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tensor.h 10 kB

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  1. /**
  2. * \file imperative/python/src/tensor.h
  3. * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
  4. *
  5. * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
  6. *
  7. * Unless required by applicable law or agreed to in writing,
  8. * software distributed under the License is distributed on an
  9. * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  10. */
  11. #pragma once
  12. #pragma GCC diagnostic ignored "-Wmissing-field-initializers"
  13. #include <variant>
  14. #include "megbrain/imperative/interpreter.h"
  15. #include "pybind11/pybind11.h"
  16. #include <string>
  17. #include <unordered_map>
  18. #include "./pyext17.h"
  19. namespace mgb::imperative::python {
  20. template<typename T, typename B = pybind11::object>
  21. struct ObjectPtr : B {
  22. using B::B;
  23. T& operator*() {return reinterpret_cast<T&>(*B::ptr());}
  24. T* operator->() {return reinterpret_cast<T*>(B::ptr());}
  25. };
  26. } // namespace mgb::imperative::python
  27. #include "./grad_info.h" // for struct GradInfo
  28. #include "./trace_info.h" // for struct TraceInfo
  29. namespace mgb::imperative::python {
  30. struct GradKey;
  31. extern interpreter::Interpreter::Channel* interpreter_for_py;
  32. class SharedHandle {
  33. using Handle = interpreter::Interpreter::Handle;
  34. static_assert(std::is_pointer_v<Handle>);
  35. std::shared_ptr<std::remove_pointer_t<Handle>> holder;
  36. public:
  37. inline explicit SharedHandle(Handle handle) : holder(handle, [](auto* h){
  38. if (h) {
  39. interpreter_for_py->del(h);
  40. }
  41. }) {}
  42. SharedHandle(const SharedHandle&) = default;
  43. SharedHandle& operator=(const SharedHandle&) = default;
  44. SharedHandle(SharedHandle&&) = default;
  45. SharedHandle& operator=(SharedHandle&&) = default;
  46. inline Handle get() {return holder.get();}
  47. };
  48. // impl in grad.cpp
  49. class GradInfoCollection {
  50. private:
  51. SmallVector<GradInfo> m_storage;
  52. protected:
  53. void _shrink();
  54. public:
  55. bool contains(GradKey* key);
  56. GradInfo& operator[](GradKey* key);
  57. GradInfo& at(GradKey* key);
  58. bool empty() {
  59. _shrink();
  60. return m_storage.empty();
  61. }
  62. auto begin() {
  63. _shrink();
  64. return m_storage.begin();
  65. }
  66. auto end() {
  67. _shrink();
  68. return m_storage.end();
  69. }
  70. size_t count(GradKey* key) {
  71. return contains(key) ? 1 : 0;
  72. }
  73. };
  74. struct Tensor : std::enable_shared_from_this<Tensor>, NonCopyableObj {
  75. using flags_t = uint64_t;
  76. struct Flags {
  77. static constexpr flags_t SCALAR = 1;
  78. static constexpr flags_t GRAD = 1 << 1;
  79. static constexpr flags_t TRACE = 1 << 2;
  80. static constexpr flags_t MODULE_TRACE = 1 << 3;
  81. };
  82. flags_t m_flags = 0;
  83. GradInfoCollection m_grad_info_dict;
  84. TraceInfo m_trace_info;
  85. SharedHandle m_handle;
  86. std::string user_custom_name;
  87. std::string automatic_name;
  88. cg::VarNode* m_var;
  89. pybind11::object m_module_trace_info;
  90. using Handle = interpreter::Interpreter::Handle;
  91. inline Tensor() : m_handle(nullptr), m_var(nullptr) {}
  92. inline explicit Tensor(Handle handle) : m_handle(handle), m_var(nullptr) {}
  93. inline explicit Tensor(SharedHandle handle) : m_handle(std::move(handle)), m_var(nullptr) {}
  94. inline explicit Tensor(cg::VarNode *var) : m_handle(nullptr), m_var(var) {}
  95. ~Tensor() = default;
  96. inline std::shared_ptr<Tensor> copy() {
  97. auto ret = std::make_shared<Tensor>(m_handle);
  98. ret->m_flags = m_flags;
  99. ret->m_grad_info_dict = m_grad_info_dict;
  100. ret->m_trace_info = m_trace_info;
  101. ret->m_var = m_var;
  102. return ret;
  103. }
  104. inline DType dtype() {
  105. if (m_var) {
  106. return m_var->dtype();
  107. }
  108. return interpreter_for_py->get_dtype(m_handle.get());
  109. }
  110. inline CompNode comp_node() {
  111. if (m_var) {
  112. return m_var->comp_node();
  113. }
  114. return interpreter_for_py->get_device(m_handle.get());
  115. }
  116. inline TensorShape shape() {
  117. if (m_var) {
  118. return m_var->shape();
  119. }
  120. return interpreter_for_py->get_shape(m_handle.get());
  121. }
  122. };
  123. struct TensorWrapper {
  124. std::shared_ptr<Tensor> m_tensor;
  125. inline TensorWrapper(std::shared_ptr<Tensor> tensor = {}) : m_tensor(std::move(tensor)) {}
  126. TensorWrapper(PyObject* args, PyObject* kwargs);
  127. ~TensorWrapper() = default;
  128. static constexpr auto tp_name = pybind11::detail::_("Tensor");
  129. using wrap_t = pyext17::wrap<TensorWrapper>;
  130. friend wrap_t;
  131. inline static TensorWrapper* cast(PyObject* obj) {return reinterpret_cast<wrap_t*>(obj)->inst();}
  132. inline static TensorWrapper* try_cast(PyObject* obj) {
  133. if (!wrap_t::type().isinstance(obj)) return nullptr;
  134. return cast(obj);
  135. }
  136. inline ObjectPtr<TensorWrapper, pybind11::handle> self() {return wrap_t::pycast(this);}
  137. template <typename... Args>
  138. static ObjectPtr<Tensor> make(Args&&... args) {
  139. auto* op = wrap_t::cnew(std::forward<Args>(args)...);
  140. return pybind11::reinterpret_steal<ObjectPtr<Tensor>>(op);
  141. }
  142. template <typename... Args>
  143. static ObjectPtr<Tensor> make(PyTypeObject* pytype, Args&&... args) {
  144. auto* op = wrap_t::cnew_with_type(pytype,std::forward<Args>(args)...);
  145. return pybind11::reinterpret_steal<ObjectPtr<Tensor>>(op);
  146. }
  147. PyObject* shape();
  148. PyObject* dtype();
  149. PyObject* device();
  150. PyObject* numpy();
  151. void reset(PyObject*);
  152. PyObject* detach();
  153. PyObject* isscalar();
  154. void setscalar();
  155. void unsetscalar();
  156. PyObject* _dev_tensor();
  157. void _swap_in();
  158. void _swap_out();
  159. void _drop();
  160. PyObject* varnode();
  161. void reset_varnode();
  162. PyObject* handle();
  163. void set_handle(PyObject *);
  164. PyObject* mixin_handle();
  165. PyObject* recording();
  166. PyObject* copied();
  167. void set_mixin_handle(PyObject*);
  168. void set_recording(PyObject*);
  169. PyObject* compiled_info();
  170. void set_compiled_info(PyObject *);
  171. PyObject* trace_mixin_info();
  172. void set_trace_mixin_info(PyObject *);
  173. PyObject* module_trace_info();
  174. void set_module_trace_info(PyObject *);
  175. PyObject* user_custom_name();
  176. void set_user_custom_name(PyObject *);
  177. PyObject* automatic_name();
  178. void set_automatic_name(PyObject *);
  179. PyObject* _use_cnt() { return PyLong_FromSize_t(m_tensor.use_count()); };
  180. };
  181. struct PySymbolVar {
  182. cg::VarNode* m_node = nullptr;
  183. bool is_scalar = false;
  184. PySymbolVar() = default;
  185. PySymbolVar(VarNode *m): m_node(m){}
  186. };
  187. PyObject* py_apply(PyObject* self, PyObject*const* args, size_t nargs/* , PyObject* kwnames */);
  188. struct ApplyContext {
  189. static Tensor::flags_t global_disable;
  190. static Tensor::flags_t global_enable;
  191. Tensor::flags_t flags = 0;
  192. std::shared_ptr<OpDef> op;
  193. Tensor*const* args;
  194. size_t nargs;
  195. PyTypeObject* pytype = nullptr;
  196. bool backward = false;
  197. class scoped_disable : NonCopyableObj {
  198. Tensor::flags_t saved_flags;
  199. public:
  200. scoped_disable(Tensor::flags_t flags) : saved_flags(ApplyContext::global_disable) {
  201. ApplyContext::global_disable |= flags;
  202. }
  203. ~scoped_disable() {
  204. ApplyContext::global_disable = saved_flags;
  205. }
  206. };
  207. };
  208. using apply_result_t = SmallVector<std::shared_ptr<Tensor>, 8>;
  209. apply_result_t apply(ApplyContext& ctx);
  210. template <typename T>
  211. decltype(auto) resolve_arrow(T&& p) {
  212. if constexpr (std::is_pointer_v<std::remove_reference_t<T>>) {
  213. auto* ret = p;
  214. return ret;
  215. } else {
  216. auto probe = [](auto&& p) -> decltype(p.operator->()) {};
  217. if constexpr (std::is_invocable_v<decltype(probe), decltype(p)>) {
  218. return resolve_arrow(p.operator->());
  219. } else {
  220. return std::forward<T>(p);
  221. }
  222. }
  223. }
  224. template <typename... Args>
  225. constexpr bool is_all_tensor_ptr = (... && std::is_same_v<decltype(resolve_arrow(std::declval<Args>())), Tensor*>);
  226. template <typename... Args, std::enable_if_t<is_all_tensor_ptr<Args...>, int> = 0>
  227. apply_result_t apply(std::shared_ptr<OpDef> op, Args&&... args) {
  228. ApplyContext ctx;
  229. Tensor* arg_arr[] = {resolve_arrow(args)...};
  230. ctx.flags = (0 | ... | args->m_flags);
  231. ctx.args = arg_arr;
  232. ctx.nargs = sizeof...(args);
  233. ctx.op = std::move(op);
  234. return apply(ctx);
  235. }
  236. inline auto apply(std::shared_ptr<OpDef> op, Tensor*const* args, size_t nargs) {
  237. ApplyContext ctx;
  238. ctx.op = std::move(op);
  239. ctx.nargs = nargs;
  240. ctx.args = args;
  241. for (size_t i = 0; i < nargs; ++i) {
  242. ctx.flags |= args[i]->m_flags;
  243. }
  244. return apply(ctx);
  245. }
  246. template <typename T>
  247. auto apply(std::shared_ptr<OpDef> op, T&& tensors)
  248. -> std::enable_if_t<std::is_same_v<decltype(resolve_arrow(tensors[0])), Tensor*>,
  249. apply_result_t> {
  250. size_t nargs = tensors.size();
  251. Tensor* args[nargs];
  252. for (size_t i = 0; i < nargs; ++i) {
  253. args[i] = resolve_arrow(tensors[i]);
  254. }
  255. return apply(op, args, nargs);
  256. }
  257. std::shared_ptr<Tensor> make_const(imperative::TensorPtr value);
  258. inline auto apply(Subgraph graph, Tensor*const* args, size_t nargs) {
  259. SmallVector<std::shared_ptr<Tensor>> inputs;
  260. for (size_t i = 0; i < nargs; ++i) {
  261. inputs.push_back(args[i]->shared_from_this());
  262. }
  263. auto apply_functor = [](std::shared_ptr<OpDef> op, SmallVector<std::shared_ptr<Tensor>> inputs, size_t) {
  264. return apply(op, std::move(inputs));
  265. };
  266. return graph.apply(inputs, apply_functor, &make_const);
  267. }
  268. template <typename T>
  269. auto apply(Subgraph graph, T&& tensors)
  270. -> std::enable_if_t<std::is_same_v<std::decay_t<decltype(tensors[0])>, Tensor*>,
  271. apply_result_t> {
  272. size_t nargs = tensors.size();
  273. Tensor* args[nargs];
  274. for (size_t i = 0; i < nargs; ++i) {
  275. args[i] = resolve_arrow(tensors[i]);
  276. }
  277. return apply(graph, args, nargs);
  278. }
  279. void init_tensor(pybind11::module);
  280. extern PyObject *cpp_apply_with_tracing;
  281. extern PyObject *cpp_apply_backward_varnode;
  282. extern PyObject *cpp_apply_module_trace;
  283. } // namespace mgb::imperative::python
  284. namespace pybind11::detail {
  285. template<> struct type_caster<mgb::imperative::python::TensorWrapper> : mgb::imperative::python::TensorWrapper::wrap_t::caster {};
  286. } // namespace pybind11::detail

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