, link the libale.so
92 | 2. Set torch dir, after building libtorch.
93 | Refer to the current CMakeLists.txt and make the relevant changes.
94 |
95 | # Future Plans
96 | Plans to support:
97 | 1. Runtime differences between C++ and Python.
98 | 2. Python bindings for the Trainer module.
99 | 3. More models and methods.
100 | 4. Support for mujoco environment.
101 |
102 | Stay tuned !
103 |
104 |
105 |
106 |
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/Trainer.cpp:
--------------------------------------------------------------------------------
1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-10.
3 | //
4 | #include "Trainer.h"
5 | #include "dqn.h"
6 | #include "ExperienceReplay.h"
7 | #include "/Users/navneetmadhukumar/Downloads/Arcade-Learning-Environment-master/src/ale_interface.hpp"
8 | #include
9 | #include
10 |
11 |
12 | Trainer::Trainer(int64_t input_channels, int64_t num_actions, int64_t capacity):
13 | buffer(capacity),
14 | network(input_channels, num_actions),
15 | target_network(input_channels, num_actions),
16 | dqn_optimizer(
17 | network.parameters(), torch::optim::AdamOptions(0.0001).beta1(0.5)){}
18 |
19 | torch::Tensor Trainer::compute_td_loss(int64_t batch_size, float gamma){
20 | std::vector> batch =
21 | buffer.sample_queue(batch_size);
22 |
23 | std::vector states;
24 | std::vector new_states;
25 | std::vector actions;
26 | std::vector rewards;
27 | std::vector dones;
28 |
29 | for (auto i : batch){
30 | states.push_back(std::get<0>(i));
31 | new_states.push_back(std::get<1>(i));
32 | actions.push_back(std::get<2>(i));
33 | rewards.push_back(std::get<3>(i));
34 | dones.push_back(std::get<4>(i));
35 | }
36 |
37 |
38 | torch::Tensor states_tensor;
39 | torch::Tensor new_states_tensor;
40 | torch::Tensor actions_tensor;
41 | torch::Tensor rewards_tensor;
42 | torch::Tensor dones_tensor;
43 |
44 | states_tensor = torch::cat(states, 0);
45 | new_states_tensor = torch::cat(new_states, 0);
46 | actions_tensor = torch::cat(actions, 0);
47 | rewards_tensor = torch::cat(rewards, 0);
48 | dones_tensor = torch::cat(dones, 0);
49 |
50 |
51 | torch::Tensor q_values = network.forward(states_tensor);
52 | torch::Tensor next_target_q_values = target_network.forward(new_states_tensor);
53 | torch::Tensor next_q_values = network.forward(new_states_tensor);
54 |
55 | actions_tensor = actions_tensor.to(torch::kInt64);
56 |
57 | torch::Tensor q_value = q_values.gather(1, actions_tensor.unsqueeze(1)).squeeze(1);
58 | torch::Tensor maximum = std::get<1>(next_q_values.max(1));
59 | torch::Tensor next_q_value = next_target_q_values.gather(1, maximum.unsqueeze(1)).squeeze(1);
60 | torch::Tensor expected_q_value = rewards_tensor + gamma*next_q_value*(1-dones_tensor);
61 | torch::Tensor loss = torch::mse_loss(q_value, expected_q_value);
62 |
63 | dqn_optimizer.zero_grad();
64 | loss.backward();
65 | dqn_optimizer.step();
66 |
67 | return loss;
68 |
69 | }
70 |
71 | void Trainer::load_enviroment(int64_t random_seed, std::string rom_path){
72 | ale.setInt("random_seed", random_seed);
73 | ale.setBool("display_screen", true);
74 | ale.loadROM(rom_path);
75 |
76 | }
77 |
78 | double Trainer::epsilon_by_frame(int64_t frame_id){
79 | return epsilon_final + (epsilon_start - epsilon_final) * exp(-1. * frame_id / epsilon_decay);
80 | }
81 |
82 | torch::Tensor Trainer::get_tensor_observation(std::vector state) {
83 | std::vector state_int;
84 | state_int.reserve(state.size());
85 |
86 | for (int i=0; icopy_(val.value());
105 | } else {
106 | t = buffers.find(name);
107 | if (t != nullptr) {
108 | t->copy_(val.value());
109 | }
110 | }
111 | }
112 | }
113 |
114 | void Trainer::train(int64_t random_seed, std::string rom_path, int64_t num_epochs){
115 | load_enviroment(random_seed, rom_path);
116 | ActionVect legal_actions = ale.getLegalActionSet();
117 | ale.reset_game();
118 | std::vector state;
119 | ale.getScreenRGB(state);
120 | float episode_reward = 0.0;
121 | std::vector all_rewards;
122 | std::vector losses;
123 | auto start = std::chrono::high_resolution_clock::now();
124 | for(int i=1; i<=num_epochs; i++){
125 | double epsilon = epsilon_by_frame(i);
126 | auto r = ((double) rand() / (RAND_MAX));
127 | torch::Tensor state_tensor = get_tensor_observation(state);
128 | Action a;
129 | if (r <= epsilon){
130 | a = legal_actions[rand() % legal_actions.size()];
131 | }
132 | else{
133 | torch::Tensor action_tensor = network.act(state_tensor);
134 | int64_t index = action_tensor[0].item();
135 | a = legal_actions[index];
136 |
137 | }
138 |
139 | float reward = ale.act(a);
140 | episode_reward += reward;
141 | std::vector new_state;
142 | ale.getScreenRGB(new_state);
143 | torch::Tensor new_state_tensor = get_tensor_observation(new_state);
144 | bool done = ale.game_over();
145 |
146 | torch::Tensor reward_tensor = torch::tensor(reward);
147 | torch::Tensor done_tensor = torch::tensor(done);
148 | done_tensor = done_tensor.to(torch::kFloat32);
149 | torch::Tensor action_tensor_new = torch::tensor(a);
150 |
151 | buffer.push(state_tensor, new_state_tensor, action_tensor_new, done_tensor, reward_tensor);
152 | state = new_state;
153 |
154 | if (done){
155 | ale.reset_game();
156 | std::vector state;
157 | ale.getScreenRGB(state);
158 | all_rewards.push_back(episode_reward);
159 | episode_reward = 0.0;
160 | }
161 |
162 | if (buffer.size_buffer() >= 10000){
163 | torch::Tensor loss = compute_td_loss(batch_size, gamma);
164 | losses.push_back(loss);
165 | }
166 |
167 | if (i%1000==0){
168 | std::cout<(stop - start);
175 | std::cout << "Time taken by function: "
176 | << duration.count() << " microseconds" << std::endl;
177 |
178 |
179 | }
180 |
181 |
182 |
183 |
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/Trainer.h:
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1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-12.
3 | //
4 | #pragma once
5 |
6 | #include
7 |
8 | #include "ExperienceReplay.h"
9 | #include "dqn.h"
10 | #include "/Users/navneetmadhukumar/Downloads/Arcade-Learning-Environment-master/src/ale_interface.hpp"
11 |
12 |
13 |
14 | class Trainer{
15 |
16 | private: ExperienceReplay buffer;
17 | private: DQN network, target_network;
18 | private: torch::optim::Adam dqn_optimizer;
19 | private: ALEInterface ale;
20 | private: double epsilon_start = 1.0;
21 | private: double epsilon_final = 0.01;
22 | private: int64_t epsilon_decay = 30000;
23 | private: int64_t batch_size = 32;
24 | private: float gamma = 0.99;
25 |
26 | public:
27 | Trainer(int64_t input_channels, int64_t num_actions, int64_t capacity);
28 | torch::Tensor compute_td_loss(int64_t batch_size, float gamma);
29 | void load_enviroment(int64_t random_seed, std::string rom_path);
30 | double epsilon_by_frame(int64_t frame_id);
31 | torch::Tensor get_tensor_observation(std::vector state);
32 | void loadstatedict(torch::nn::Module& model,
33 | torch::nn::Module& target_model);
34 | void train(int64_t random_seed, std::string rom_path, int64_t num_epochs);
35 |
36 |
37 |
38 |
39 |
40 | };
41 |
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1 | # This is the CMakeCache file.
2 | # For build in directory: /Users/navneetmadhukumar/CLionProjects/Reinforcement_CPP/build
3 | # It was generated by CMake: /usr/local/Cellar/cmake/3.14.5/bin/cmake
4 | # You can edit this file to change values found and used by cmake.
5 | # If you do not want to change any of the values, simply exit the editor.
6 | # If you do want to change a value, simply edit, save, and exit the editor.
7 | # The syntax for the file is as follows:
8 | # KEY:TYPE=VALUE
9 | # KEY is the name of a variable in the cache.
10 | # TYPE is a hint to GUIs for the type of VALUE, DO NOT EDIT TYPE!.
11 | # VALUE is the current value for the KEY.
12 |
13 | ########################
14 | # EXTERNAL cache entries
15 | ########################
16 |
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2 | set(CMAKE_HOST_SYSTEM_NAME "Darwin")
3 | set(CMAKE_HOST_SYSTEM_VERSION "18.7.0")
4 | set(CMAKE_HOST_SYSTEM_PROCESSOR "x86_64")
5 |
6 |
7 |
8 | set(CMAKE_SYSTEM "Darwin-18.7.0")
9 | set(CMAKE_SYSTEM_NAME "Darwin")
10 | set(CMAKE_SYSTEM_VERSION "18.7.0")
11 | set(CMAKE_SYSTEM_PROCESSOR "x86_64")
12 |
13 | set(CMAKE_CROSSCOMPILING "FALSE")
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15 | set(CMAKE_SYSTEM_LOADED 1)
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1 | /* This source file must have a .cpp extension so that all C++ compilers
2 | recognize the extension without flags. Borland does not know .cxx for
3 | example. */
4 | #ifndef __cplusplus
5 | # error "A C compiler has been selected for C++."
6 | #endif
7 |
8 |
9 | /* Version number components: V=Version, R=Revision, P=Patch
10 | Version date components: YYYY=Year, MM=Month, DD=Day */
11 |
12 | #if defined(__COMO__)
13 | # define COMPILER_ID "Comeau"
14 | /* __COMO_VERSION__ = VRR */
15 | # define COMPILER_VERSION_MAJOR DEC(__COMO_VERSION__ / 100)
16 | # define COMPILER_VERSION_MINOR DEC(__COMO_VERSION__ % 100)
17 |
18 | #elif defined(__INTEL_COMPILER) || defined(__ICC)
19 | # define COMPILER_ID "Intel"
20 | # if defined(_MSC_VER)
21 | # define SIMULATE_ID "MSVC"
22 | # endif
23 | /* __INTEL_COMPILER = VRP */
24 | # define COMPILER_VERSION_MAJOR DEC(__INTEL_COMPILER/100)
25 | # define COMPILER_VERSION_MINOR DEC(__INTEL_COMPILER/10 % 10)
26 | # if defined(__INTEL_COMPILER_UPDATE)
27 | # define COMPILER_VERSION_PATCH DEC(__INTEL_COMPILER_UPDATE)
28 | # else
29 | # define COMPILER_VERSION_PATCH DEC(__INTEL_COMPILER % 10)
30 | # endif
31 | # if defined(__INTEL_COMPILER_BUILD_DATE)
32 | /* __INTEL_COMPILER_BUILD_DATE = YYYYMMDD */
33 | # define COMPILER_VERSION_TWEAK DEC(__INTEL_COMPILER_BUILD_DATE)
34 | # endif
35 | # if defined(_MSC_VER)
36 | /* _MSC_VER = VVRR */
37 | # define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100)
38 | # define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100)
39 | # endif
40 |
41 | #elif defined(__PATHCC__)
42 | # define COMPILER_ID "PathScale"
43 | # define COMPILER_VERSION_MAJOR DEC(__PATHCC__)
44 | # define COMPILER_VERSION_MINOR DEC(__PATHCC_MINOR__)
45 | # if defined(__PATHCC_PATCHLEVEL__)
46 | # define COMPILER_VERSION_PATCH DEC(__PATHCC_PATCHLEVEL__)
47 | # endif
48 |
49 | #elif defined(__BORLANDC__) && defined(__CODEGEARC_VERSION__)
50 | # define COMPILER_ID "Embarcadero"
51 | # define COMPILER_VERSION_MAJOR HEX(__CODEGEARC_VERSION__>>24 & 0x00FF)
52 | # define COMPILER_VERSION_MINOR HEX(__CODEGEARC_VERSION__>>16 & 0x00FF)
53 | # define COMPILER_VERSION_PATCH DEC(__CODEGEARC_VERSION__ & 0xFFFF)
54 |
55 | #elif defined(__BORLANDC__)
56 | # define COMPILER_ID "Borland"
57 | /* __BORLANDC__ = 0xVRR */
58 | # define COMPILER_VERSION_MAJOR HEX(__BORLANDC__>>8)
59 | # define COMPILER_VERSION_MINOR HEX(__BORLANDC__ & 0xFF)
60 |
61 | #elif defined(__WATCOMC__) && __WATCOMC__ < 1200
62 | # define COMPILER_ID "Watcom"
63 | /* __WATCOMC__ = VVRR */
64 | # define COMPILER_VERSION_MAJOR DEC(__WATCOMC__ / 100)
65 | # define COMPILER_VERSION_MINOR DEC((__WATCOMC__ / 10) % 10)
66 | # if (__WATCOMC__ % 10) > 0
67 | # define COMPILER_VERSION_PATCH DEC(__WATCOMC__ % 10)
68 | # endif
69 |
70 | #elif defined(__WATCOMC__)
71 | # define COMPILER_ID "OpenWatcom"
72 | /* __WATCOMC__ = VVRP + 1100 */
73 | # define COMPILER_VERSION_MAJOR DEC((__WATCOMC__ - 1100) / 100)
74 | # define COMPILER_VERSION_MINOR DEC((__WATCOMC__ / 10) % 10)
75 | # if (__WATCOMC__ % 10) > 0
76 | # define COMPILER_VERSION_PATCH DEC(__WATCOMC__ % 10)
77 | # endif
78 |
79 | #elif defined(__SUNPRO_CC)
80 | # define COMPILER_ID "SunPro"
81 | # if __SUNPRO_CC >= 0x5100
82 | /* __SUNPRO_CC = 0xVRRP */
83 | # define COMPILER_VERSION_MAJOR HEX(__SUNPRO_CC>>12)
84 | # define COMPILER_VERSION_MINOR HEX(__SUNPRO_CC>>4 & 0xFF)
85 | # define COMPILER_VERSION_PATCH HEX(__SUNPRO_CC & 0xF)
86 | # else
87 | /* __SUNPRO_CC = 0xVRP */
88 | # define COMPILER_VERSION_MAJOR HEX(__SUNPRO_CC>>8)
89 | # define COMPILER_VERSION_MINOR HEX(__SUNPRO_CC>>4 & 0xF)
90 | # define COMPILER_VERSION_PATCH HEX(__SUNPRO_CC & 0xF)
91 | # endif
92 |
93 | #elif defined(__HP_aCC)
94 | # define COMPILER_ID "HP"
95 | /* __HP_aCC = VVRRPP */
96 | # define COMPILER_VERSION_MAJOR DEC(__HP_aCC/10000)
97 | # define COMPILER_VERSION_MINOR DEC(__HP_aCC/100 % 100)
98 | # define COMPILER_VERSION_PATCH DEC(__HP_aCC % 100)
99 |
100 | #elif defined(__DECCXX)
101 | # define COMPILER_ID "Compaq"
102 | /* __DECCXX_VER = VVRRTPPPP */
103 | # define COMPILER_VERSION_MAJOR DEC(__DECCXX_VER/10000000)
104 | # define COMPILER_VERSION_MINOR DEC(__DECCXX_VER/100000 % 100)
105 | # define COMPILER_VERSION_PATCH DEC(__DECCXX_VER % 10000)
106 |
107 | #elif defined(__IBMCPP__) && defined(__COMPILER_VER__)
108 | # define COMPILER_ID "zOS"
109 | # if defined(__ibmxl__)
110 | # define COMPILER_VERSION_MAJOR DEC(__ibmxl_version__)
111 | # define COMPILER_VERSION_MINOR DEC(__ibmxl_release__)
112 | # define COMPILER_VERSION_PATCH DEC(__ibmxl_modification__)
113 | # define COMPILER_VERSION_TWEAK DEC(__ibmxl_ptf_fix_level__)
114 | # else
115 | /* __IBMCPP__ = VRP */
116 | # define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100)
117 | # define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10)
118 | # define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10)
119 | # endif
120 |
121 |
122 | #elif defined(__ibmxl__) || (defined(__IBMCPP__) && !defined(__COMPILER_VER__) && __IBMCPP__ >= 800)
123 | # define COMPILER_ID "XL"
124 | # if defined(__ibmxl__)
125 | # define COMPILER_VERSION_MAJOR DEC(__ibmxl_version__)
126 | # define COMPILER_VERSION_MINOR DEC(__ibmxl_release__)
127 | # define COMPILER_VERSION_PATCH DEC(__ibmxl_modification__)
128 | # define COMPILER_VERSION_TWEAK DEC(__ibmxl_ptf_fix_level__)
129 | # else
130 | /* __IBMCPP__ = VRP */
131 | # define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100)
132 | # define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10)
133 | # define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10)
134 | # endif
135 |
136 |
137 | #elif defined(__IBMCPP__) && !defined(__COMPILER_VER__) && __IBMCPP__ < 800
138 | # define COMPILER_ID "VisualAge"
139 | # if defined(__ibmxl__)
140 | # define COMPILER_VERSION_MAJOR DEC(__ibmxl_version__)
141 | # define COMPILER_VERSION_MINOR DEC(__ibmxl_release__)
142 | # define COMPILER_VERSION_PATCH DEC(__ibmxl_modification__)
143 | # define COMPILER_VERSION_TWEAK DEC(__ibmxl_ptf_fix_level__)
144 | # else
145 | /* __IBMCPP__ = VRP */
146 | # define COMPILER_VERSION_MAJOR DEC(__IBMCPP__/100)
147 | # define COMPILER_VERSION_MINOR DEC(__IBMCPP__/10 % 10)
148 | # define COMPILER_VERSION_PATCH DEC(__IBMCPP__ % 10)
149 | # endif
150 |
151 |
152 | #elif defined(__PGI)
153 | # define COMPILER_ID "PGI"
154 | # define COMPILER_VERSION_MAJOR DEC(__PGIC__)
155 | # define COMPILER_VERSION_MINOR DEC(__PGIC_MINOR__)
156 | # if defined(__PGIC_PATCHLEVEL__)
157 | # define COMPILER_VERSION_PATCH DEC(__PGIC_PATCHLEVEL__)
158 | # endif
159 |
160 | #elif defined(_CRAYC)
161 | # define COMPILER_ID "Cray"
162 | # define COMPILER_VERSION_MAJOR DEC(_RELEASE_MAJOR)
163 | # define COMPILER_VERSION_MINOR DEC(_RELEASE_MINOR)
164 |
165 | #elif defined(__TI_COMPILER_VERSION__)
166 | # define COMPILER_ID "TI"
167 | /* __TI_COMPILER_VERSION__ = VVVRRRPPP */
168 | # define COMPILER_VERSION_MAJOR DEC(__TI_COMPILER_VERSION__/1000000)
169 | # define COMPILER_VERSION_MINOR DEC(__TI_COMPILER_VERSION__/1000 % 1000)
170 | # define COMPILER_VERSION_PATCH DEC(__TI_COMPILER_VERSION__ % 1000)
171 |
172 | #elif defined(__FUJITSU) || defined(__FCC_VERSION) || defined(__fcc_version)
173 | # define COMPILER_ID "Fujitsu"
174 |
175 | #elif defined(__ghs__)
176 | # define COMPILER_ID "GHS"
177 | /* __GHS_VERSION_NUMBER = VVVVRP */
178 | # ifdef __GHS_VERSION_NUMBER
179 | # define COMPILER_VERSION_MAJOR DEC(__GHS_VERSION_NUMBER / 100)
180 | # define COMPILER_VERSION_MINOR DEC(__GHS_VERSION_NUMBER / 10 % 10)
181 | # define COMPILER_VERSION_PATCH DEC(__GHS_VERSION_NUMBER % 10)
182 | # endif
183 |
184 | #elif defined(__SCO_VERSION__)
185 | # define COMPILER_ID "SCO"
186 |
187 | #elif defined(__ARMCC_VERSION) && !defined(__clang__)
188 | # define COMPILER_ID "ARMCC"
189 | #if __ARMCC_VERSION >= 1000000
190 | /* __ARMCC_VERSION = VRRPPPP */
191 | # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/1000000)
192 | # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 100)
193 | # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000)
194 | #else
195 | /* __ARMCC_VERSION = VRPPPP */
196 | # define COMPILER_VERSION_MAJOR DEC(__ARMCC_VERSION/100000)
197 | # define COMPILER_VERSION_MINOR DEC(__ARMCC_VERSION/10000 % 10)
198 | # define COMPILER_VERSION_PATCH DEC(__ARMCC_VERSION % 10000)
199 | #endif
200 |
201 |
202 | #elif defined(__clang__) && defined(__apple_build_version__)
203 | # define COMPILER_ID "AppleClang"
204 | # if defined(_MSC_VER)
205 | # define SIMULATE_ID "MSVC"
206 | # endif
207 | # define COMPILER_VERSION_MAJOR DEC(__clang_major__)
208 | # define COMPILER_VERSION_MINOR DEC(__clang_minor__)
209 | # define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__)
210 | # if defined(_MSC_VER)
211 | /* _MSC_VER = VVRR */
212 | # define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100)
213 | # define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100)
214 | # endif
215 | # define COMPILER_VERSION_TWEAK DEC(__apple_build_version__)
216 |
217 | #elif defined(__clang__)
218 | # define COMPILER_ID "Clang"
219 | # if defined(_MSC_VER)
220 | # define SIMULATE_ID "MSVC"
221 | # endif
222 | # define COMPILER_VERSION_MAJOR DEC(__clang_major__)
223 | # define COMPILER_VERSION_MINOR DEC(__clang_minor__)
224 | # define COMPILER_VERSION_PATCH DEC(__clang_patchlevel__)
225 | # if defined(_MSC_VER)
226 | /* _MSC_VER = VVRR */
227 | # define SIMULATE_VERSION_MAJOR DEC(_MSC_VER / 100)
228 | # define SIMULATE_VERSION_MINOR DEC(_MSC_VER % 100)
229 | # endif
230 |
231 | #elif defined(__GNUC__) || defined(__GNUG__)
232 | # define COMPILER_ID "GNU"
233 | # if defined(__GNUC__)
234 | # define COMPILER_VERSION_MAJOR DEC(__GNUC__)
235 | # else
236 | # define COMPILER_VERSION_MAJOR DEC(__GNUG__)
237 | # endif
238 | # if defined(__GNUC_MINOR__)
239 | # define COMPILER_VERSION_MINOR DEC(__GNUC_MINOR__)
240 | # endif
241 | # if defined(__GNUC_PATCHLEVEL__)
242 | # define COMPILER_VERSION_PATCH DEC(__GNUC_PATCHLEVEL__)
243 | # endif
244 |
245 | #elif defined(_MSC_VER)
246 | # define COMPILER_ID "MSVC"
247 | /* _MSC_VER = VVRR */
248 | # define COMPILER_VERSION_MAJOR DEC(_MSC_VER / 100)
249 | # define COMPILER_VERSION_MINOR DEC(_MSC_VER % 100)
250 | # if defined(_MSC_FULL_VER)
251 | # if _MSC_VER >= 1400
252 | /* _MSC_FULL_VER = VVRRPPPPP */
253 | # define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 100000)
254 | # else
255 | /* _MSC_FULL_VER = VVRRPPPP */
256 | # define COMPILER_VERSION_PATCH DEC(_MSC_FULL_VER % 10000)
257 | # endif
258 | # endif
259 | # if defined(_MSC_BUILD)
260 | # define COMPILER_VERSION_TWEAK DEC(_MSC_BUILD)
261 | # endif
262 |
263 | #elif defined(__VISUALDSPVERSION__) || defined(__ADSPBLACKFIN__) || defined(__ADSPTS__) || defined(__ADSP21000__)
264 | # define COMPILER_ID "ADSP"
265 | #if defined(__VISUALDSPVERSION__)
266 | /* __VISUALDSPVERSION__ = 0xVVRRPP00 */
267 | # define COMPILER_VERSION_MAJOR HEX(__VISUALDSPVERSION__>>24)
268 | # define COMPILER_VERSION_MINOR HEX(__VISUALDSPVERSION__>>16 & 0xFF)
269 | # define COMPILER_VERSION_PATCH HEX(__VISUALDSPVERSION__>>8 & 0xFF)
270 | #endif
271 |
272 | #elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC)
273 | # define COMPILER_ID "IAR"
274 | # if defined(__VER__) && defined(__ICCARM__)
275 | # define COMPILER_VERSION_MAJOR DEC((__VER__) / 1000000)
276 | # define COMPILER_VERSION_MINOR DEC(((__VER__) / 1000) % 1000)
277 | # define COMPILER_VERSION_PATCH DEC((__VER__) % 1000)
278 | # define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__)
279 | # elif defined(__VER__) && defined(__ICCAVR__)
280 | # define COMPILER_VERSION_MAJOR DEC((__VER__) / 100)
281 | # define COMPILER_VERSION_MINOR DEC((__VER__) - (((__VER__) / 100)*100))
282 | # define COMPILER_VERSION_PATCH DEC(__SUBVERSION__)
283 | # define COMPILER_VERSION_INTERNAL DEC(__IAR_SYSTEMS_ICC__)
284 | # endif
285 |
286 | #elif defined(_SGI_COMPILER_VERSION) || defined(_COMPILER_VERSION)
287 | # define COMPILER_ID "MIPSpro"
288 | # if defined(_SGI_COMPILER_VERSION)
289 | /* _SGI_COMPILER_VERSION = VRP */
290 | # define COMPILER_VERSION_MAJOR DEC(_SGI_COMPILER_VERSION/100)
291 | # define COMPILER_VERSION_MINOR DEC(_SGI_COMPILER_VERSION/10 % 10)
292 | # define COMPILER_VERSION_PATCH DEC(_SGI_COMPILER_VERSION % 10)
293 | # else
294 | /* _COMPILER_VERSION = VRP */
295 | # define COMPILER_VERSION_MAJOR DEC(_COMPILER_VERSION/100)
296 | # define COMPILER_VERSION_MINOR DEC(_COMPILER_VERSION/10 % 10)
297 | # define COMPILER_VERSION_PATCH DEC(_COMPILER_VERSION % 10)
298 | # endif
299 |
300 |
301 | /* These compilers are either not known or too old to define an
302 | identification macro. Try to identify the platform and guess that
303 | it is the native compiler. */
304 | #elif defined(__hpux) || defined(__hpua)
305 | # define COMPILER_ID "HP"
306 |
307 | #else /* unknown compiler */
308 | # define COMPILER_ID ""
309 | #endif
310 |
311 | /* Construct the string literal in pieces to prevent the source from
312 | getting matched. Store it in a pointer rather than an array
313 | because some compilers will just produce instructions to fill the
314 | array rather than assigning a pointer to a static array. */
315 | char const* info_compiler = "INFO" ":" "compiler[" COMPILER_ID "]";
316 | #ifdef SIMULATE_ID
317 | char const* info_simulate = "INFO" ":" "simulate[" SIMULATE_ID "]";
318 | #endif
319 |
320 | #ifdef __QNXNTO__
321 | char const* qnxnto = "INFO" ":" "qnxnto[]";
322 | #endif
323 |
324 | #if defined(__CRAYXE) || defined(__CRAYXC)
325 | char const *info_cray = "INFO" ":" "compiler_wrapper[CrayPrgEnv]";
326 | #endif
327 |
328 | #define STRINGIFY_HELPER(X) #X
329 | #define STRINGIFY(X) STRINGIFY_HELPER(X)
330 |
331 | /* Identify known platforms by name. */
332 | #if defined(__linux) || defined(__linux__) || defined(linux)
333 | # define PLATFORM_ID "Linux"
334 |
335 | #elif defined(__CYGWIN__)
336 | # define PLATFORM_ID "Cygwin"
337 |
338 | #elif defined(__MINGW32__)
339 | # define PLATFORM_ID "MinGW"
340 |
341 | #elif defined(__APPLE__)
342 | # define PLATFORM_ID "Darwin"
343 |
344 | #elif defined(_WIN32) || defined(__WIN32__) || defined(WIN32)
345 | # define PLATFORM_ID "Windows"
346 |
347 | #elif defined(__FreeBSD__) || defined(__FreeBSD)
348 | # define PLATFORM_ID "FreeBSD"
349 |
350 | #elif defined(__NetBSD__) || defined(__NetBSD)
351 | # define PLATFORM_ID "NetBSD"
352 |
353 | #elif defined(__OpenBSD__) || defined(__OPENBSD)
354 | # define PLATFORM_ID "OpenBSD"
355 |
356 | #elif defined(__sun) || defined(sun)
357 | # define PLATFORM_ID "SunOS"
358 |
359 | #elif defined(_AIX) || defined(__AIX) || defined(__AIX__) || defined(__aix) || defined(__aix__)
360 | # define PLATFORM_ID "AIX"
361 |
362 | #elif defined(__hpux) || defined(__hpux__)
363 | # define PLATFORM_ID "HP-UX"
364 |
365 | #elif defined(__HAIKU__)
366 | # define PLATFORM_ID "Haiku"
367 |
368 | #elif defined(__BeOS) || defined(__BEOS__) || defined(_BEOS)
369 | # define PLATFORM_ID "BeOS"
370 |
371 | #elif defined(__QNX__) || defined(__QNXNTO__)
372 | # define PLATFORM_ID "QNX"
373 |
374 | #elif defined(__tru64) || defined(_tru64) || defined(__TRU64__)
375 | # define PLATFORM_ID "Tru64"
376 |
377 | #elif defined(__riscos) || defined(__riscos__)
378 | # define PLATFORM_ID "RISCos"
379 |
380 | #elif defined(__sinix) || defined(__sinix__) || defined(__SINIX__)
381 | # define PLATFORM_ID "SINIX"
382 |
383 | #elif defined(__UNIX_SV__)
384 | # define PLATFORM_ID "UNIX_SV"
385 |
386 | #elif defined(__bsdos__)
387 | # define PLATFORM_ID "BSDOS"
388 |
389 | #elif defined(_MPRAS) || defined(MPRAS)
390 | # define PLATFORM_ID "MP-RAS"
391 |
392 | #elif defined(__osf) || defined(__osf__)
393 | # define PLATFORM_ID "OSF1"
394 |
395 | #elif defined(_SCO_SV) || defined(SCO_SV) || defined(sco_sv)
396 | # define PLATFORM_ID "SCO_SV"
397 |
398 | #elif defined(__ultrix) || defined(__ultrix__) || defined(_ULTRIX)
399 | # define PLATFORM_ID "ULTRIX"
400 |
401 | #elif defined(__XENIX__) || defined(_XENIX) || defined(XENIX)
402 | # define PLATFORM_ID "Xenix"
403 |
404 | #elif defined(__WATCOMC__)
405 | # if defined(__LINUX__)
406 | # define PLATFORM_ID "Linux"
407 |
408 | # elif defined(__DOS__)
409 | # define PLATFORM_ID "DOS"
410 |
411 | # elif defined(__OS2__)
412 | # define PLATFORM_ID "OS2"
413 |
414 | # elif defined(__WINDOWS__)
415 | # define PLATFORM_ID "Windows3x"
416 |
417 | # else /* unknown platform */
418 | # define PLATFORM_ID
419 | # endif
420 |
421 | #elif defined(__INTEGRITY)
422 | # if defined(INT_178B)
423 | # define PLATFORM_ID "Integrity178"
424 |
425 | # else /* regular Integrity */
426 | # define PLATFORM_ID "Integrity"
427 | # endif
428 |
429 | #else /* unknown platform */
430 | # define PLATFORM_ID
431 |
432 | #endif
433 |
434 | /* For windows compilers MSVC and Intel we can determine
435 | the architecture of the compiler being used. This is because
436 | the compilers do not have flags that can change the architecture,
437 | but rather depend on which compiler is being used
438 | */
439 | #if defined(_WIN32) && defined(_MSC_VER)
440 | # if defined(_M_IA64)
441 | # define ARCHITECTURE_ID "IA64"
442 |
443 | # elif defined(_M_X64) || defined(_M_AMD64)
444 | # define ARCHITECTURE_ID "x64"
445 |
446 | # elif defined(_M_IX86)
447 | # define ARCHITECTURE_ID "X86"
448 |
449 | # elif defined(_M_ARM64)
450 | # define ARCHITECTURE_ID "ARM64"
451 |
452 | # elif defined(_M_ARM)
453 | # if _M_ARM == 4
454 | # define ARCHITECTURE_ID "ARMV4I"
455 | # elif _M_ARM == 5
456 | # define ARCHITECTURE_ID "ARMV5I"
457 | # else
458 | # define ARCHITECTURE_ID "ARMV" STRINGIFY(_M_ARM)
459 | # endif
460 |
461 | # elif defined(_M_MIPS)
462 | # define ARCHITECTURE_ID "MIPS"
463 |
464 | # elif defined(_M_SH)
465 | # define ARCHITECTURE_ID "SHx"
466 |
467 | # else /* unknown architecture */
468 | # define ARCHITECTURE_ID ""
469 | # endif
470 |
471 | #elif defined(__WATCOMC__)
472 | # if defined(_M_I86)
473 | # define ARCHITECTURE_ID "I86"
474 |
475 | # elif defined(_M_IX86)
476 | # define ARCHITECTURE_ID "X86"
477 |
478 | # else /* unknown architecture */
479 | # define ARCHITECTURE_ID ""
480 | # endif
481 |
482 | #elif defined(__IAR_SYSTEMS_ICC__) || defined(__IAR_SYSTEMS_ICC)
483 | # if defined(__ICCARM__)
484 | # define ARCHITECTURE_ID "ARM"
485 |
486 | # elif defined(__ICCAVR__)
487 | # define ARCHITECTURE_ID "AVR"
488 |
489 | # else /* unknown architecture */
490 | # define ARCHITECTURE_ID ""
491 | # endif
492 |
493 | #elif defined(__ghs__)
494 | # if defined(__PPC64__)
495 | # define ARCHITECTURE_ID "PPC64"
496 |
497 | # elif defined(__ppc__)
498 | # define ARCHITECTURE_ID "PPC"
499 |
500 | # elif defined(__ARM__)
501 | # define ARCHITECTURE_ID "ARM"
502 |
503 | # elif defined(__x86_64__)
504 | # define ARCHITECTURE_ID "x64"
505 |
506 | # elif defined(__i386__)
507 | # define ARCHITECTURE_ID "X86"
508 |
509 | # else /* unknown architecture */
510 | # define ARCHITECTURE_ID ""
511 | # endif
512 | #else
513 | # define ARCHITECTURE_ID
514 | #endif
515 |
516 | /* Convert integer to decimal digit literals. */
517 | #define DEC(n) \
518 | ('0' + (((n) / 10000000)%10)), \
519 | ('0' + (((n) / 1000000)%10)), \
520 | ('0' + (((n) / 100000)%10)), \
521 | ('0' + (((n) / 10000)%10)), \
522 | ('0' + (((n) / 1000)%10)), \
523 | ('0' + (((n) / 100)%10)), \
524 | ('0' + (((n) / 10)%10)), \
525 | ('0' + ((n) % 10))
526 |
527 | /* Convert integer to hex digit literals. */
528 | #define HEX(n) \
529 | ('0' + ((n)>>28 & 0xF)), \
530 | ('0' + ((n)>>24 & 0xF)), \
531 | ('0' + ((n)>>20 & 0xF)), \
532 | ('0' + ((n)>>16 & 0xF)), \
533 | ('0' + ((n)>>12 & 0xF)), \
534 | ('0' + ((n)>>8 & 0xF)), \
535 | ('0' + ((n)>>4 & 0xF)), \
536 | ('0' + ((n) & 0xF))
537 |
538 | /* Construct a string literal encoding the version number components. */
539 | #ifdef COMPILER_VERSION_MAJOR
540 | char const info_version[] = {
541 | 'I', 'N', 'F', 'O', ':',
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1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-18.
3 | //
4 |
5 |
6 | #pragma once
7 |
8 |
9 | #include
10 | #include "noisy.h"
11 |
12 | struct CategoricalDQN : torch::nn::Module{
13 | CategoricalDQN(int64_t num_inputs, int64_t num_actions, int64_t num_atoms, int64_t Vmin, int64_t Vmax)
14 | :
15 | num_atoms(num_atoms),
16 | num_actions(num_actions),
17 | Vmin(Vmin),
18 | Vmax(Vmax),
19 | linear1(torch::nn::Linear(num_inputs, 128)),
20 | linear2(torch::nn::Linear(128, 128)),
21 | noisy1(NoisyLinear(128, 512, 0.4)),
22 | noisy2(NoisyLinear(512, num_actions*num_atoms, 0.4)){
23 |
24 | }
25 |
26 | torch::Tensor forward(torch::Tensor input) {
27 | // Flatten the output
28 | input = torch::relu(linear1(input));
29 | input = torch::relu(linear2(input));
30 | input = torch::relu(noisy1.forward(input));
31 | input = noisy2.forward(input);
32 | input = torch::softmax(input.view({-1, num_atoms}), 1).view({-1, num_actions, num_atoms});
33 | return input;
34 | }
35 |
36 | torch::Tensor act(torch::Tensor state){
37 | torch::Tensor dist = forward(state);
38 | dist = dist*torch::linspace(Vmin, Vmax, num_atoms);
39 | torch::Tensor action = std::get<1>(dist.sum(2).max(1));
40 | return action;
41 | }
42 |
43 | int64_t num_atoms;
44 | int64_t num_actions;
45 | int64_t Vmin;
46 | int64_t Vmax;
47 | torch::nn::Linear linear1, linear2;
48 | NoisyLinear noisy1, noisy2;
49 |
50 |
51 | };
52 |
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/dqn.cpp:
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1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-10.
3 | //
4 |
5 |
--------------------------------------------------------------------------------
/dqn.h:
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1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-10.
3 | //
4 |
5 | #pragma once
6 |
7 |
8 | #include
9 |
10 | struct DQN : torch::nn::Module{
11 | DQN(int64_t input_channels, int64_t num_actions)
12 | :
13 | conv1(torch::nn::Conv2dOptions(input_channels, 32, 8)
14 | .stride(4)
15 | ),
16 | conv2(torch::nn::Conv2dOptions(32, 64, 4)
17 | .stride(2)
18 | ),
19 | conv3(torch::nn::Conv2dOptions(64, 64, 3)
20 | .stride(1)
21 | ),
22 |
23 | linear1(torch::nn::Linear(64*22*16, 512)),
24 | output(torch::nn::Linear(512, num_actions)){}
25 |
26 | torch::Tensor forward(torch::Tensor input) {
27 | input = torch::relu(conv1(input));
28 | input = torch::relu(conv2(input));
29 | input = torch::relu(conv3(input));
30 | // Flatten the output
31 | input = input.view({input.size(0), -1});
32 | input = torch::relu(linear1(input));
33 | input = output(input);
34 | return input;
35 | }
36 |
37 | torch::Tensor act(torch::Tensor state){
38 | torch::Tensor q_value = forward(state);
39 | torch::Tensor action = std::get<1>(q_value.max(1));
40 | return action;
41 | }
42 |
43 | torch::nn::Conv2d conv1, conv2, conv3;
44 | torch::nn::Linear linear1, output;
45 | };
46 |
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/main.cpp:
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1 | #include "Trainer.h"
2 | #include
3 | // Move torch imports before ale because ale uses namespace std which interferes with the torch imports.
4 | #include "/Users/navneetmadhukumar/Downloads/Arcade-Learning-Environment-master/src/ale_interface.hpp"
5 |
6 |
7 | int main() {
8 |
9 | Trainer trainer(3, 18, 100000);
10 | trainer.train(123, "/Users/navneetmadhukumar/CLionProjects/Reinforcement_CPP/atari_roms/pong.bin", 1000000);
11 |
12 | }
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/noisy.h:
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1 | //
2 | // Created by Navneet Madhu Kumar on 2019-07-18.
3 | //
4 |
5 | #pragma once
6 |
7 |
8 | #include
9 | #include
10 |
11 | struct NoisyLinear : torch::nn::Module{
12 | NoisyLinear(int64_t in_features, int64_t out_features, float_t std_init){
13 | W_mu = register_parameter("W_mu", torch::randn({out_features, in_features}));
14 | W_sigma = register_parameter("W_sigma", torch::randn({out_features, in_features}));
15 | b_mu = register_parameter("b_mu", torch::randn(out_features));
16 | b_sigma = register_parameter("b_sigma", torch::randn(out_features));
17 | W_epsilon = register_buffer("W_epsilon", torch::randn({out_features, in_features}));
18 | b_epsilon = register_buffer("b_epsilon", torch::randn(out_features));
19 |
20 | reset_params(std_init);
21 | reset_noise(in_features, out_features);
22 |
23 | }
24 |
25 | torch::Tensor forward(torch::Tensor input) {
26 | torch::Tensor weight;
27 | torch::Tensor bias;
28 | if (is_training()){
29 | weight = W_mu + W_sigma.mul(W_epsilon);
30 | bias = b_mu + b_sigma.mul(b_epsilon);
31 |
32 | }else{
33 | weight = W_mu;
34 | bias = b_mu;
35 | }
36 |
37 | return torch::addmm(bias, input, weight);
38 | }
39 |
40 | void reset_params(float_t std_init){
41 | float_t mu_range = 1 / sqrt(W_mu.size(1));
42 | W_mu.uniform_(-mu_range, mu_range);
43 | W_sigma.fill_(std_init / sqrt(W_sigma.size(1)));
44 |
45 | b_mu.uniform_(-mu_range, mu_range);
46 | b_sigma.fill_(std_init / sqrt(b_sigma.size(1)));
47 |
48 | }
49 | void reset_noise(int64_t in_features, int64_t out_features){
50 | torch::Tensor epsilon_in = scale_noise(in_features);
51 | torch::Tensor epsilon_out = scale_noise(out_features);
52 |
53 | W_epsilon.copy_(epsilon_out.ger(epsilon_in));
54 | b_epsilon.copy_(scale_noise(out_features));
55 |
56 | }
57 |
58 | torch::Tensor scale_noise(int64_t size){
59 | torch::Tensor x = torch::randn(size);
60 | x = x.sign().mul(x.abs().sqrt());
61 | return x;
62 | }
63 |
64 | torch::Tensor W_mu, W_sigma, b_mu, b_sigma, W_epsilon, b_epsilon;
65 | };
66 |
67 |
68 |
69 |
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