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This refactor was prompted by challenges handling mixed int/float operations in C++. A previous version of this patch added overloads for each permutation of int/float and was unwieldy https://github.com/pytorch/pytorch/pull/87722/ This PR takes a different approach. The general outline of the patch is to combine the C++ types SymIntNode and SymFloatNode into a single type, SymNode. This is type erased; we no longer know statically at C++ if we have an int/float and have to test it with the is_int()/is_float() virtual methods. This has a number of knock on effects. - We no longer have C++ classes to bind to Python. Instead, we take an entirely new approach to our Python API, where we have a SymInt/SymFloat class defined entirely in Python, which hold a SymNode (which corresponds to the C++ SymNode). However, SymNode is not pybind11-bound; instead, it lives as-is in Python, and is wrapped into C++ SymNode using PythonSymNode when it goes into C++. This implies a userland rename. In principle, it is also possible for the canonical implementation of SymNode to be written in C++, and then bound to Python with pybind11 (we have this code, although it is commented out.) However, I did not implement this as we currently have no C++ implementations of SymNode. Because we do return SymInt/SymFloat from C++ bindings, the C++ binding code needs to know how to find these classes. Currently, this is done just by manually importing torch and getting the attributes. - Because SymInt/SymFloat are easy Python wrappers, __sym_dispatch__ now takes SymInt/SymFloat, rather than SymNode, bringing it in line with how __torch_dispatch__ works. Some miscellaneous improvements: - SymInt now has a constructor that takes SymNode. Note that this constructor is ambiguous if you pass in a subclass of SymNode, so an explicit downcast is necessary. This means toSymFloat/toSymInt are no more. This is a mild optimization as it means rvalue reference works automatically. - We uniformly use the caster for c10::SymInt/SymFloat, rather than going the long way via the SymIntNode/SymFloatNode. - Removed some unnecessary toSymInt/toSymFloat calls in normalize_* functions, pretty sure this doesn't do anything. - guard_int is now a free function, since to guard on an int you cannot assume the method exists. A function can handle both int and SymInt inputs. - We clean up the magic method definition code for SymInt/SymFloat/SymNode. ONLY the user classes (SymInt/SymFloat) get magic methods; SymNode gets plain methods; this is to help avoid confusion between the two types. Signed-off-by: Edward Z. Yang <ezyang@fb.com> cc @jansel @mlazos @soumith @voznesenskym @yanboliang @penguinwu @anijain2305 Pull Request resolved: https://github.com/pytorch/pytorch/pull/87817 Approved by: https://github.com/albanD, https://github.com/anjali411
183 lines
5.1 KiB
C++
183 lines
5.1 KiB
C++
#pragma once
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#include <c10/core/SafePyObject.h>
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#include <c10/core/SymNodeImpl.h>
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#include <torch/csrc/autograd/python_variable.h>
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#include <torch/csrc/utils/pybind.h>
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namespace torch {
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TORCH_PYTHON_API py::handle get_symint_class();
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TORCH_PYTHON_API py::handle get_symfloat_class();
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// NB: These functions must not be called too early, otherwise torch not setup.
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// Alternate design is to have torch "register" the object to us
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inline bool is_symint(py::handle obj) {
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return py::isinstance(obj, get_symint_class());
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}
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inline bool is_symfloat(py::handle obj) {
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return py::isinstance(obj, get_symfloat_class());
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}
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namespace impl {
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// This c10::SymNodeImpl simply backends to a Python object that
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// implements the API. The Python object is the source of truth,
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// this is just an adapter so C++ calls can get to the object.
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class PythonSymNodeImpl : public c10::SymNodeImpl {
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public:
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PythonSymNodeImpl(py::object pyobj) : c10::SymNodeImpl() {
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pyobj_ = std::make_shared<c10::SafePyObject>(
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pyobj.release().ptr(), getPyInterpreter());
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};
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c10::SymNode wrap_int(int64_t num) override {
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py::gil_scoped_acquire acquire;
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auto r = getPyObj().attr("wrap_int")(num);
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return c10::make_intrusive<PythonSymNodeImpl>(r);
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}
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c10::SymNode wrap_float(double num) override {
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py::gil_scoped_acquire acquire;
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auto r = getPyObj().attr("wrap_float")(num);
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return c10::make_intrusive<PythonSymNodeImpl>(r);
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}
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bool bool_() override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("bool_")().is(py::handle(Py_True));
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}
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bool is_int() override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("is_int")().is(py::handle(Py_True));
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}
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bool is_float() override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("is_float")().is(py::handle(Py_True));
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}
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int64_t guard_int(const char* file, int64_t line) override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("guard_int")(file, line).cast<int64_t>();
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}
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double guard_float(const char* file, int64_t line) override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("guard_float")(file, line).cast<double>();
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}
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int64_t int_() override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("int_")().cast<int64_t>();
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}
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std::string str() override {
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py::gil_scoped_acquire acquire;
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return getPyObj().attr("str")().cast<std::string>();
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}
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c10::SymNode dispatch_common_(const char* fname, const c10::SymNode& other) {
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auto pother = dynamic_cast<PythonSymNodeImpl*>(other.get());
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TORCH_CHECK(pother);
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py::gil_scoped_acquire acquire;
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auto r = getPyObj().attr(fname)(pother->getPyObj());
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return c10::make_intrusive<PythonSymNodeImpl>(r);
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}
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c10::SymNode dispatch_common_(const char* fname) {
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py::gil_scoped_acquire acquire;
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auto r = getPyObj().attr(fname)();
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return c10::make_intrusive<PythonSymNodeImpl>(r);
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}
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c10::SymNode add(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode sub(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode mul(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode truediv(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode pow(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode floordiv(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode mod(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode eq(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode gt(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode lt(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode le(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode ge(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode min(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode max(const c10::SymNode& other) override {
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return dispatch_common_(__FUNCTION__, other);
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}
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c10::SymNode ceil() override {
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return dispatch_common_(__FUNCTION__);
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}
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c10::SymNode floor() override {
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return dispatch_common_(__FUNCTION__);
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}
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c10::SymNode neg() override {
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return dispatch_common_(__FUNCTION__);
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}
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c10::SymNode clone() override {
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return dispatch_common_(__FUNCTION__);
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}
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c10::SymNode sym_int() override {
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return dispatch_common_(__FUNCTION__);
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}
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c10::SymNode sym_float() override {
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return dispatch_common_(__FUNCTION__);
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}
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py::handle getPyObj() {
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return py::handle(pyobj_.get()->ptr(getPyInterpreter()));
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}
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std::shared_ptr<c10::SafePyObject> pyobj_ = nullptr;
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};
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} // namespace impl
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} // namespace torch
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