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https://github.com/zebrajr/pytorch.git
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bd5303010d
The core autograd Variable, Function, and Engine no longer depend on the Python API. This let's us implement functions in C++. In the future, we can also multithread engine and release the GIL for most of the non-Python backwards.
46 lines
1.2 KiB
C++
46 lines
1.2 KiB
C++
#pragma once
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#include <Python.h>
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#include <memory>
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#include <typeinfo>
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#include "torch/csrc/autograd/function.h"
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#include "torch/csrc/utils/object_ptr.h"
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namespace torch { namespace autograd {
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struct THPCppFunction {
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PyObject_HEAD
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std::shared_ptr<Function> cdata;
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};
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template<typename Ctor>
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PyObject* CppFunction_pynew(PyTypeObject *type, PyObject *args, PyObject *kwds)
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{
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THPObjectPtr obj = type->tp_alloc(type, 0);
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if (!obj) return NULL;
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THPCppFunction* f = (THPCppFunction*)obj.get();
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new (&f->cdata) std::shared_ptr<Function>(Ctor()(args));
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if (!f->cdata) {
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return NULL;
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}
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return obj.release();
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}
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PyTypeObject* _initFunctionPyTypeObject(PyTypeObject& type, const char* name);
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template<typename Ctor>
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PyTypeObject* createForwardFunctionPyTypeObject(PyTypeObject& type, const char* name)
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{
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type.tp_new = &CppFunction_pynew<Ctor>;
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return _initFunctionPyTypeObject(type, name);
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}
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// conversion utilities for PyArg_ParseTuple
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int TensorConverter(PyObject* obj, std::unique_ptr<thpp::Tensor>* address);
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void registerCppFunction(const std::type_info& type, PyTypeObject* pytype);
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PyObject* functionToPyObject(std::shared_ptr<Function> cdata);
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}} // namespace torch::autograd
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