| #pragma once |
| |
| #include <torch/csrc/python_headers.h> |
| |
| #include <ATen/core/Tensor.h> |
| #include <ATen/core/jit_type_base.h> |
| #include <c10/util/irange.h> |
| #include <pybind11/pybind11.h> |
| #include <pybind11/stl.h> |
| |
| #include <torch/csrc/Device.h> |
| #include <torch/csrc/DynamicTypes.h> |
| #include <torch/csrc/Generator.h> |
| #include <torch/csrc/MemoryFormat.h> |
| #include <torch/csrc/Stream.h> |
| #include <torch/csrc/utils/tensor_memoryformats.h> |
| |
| namespace py = pybind11; |
| |
| // This makes intrusive_ptr to be available as a custom pybind11 holder type, |
| // see |
| // https://pybind11.readthedocs.io/en/stable/advanced/smart_ptrs.html#custom-smart-pointers |
| PYBIND11_DECLARE_HOLDER_TYPE(T, c10::intrusive_ptr<T>, true); |
| |
| PYBIND11_DECLARE_HOLDER_TYPE(T, c10::SingletonOrSharedTypePtr<T>); |
| PYBIND11_DECLARE_HOLDER_TYPE(T, c10::SingletonTypePtr<T>, true); |
| |
| namespace pybind11::detail { |
| |
| // torch.Tensor <-> at::Tensor conversions (without unwrapping) |
| template <> |
| struct TORCH_PYTHON_API type_caster<at::Tensor> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::Tensor, _("torch.Tensor")); |
| |
| bool load(handle src, bool); |
| |
| static handle cast( |
| const at::Tensor& src, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| }; |
| |
| // torch._StorageBase <-> at::Storage |
| template <> |
| struct type_caster<at::Storage> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::Storage, _("torch.StorageBase")); |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| if (torch::isStorage(obj)) { |
| value = torch::createStorage(obj); |
| return true; |
| } |
| return false; |
| } |
| |
| static handle cast( |
| const at::Storage& src, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| return handle(torch::createPyObject(src)); |
| } |
| }; |
| |
| template <> |
| struct type_caster<at::Generator> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::Generator, _("torch.Generator")); |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| if (THPGenerator_Check(obj)) { |
| value = reinterpret_cast<THPGenerator*>(obj)->cdata; |
| return true; |
| } |
| return false; |
| } |
| |
| static handle cast( |
| const at::Generator& src, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| return handle(THPGenerator_Wrap(src)); |
| } |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<at::IntArrayRef> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::IntArrayRef, _("Tuple[int, ...]")); |
| |
| bool load(handle src, bool); |
| static handle cast( |
| at::IntArrayRef src, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| |
| private: |
| std::vector<int64_t> v_value; |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<at::SymIntArrayRef> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::SymIntArrayRef, _("List[int]")); |
| |
| bool load(handle src, bool); |
| static handle cast( |
| at::SymIntArrayRef src, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| |
| private: |
| std::vector<c10::SymInt> v_value; |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<at::ArrayRef<c10::SymNode>> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::ArrayRef<c10::SymNode>, _("List[SymNode]")); |
| |
| bool load(handle src, bool); |
| static handle cast( |
| at::ArrayRef<c10::SymNode> src, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| |
| private: |
| std::vector<c10::SymNode> v_value; |
| }; |
| |
| template <> |
| struct type_caster<at::MemoryFormat> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::MemoryFormat, _("torch.memory_format")); |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| if (THPMemoryFormat_Check(obj)) { |
| value = reinterpret_cast<THPMemoryFormat*>(obj)->memory_format; |
| return true; |
| } |
| return false; |
| } |
| static handle cast( |
| at::MemoryFormat src, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| return handle(torch::utils::getTHPMemoryFormat(src)); |
| } |
| }; |
| |
| template <> |
| struct type_caster<at::Device> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(at::Device, _("torch.device")); |
| |
| // PYBIND11_TYPE_CASTER defines a member field called value. Since at::Device |
| // cannot be default-initialized, we provide this constructor to explicitly |
| // initialize that field. The value doesn't matter as it will be overwritten |
| // after a successful call to load. |
| type_caster() : value(c10::kCPU) {} |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| if (THPDevice_Check(obj)) { |
| value = reinterpret_cast<THPDevice*>(obj)->device; |
| return true; |
| } |
| return false; |
| } |
| |
| static handle cast( |
| const at::Device& src, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| return handle(THPDevice_New(src)); |
| } |
| }; |
| |
| template <> |
| struct type_caster<c10::Stream> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(c10::Stream, _("torch.Stream")); |
| |
| // PYBIND11_TYPE_CASTER defines a member field called value. Since c10::Stream |
| // cannot be default-initialized, we provide this constructor to explicitly |
| // initialize that field. The value doesn't matter as it will be overwritten |
| // after a successful call to load. |
| type_caster() : value(c10::Stream::DEFAULT, c10::Device(c10::kCPU, 0)) {} |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| if (THPStream_Check(obj)) { |
| value = c10::Stream::unpack3( |
| ((THPStream*)obj)->stream_id, |
| ((THPStream*)obj)->device_index, |
| static_cast<c10::DeviceType>(((THPStream*)obj)->device_type)); |
| return true; |
| } |
| return false; |
| } |
| |
| static handle cast( |
| const c10::Stream& src, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| return handle(THPStream_Wrap(src)); |
| } |
| }; |
| |
| template <> |
| struct type_caster<c10::DispatchKey> |
| : public type_caster_base<c10::DispatchKey> { |
| using base = type_caster_base<c10::DispatchKey>; |
| c10::DispatchKey tmp; |
| |
| public: |
| bool load(handle src, bool convert) { |
| if (base::load(src, convert)) { |
| return true; |
| } else if (py::isinstance( |
| src, py::module_::import("builtins").attr("str"))) { |
| tmp = c10::parseDispatchKey(py::cast<std::string>(src)); |
| value = &tmp; |
| return true; |
| } |
| return false; |
| } |
| |
| static handle cast( |
| c10::DispatchKey src, |
| return_value_policy policy, |
| handle parent) { |
| return base::cast(src, policy, parent); |
| } |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<c10::Scalar> { |
| public: |
| PYBIND11_TYPE_CASTER( |
| c10::Scalar, |
| _("Union[Number, torch.SymInt, torch.SymFloat, torch.SymBool]")); |
| bool load(py::handle src, bool); |
| |
| static py::handle cast( |
| const c10::Scalar& si, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<c10::SymInt> { |
| public: |
| PYBIND11_TYPE_CASTER(c10::SymInt, _("Union[int, torch.SymInt]")); |
| bool load(py::handle src, bool); |
| |
| static py::handle cast( |
| const c10::SymInt& si, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<c10::SymFloat> { |
| public: |
| PYBIND11_TYPE_CASTER(c10::SymFloat, _("float")); |
| bool load(py::handle src, bool); |
| |
| static py::handle cast( |
| const c10::SymFloat& si, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| }; |
| |
| template <> |
| struct TORCH_PYTHON_API type_caster<c10::SymBool> { |
| public: |
| PYBIND11_TYPE_CASTER(c10::SymBool, _("Union[bool, torch.SymBool]")); |
| bool load(py::handle src, bool); |
| |
| static py::handle cast( |
| const c10::SymBool& si, |
| return_value_policy /* policy */, |
| handle /* parent */); |
| }; |
| |
| template <typename T> |
| struct type_caster<c10::complex<T>> { |
| public: |
| // NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes) |
| PYBIND11_TYPE_CASTER(c10::complex<T>, _("complex")); |
| |
| bool load(handle src, bool) { |
| PyObject* obj = src.ptr(); |
| |
| // Refered from `THPUtils_unpackComplexDouble` |
| Py_complex py_complex = PyComplex_AsCComplex(obj); |
| if (py_complex.real == -1.0 && PyErr_Occurred()) { |
| return false; |
| } |
| |
| // Python's Complex is always double precision. |
| value = c10::complex<double>(py_complex.real, py_complex.imag); |
| return true; |
| } |
| |
| static handle cast( |
| const c10::complex<T>& complex, |
| return_value_policy /* policy */, |
| handle /* parent */) { |
| // Python only knows double precision complex. |
| return handle(PyComplex_FromDoubles(complex.real(), complex.imag())); |
| } |
| }; |
| |
| } // namespace pybind11::detail |
| |
| namespace torch::impl { |
| |
| // Use this function if you have a C++ object that is used from both C++ |
| // and Python contexts, and you need its GIL to be released when you |
| // destruct it in the Python context. |
| // |
| // This function is a valid shared_ptr destructor and can be used to |
| // conveniently allocate a shared_ptr to an object whose destructor will be run |
| // without the GIL. Pass it as the second argument to shared_ptr, e.g., |
| // |
| // shared_ptr<T>(new T(), destroy_without_gil<T>) |
| // |
| // Attaching the GIL release logic to the holder pointer rather than the |
| // actual destructor of T is helpful when T is Python-agnostic and |
| // shouldn't refer to the PYthon API. |
| // |
| // Note there are limitations to the correctness of code that makes use of this. |
| // In particular, if a shared_ptr is constructed from C++ code without this |
| // destructor and then passed to pybind11, pybind11 will happily take ownership |
| // of the shared_ptr (and be willing to destruct it from a context where it is |
| // holding the GIL). unique_ptr with a type branded deleter is less prone to |
| // this problem, because a stock deleter unique_ptr is not convertible with it. |
| // I plan to mitigate this problem by adding DEBUG-only asserts to the true C++ |
| // destructors that the GIL is not held (using a virtual call to get to the |
| // Python interpreter); alternately, we could use a virtual call to simply |
| // ensure we release the GIL in the C++ destructor, however, this is a layering |
| // violation (why does code that is ostensibly Python agnostic calling into the |
| // GIL). |
| // |
| // Adapted from |
| // https://github.com/pybind/pybind11/issues/1446#issuecomment-406341510 |
| template <typename T> |
| inline void destroy_without_gil(T* ptr) { |
| // Because the ownership of a shared_ptr is diffuse, it's not possible to |
| // necessarily predict whether or not the last reference to an object will |
| // be destructed from Python or C++. This means that in the destructor here, |
| // we don't necessarily know if we actually have the GIL or not; in fact, |
| // we don't even know if the Python interpreter still exists! Thus, we have |
| // to test for it before releasing the GIL. |
| // |
| // PyGILState_Check is hopefully self explanatory. But Py_IsInitialized or |
| // _PyIsFinalizing? Both get set at the same time during the Python |
| // destruction process: |
| // https://github.com/python/cpython/blob/d92513390a1a0da781bb08c284136f4d7abea36d/Python/pylifecycle.c#L1716-L1717 |
| // so the operant question is whether or not you want to release the GIL after |
| // finalization has completed (and there is just no Python interpreter). |
| // Clearly there is no need to release GIL in that state, so we want |
| // Py_IsInitialized. |
| if (Py_IsInitialized() && PyGILState_Check()) { |
| pybind11::gil_scoped_release nogil; |
| delete ptr; |
| } else { |
| delete ptr; |
| } |
| } |
| |
| } // namespace torch::impl |