mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
This reverts commit b428f1ad77aedfd150e920c8b0d23b7e6393ad6f.
Reverted https://github.com/pytorch/pytorch/pull/129185 on behalf of https://github.com/huydhn due to dr ci categorization is wrong, the test_linalg xsuccess is real, theres also a test_jit failure https://github.com/pytorch/pytorch/actions/runs/9844339391/job/27178009798 b428f1ad77
([comment](https://github.com/pytorch/pytorch/pull/129185#issuecomment-2215230345))
866 lines
30 KiB
C
866 lines
30 KiB
C
#define PY_SSIZE_T_CLEAN
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#include <torch/csrc/dynamo/cache_entry.h>
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#include <torch/csrc/dynamo/cpp_shim.h>
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#include <torch/csrc/dynamo/cpython_defs.h>
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#include <torch/csrc/dynamo/debug_macros.h>
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#include <torch/csrc/dynamo/extra_state.h>
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#include <torch/csrc/utils/python_compat.h>
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#include <opcode.h>
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#include <stdbool.h>
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PyObject* guard_error_hook = NULL;
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const char* cache_lookup_profiler_str = "TorchDynamo Cache Lookup";
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static int active_dynamo_threads = 0;
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static Py_tss_t eval_frame_callback_key = Py_tss_NEEDS_INIT;
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inline static PyObject* eval_frame_callback_get(void) {
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void* result = PyThread_tss_get(&eval_frame_callback_key);
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if (unlikely(result == NULL)) {
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return (PyObject*)Py_None;
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} else {
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return (PyObject*)result;
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}
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}
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inline static void eval_frame_callback_set(PyObject* obj) {
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PyThread_tss_set(&eval_frame_callback_key, obj);
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}
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// 3.14 Not supported at all. See cpython_defs.c for hints
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#if !(IS_PYTHON_3_14_PLUS)
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// Problem in CPython includes when mixing core and non-core build
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// The fix was not backported to 3.12 so this is needed here
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// https://github.com/python/cpython/issues/105268
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#if IS_PYTHON_3_12_PLUS
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#undef _PyGC_FINALIZED
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#endif
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// see https://bugs.python.org/issue35886
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#if PY_VERSION_HEX >= 0x03080000
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#define Py_BUILD_CORE
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#include <internal/pycore_pystate.h>
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// These headers were added in 3.11
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#if IS_PYTHON_3_11_PLUS
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#include <internal/pycore_frame.h>
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#endif
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#undef Py_BUILD_CORE
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#endif // PY_VERSION_HEX >= 0x03080000
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// All the eval APIs change in 3.11 so we need to decide which one to use on the fly
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// https://docs.python.org/3/c-api/init.html#c._PyFrameEvalFunction
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#if IS_PYTHON_3_11_PLUS
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#define THP_EVAL_API_FRAME_OBJECT _PyInterpreterFrame
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// We need to be able to return the _PyInterpreterFrame to python so create
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// a python binding for it
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typedef struct THPPyInterpreterFrame {
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PyObject_HEAD
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_PyInterpreterFrame* frame; // Borrowed reference
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} THPPyInterpreterFrame;
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THPPyInterpreterFrame* THPPyInterpreterFrame_New(_PyInterpreterFrame* frame);
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#define DECLARE_PYOBJ_ATTR(name) \
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static PyObject* THPPyInterpreterFrame_##name(THPPyInterpreterFrame* self, PyObject* _noargs) { \
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PyObject* res = (PyObject*)self->frame->name; \
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Py_XINCREF(res); \
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return res; \
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}
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#if IS_PYTHON_3_12_PLUS
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DECLARE_PYOBJ_ATTR(f_funcobj)
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#else
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DECLARE_PYOBJ_ATTR(f_func)
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#endif
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DECLARE_PYOBJ_ATTR(f_globals)
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DECLARE_PYOBJ_ATTR(f_builtins)
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DECLARE_PYOBJ_ATTR(f_locals)
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#if IS_PYTHON_3_13_PLUS
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DECLARE_PYOBJ_ATTR(f_executable)
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#else
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DECLARE_PYOBJ_ATTR(f_code)
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#endif
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DECLARE_PYOBJ_ATTR(frame_obj)
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#undef DECLARE_PYOBJ_ATTR
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static THPPyInterpreterFrame* THPPyInterpreterFrame_previous(THPPyInterpreterFrame* self, PyObject* _noargs) {
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THPPyInterpreterFrame* res = THPPyInterpreterFrame_New(self->frame->previous);
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return res;
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}
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// This is not a true attribute of the class but we do access it in python and it is hard to implement
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// on the python side, so do it here:
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static PyObject* THPPyInterpreterFrame_f_lasti(THPPyInterpreterFrame* self, PyObject* _noargs) {
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return PyLong_FromLong(_PyInterpreterFrame_LASTI(self->frame));
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}
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static PyObject* THPPyInterpreterFrame_f_lineno(THPPyInterpreterFrame* self, PyObject* _noargs) {
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if (!self->frame->frame_obj) {
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return PyLong_FromLong(F_CODE(self->frame)->co_firstlineno);
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}
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int lineno = PyFrame_GetLineNumber(self->frame->frame_obj);
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if (lineno < 0) {
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Py_RETURN_NONE;
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}
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return PyLong_FromLong(lineno);
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}
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static PyObject* THPPyInterpreterFrame_f_back(THPPyInterpreterFrame* self, PyObject* _noargs) {
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if (!self->frame->frame_obj) {
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Py_RETURN_NONE;
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}
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return (PyObject*)PyFrame_GetBack(self->frame->frame_obj);
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}
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables,modernize-avoid-c-arrays)
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static struct PyGetSetDef THPPyInterpreterFrame_properties[] = {
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#if IS_PYTHON_3_12_PLUS
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{"f_func", (getter)THPPyInterpreterFrame_f_funcobj, NULL, NULL, NULL},
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#else
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{"f_func", (getter)THPPyInterpreterFrame_f_func, NULL, NULL, NULL},
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#endif
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{"f_globals", (getter)THPPyInterpreterFrame_f_globals, NULL, NULL, NULL},
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{"f_builtins", (getter)THPPyInterpreterFrame_f_builtins, NULL, NULL, NULL},
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{"f_locals", (getter)THPPyInterpreterFrame_f_locals, NULL, NULL, NULL},
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#if IS_PYTHON_3_13_PLUS
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{"f_code", (getter)THPPyInterpreterFrame_f_executable, NULL, NULL, NULL},
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#else
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{"f_code", (getter)THPPyInterpreterFrame_f_code, NULL, NULL, NULL},
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#endif
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{"frame_obj", (getter)THPPyInterpreterFrame_frame_obj, NULL, NULL, NULL},
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{"previous", (getter)THPPyInterpreterFrame_previous, NULL, NULL, NULL},
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{"f_lasti", (getter)THPPyInterpreterFrame_f_lasti, NULL, NULL, NULL},
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{"f_lineno", (getter)THPPyInterpreterFrame_f_lineno, NULL, NULL, NULL},
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{"f_back", (getter)THPPyInterpreterFrame_f_back, NULL, NULL, NULL},
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{NULL}};
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static PyTypeObject THPPyInterpreterFrameType = {
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PyVarObject_HEAD_INIT(NULL, 0)
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.tp_name = "torch._C.dynamo.eval_frame._PyInterpreterFrame",
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.tp_basicsize = sizeof(THPPyInterpreterFrame),
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.tp_flags = Py_TPFLAGS_DEFAULT,
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.tp_getset = THPPyInterpreterFrame_properties,
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};
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THPPyInterpreterFrame* THPPyInterpreterFrame_New(_PyInterpreterFrame* frame) {
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PyTypeObject* type = (PyTypeObject*)&THPPyInterpreterFrameType;
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THPPyInterpreterFrame* self = (THPPyInterpreterFrame*)type->tp_alloc(type, 0);
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if (!self)
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return NULL;
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self->frame = frame;
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return self;
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}
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#else
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#define THP_EVAL_API_FRAME_OBJECT PyFrameObject
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static int
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THP_PyFrame_FastToLocalsWithError(THP_EVAL_API_FRAME_OBJECT *frame, int *free_vars_copied) {
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return PyFrame_FastToLocalsWithError(frame);
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}
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#endif
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static PyObject* _custom_eval_frame_shim(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame,
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int throw_flag);
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static PyObject* _custom_eval_frame(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame,
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int throw_flag,
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PyObject* callback,
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int* should_clear_frame);
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static PyObject *(*previous_eval_frame)(PyThreadState *tstate,
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THP_EVAL_API_FRAME_OBJECT* frame, int throw_flag) = NULL;
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#if PY_VERSION_HEX >= 0x03090000
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static PyObject* custom_eval_frame_shim(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame,
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int throw_flag) {
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return _custom_eval_frame_shim(tstate, frame, throw_flag);
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}
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#else
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static PyObject* custom_eval_frame_shim(THP_EVAL_API_FRAME_OBJECT* frame, int throw_flag) {
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PyThreadState* tstate = PyThreadState_GET();
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return _custom_eval_frame_shim(tstate, frame, throw_flag);
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}
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#endif
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inline static PyObject* eval_frame_default(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame,
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int throw_flag) {
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#if PY_VERSION_HEX >= 0x03090000
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if (tstate == NULL) {
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tstate = PyThreadState_GET();
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}
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if (previous_eval_frame) {
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return previous_eval_frame(tstate, frame, throw_flag);
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}
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else {
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return _PyEval_EvalFrameDefault(tstate, frame, throw_flag);
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}
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#else
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return _PyEval_EvalFrameDefault(frame, throw_flag);
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#endif
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}
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inline static void enable_eval_frame_shim(PyThreadState* tstate) {
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#if PY_VERSION_HEX >= 0x03090000
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if (_PyInterpreterState_GetEvalFrameFunc(tstate->interp) !=
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&custom_eval_frame_shim) {
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DEBUG_CHECK(previous_eval_frame == NULL);
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previous_eval_frame = _PyInterpreterState_GetEvalFrameFunc(tstate->interp);
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_PyInterpreterState_SetEvalFrameFunc(tstate->interp,
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&custom_eval_frame_shim);
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}
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#else
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if (tstate->interp->eval_frame != &custom_eval_frame_shim) {
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// First call
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tstate->interp->eval_frame = &custom_eval_frame_shim;
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}
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#endif
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}
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inline static void enable_eval_frame_default(PyThreadState* tstate) {
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#if PY_VERSION_HEX >= 0x03090000
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if (_PyInterpreterState_GetEvalFrameFunc(tstate->interp) !=
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previous_eval_frame) {
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DEBUG_CHECK(previous_eval_frame != NULL);
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_PyInterpreterState_SetEvalFrameFunc(tstate->interp,
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previous_eval_frame);
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previous_eval_frame = NULL;
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}
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#else
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if (tstate->interp->eval_frame != &_PyEval_EvalFrameDefault) {
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// First call
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tstate->interp->eval_frame = &_PyEval_EvalFrameDefault;
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}
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#endif
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}
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inline static const char* get_frame_name(THP_EVAL_API_FRAME_OBJECT* frame) {
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// Returns the C string name of the current frame.
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DEBUG_CHECK(PyUnicode_Check(F_CODE(frame)->co_name));
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return PyUnicode_AsUTF8(F_CODE(frame)->co_name);
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}
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static inline PyObject* call_callback(
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PyObject* callable,
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THP_EVAL_API_FRAME_OBJECT* _frame,
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CacheEntry* cache_entry,
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FrameState* frame_state) {
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// remember to update the type signature for DynamoCallbackFn.__call__ in torch/_dynamo/types.py
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// if this function changes
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#if IS_PYTHON_3_11_PLUS
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THPPyInterpreterFrame* frame = THPPyInterpreterFrame_New(_frame);
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if (frame == NULL) {
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return NULL;
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}
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#else
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PyObject* frame = Py_NewRef(_frame);
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#endif
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PyObject* cache_entry_pyobj = CacheEntry_to_obj(cache_entry);
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PyObject* res = PyObject_CallFunction(
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callable,
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"OOO",
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frame,
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cache_entry_pyobj,
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frame_state);
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Py_DECREF(frame);
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Py_DECREF(cache_entry_pyobj);
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return res;
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}
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static inline void clear_old_frame_if_python_312_plus(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame) {
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#if IS_PYTHON_3_12_PLUS
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THP_PyFrame_Clear(frame);
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THP_PyThreadState_PopFrame(tstate, frame);
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#endif
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}
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inline static PyObject* eval_custom_code_impl(
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PyThreadState* tstate,
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THP_EVAL_API_FRAME_OBJECT* frame,
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PyCodeObject* code,
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int throw_flag,
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int free_vars_copied) {
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DEBUG_NULL_CHECK(tstate);
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DEBUG_NULL_CHECK(frame);
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DEBUG_NULL_CHECK(code);
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#if IS_PYTHON_3_11_PLUS
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// Generate Python function object and _PyInterpreterFrame in a way similar to
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// https://github.com/python/cpython/blob/e715da6db1d1d70cd779dc48e1ba8110c51cc1bf/Python/ceval.c#L1130
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#if IS_PYTHON_3_12_PLUS
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PyFunctionObject* old_func = (PyFunctionObject*) frame->f_funcobj;
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size_t size = code->co_framesize;
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#else
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PyFunctionObject* old_func = frame->f_func;
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size_t size = code->co_nlocalsplus + code->co_stacksize + FRAME_SPECIALS_SIZE;
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#endif
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PyFunctionObject* func = _PyFunction_CopyWithNewCode(old_func, code);
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if (func == NULL) {
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return NULL;
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}
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THP_EVAL_API_FRAME_OBJECT* shadow = THP_PyThreadState_BumpFramePointerSlow(tstate, size);
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if (shadow == NULL) {
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Py_DECREF(func);
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return NULL;
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}
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Py_INCREF(func);
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// consumes reference to func
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#if IS_PYTHON_3_12_PLUS
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_PyFrame_Initialize(shadow, func, NULL, code, 0);
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#else
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_PyFrame_InitializeSpecials(shadow, func, NULL, code->co_nlocalsplus);
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#endif
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PyObject** fastlocals_old = frame->localsplus;
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PyObject** fastlocals_new = shadow->localsplus;
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Py_ssize_t n_old = F_CODE(frame)->co_nlocalsplus;
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Py_ssize_t n_new = code->co_nlocalsplus;
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// localsplus are XINCREF'd by default eval frame, so all values must be valid.
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#if !(IS_PYTHON_3_12_PLUS)
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// _PyFrame_Initialize in 3.12 already does this
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for (int i = 0; i < code->co_nlocalsplus; i++) {
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fastlocals_new[i] = NULL;
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}
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#endif
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// for 3.11+, if free_vars_copied is true, we do not need to
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// run the first COPY_FREE_VARS since THP_PyFrame_FastToLocalsWithError
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// already did the equivalent action.
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if (free_vars_copied && _Py_OPCODE(_PyCode_CODE(F_CODE(shadow))[0]) == COPY_FREE_VARS) {
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PREV_INSTR(shadow) = _PyCode_CODE(F_CODE(shadow));
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}
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#else
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THP_EVAL_API_FRAME_OBJECT* shadow = PyFrame_New(tstate, code, frame->f_globals, NULL);
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if (shadow == NULL) {
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return NULL;
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}
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PyObject** fastlocals_old = frame->f_localsplus;
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PyObject** fastlocals_new = shadow->f_localsplus;
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Py_ssize_t n_old = F_CODE(frame)->co_nlocals + PyCode_GetNFreevars(F_CODE(frame)) + PyCode_GetNCellvars(F_CODE(frame));
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Py_ssize_t n_new = code->co_nlocals + PyCode_GetNFreevars(code) + PyCode_GetNCellvars(code);
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#endif
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// ============== Initialize new frame from old frame ============
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// Python internal for executing a function:
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// 1. CPython interpreter first creates an empty frame according to the code object
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// 2. CPython interpreter initializes the frame by filling arguments/free variables into frame and initializing cell variables
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// 3. CPython interpreter executes the code object
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//
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// Dynamo hooks the 3th step: before executing the code object, Dynamo transforms the code object into a new code object. Then, the old frame is not suitable for executing the new code. Therefore, Dynamo needs to manually create and initialize a new frame to execute the new code.
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// The main task is to copy data in old frame to new frame, concerning a storage space named `localsplus`.
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//
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// localsplus storage is an array with the following layout:
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// | args | new_locals | cell_variables | free_variables |
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// | <--- from left to right, index from 0 to n - 1 ---> |
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// code.co_varnames == args + new_locals, code.co_nlocals == len(code.co_varnames)
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// code.co_freevars == free_variables
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// In Python 3.10 and lower, `n == code.co_nlocals + len(code.co_cellvars) + len(code.co_freevars)` (Python expression)
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// In Python 3.11 and higher, `n <= code.co_nlocals + len(code.co_cellvars) + len(code.co_freevars)` (Python expression). There is an extra field in Python C-API: `n == code->co_nlocalsplus` (C expression) to retrieve the length of array.
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// The complexity happens if an argument becomes a cell variable:
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// In Python 3.10 and lower, `code.co_cellvars == cell_variables`, and the corresponding slot in args becomes `NULL`.
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// In Python 3.11 and higher, `code.co_cellvars > cell_variables`, that cell variable is still stored in args, with a flag set in corresponding item's `co_localspluskinds` .
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//
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// ideally, we need to look up new localsplus from old localsplus by name:
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// for i, name, value in enumerate(localsplusnames_old):
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// if value != NULL: (NULL happens for new local variables and arguments that becomes cell variables)
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// name_to_idx[name] = i
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// for i, name in enumerate(localsplusnames_new):
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// if name in name_to_idx:
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// fastlocals_new[i] = fastlocals_old[name_to_idx[name]]
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//
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// The above process of building a `name_to_idx` mapping is expensive.
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// Dynamo makes the following assumptions:
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// 1. new code has the same arguments as the old code (both the number and the order)
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// 2. new code has the same cell variables as the old code (both the number and the order)
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// 3. new code has the same free variables as the old code (both the number and the order)
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// The only flexibility lies in new local variables: new code can introduce their own variables.
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// With these assumptions, Dynamo can copy data directly by index. Dynamo just needs to take care of copying cell variables correctly.
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// To avoid runtime cost, the assumptions are checked when we first generate the code object in pytorch/torch/_dynamo/convert_frame.py .
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// copy args
|
|
// according to https://docs.python.org/3/library/inspect.html , `co_argcount` is the number of arguments (not including keyword only arguments, * or ** args). so we need to add `co_kwonlyargcount` and `co_flags` to get the total number of arguments.
|
|
// !!(F_CODE(frame)->co_flags & CO_VARARGS) is 1 if the function has *args, 0 otherwise
|
|
// !!(F_CODE(frame)->co_flags & CO_VARKEYWORDS) is 1 if the function has **kwargs, 0 otherwise
|
|
// they convert bit flags to 0 or 1, and avoid branching.
|
|
// This is performance critical code, so we really care about performance.
|
|
Py_ssize_t total_argcount_old = F_CODE(frame)->co_argcount + F_CODE(frame)->co_kwonlyargcount + !!(F_CODE(frame)->co_flags & CO_VARARGS) + !!(F_CODE(frame)->co_flags & CO_VARKEYWORDS);
|
|
|
|
for (Py_ssize_t i = 0; i < total_argcount_old; i++) {
|
|
Py_XINCREF(fastlocals_old[i]);
|
|
fastlocals_new[i] = fastlocals_old[i];
|
|
}
|
|
|
|
// copy free vars
|
|
Py_ssize_t nfrees_old = PyCode_GetNFreevars(F_CODE(frame));
|
|
|
|
for (Py_ssize_t i = 0; i < nfrees_old; i++) {
|
|
Py_XINCREF(fastlocals_old[n_old - 1 - i]);
|
|
fastlocals_new[n_new - 1 - i] = fastlocals_old[n_old - 1 - i];
|
|
}
|
|
|
|
// copy cell vars, from high index to low index, until it meets a variable that is not cell variable.
|
|
for (Py_ssize_t i = n_old - nfrees_old - 1, j = n_new - nfrees_old - 1; i >= total_argcount_old; i--, j--) {
|
|
|
|
// conditional test to tell if a variable is not a cell variable
|
|
// this is straightforward in Python 3.11 and higher, as there are bit flags in `co_localspluskinds` to tell if a variable is a cell variable.
|
|
// in Python 3.10 and lower, essentially we are checking if a variable is a new local variable (because of the layout mentioned above, the first variable that is not cell variable is the first new local variable). the corresponding slot in `flocalsplus` is NULL for new local variables.
|
|
#if IS_PYTHON_3_11_PLUS
|
|
if(!(_PyLocals_GetKind(F_CODE(frame)->co_localspluskinds, i) & CO_FAST_CELL))
|
|
{
|
|
break;
|
|
}
|
|
#else
|
|
if(fastlocals_old[i] == NULL)
|
|
{
|
|
break;
|
|
}
|
|
#endif
|
|
|
|
Py_XINCREF(fastlocals_old[i]);
|
|
fastlocals_new[j] = fastlocals_old[i];
|
|
}
|
|
|
|
// NOTE: if you want to evaluate frame instead of shadow in 3.12+,
|
|
// you need to clear_old_frame_if_python_312_plus the shadow frame BEFORE
|
|
// calling eval_frame_default (i.e. here) and comment out the
|
|
// clear_old_frame_if_python_312_plus call on the original frame.
|
|
|
|
PyObject* result = eval_frame_default(tstate, shadow, throw_flag);
|
|
|
|
#if IS_PYTHON_3_12_PLUS
|
|
|
|
// frame is cleared by caller
|
|
Py_DECREF(func);
|
|
|
|
#elif IS_PYTHON_3_11_PLUS
|
|
|
|
// In 3.11, shadow has is_entry set to true, so _PyEvalFrameClearAndPop is not called,
|
|
// so we manually clear and pop the shadow frame.
|
|
THP_PyFrame_Clear(shadow);
|
|
THP_PyThreadState_PopFrame(tstate, shadow);
|
|
Py_DECREF(func);
|
|
|
|
#else
|
|
|
|
Py_DECREF(shadow);
|
|
|
|
#endif
|
|
|
|
return result;
|
|
}
|
|
|
|
// This wrapper function adds a profiler event
|
|
inline static PyObject* eval_custom_code(
|
|
PyThreadState* tstate,
|
|
THP_EVAL_API_FRAME_OBJECT* frame,
|
|
PyCodeObject* code,
|
|
int throw_flag,
|
|
int free_vars_copied) {
|
|
_PytorchRecordFunctionState* rf = _pytorch_record_function_enter("Torch-Compiled Region");
|
|
PyObject* result = eval_custom_code_impl(
|
|
tstate,
|
|
frame,
|
|
code,
|
|
throw_flag,
|
|
free_vars_copied
|
|
);
|
|
_pytorch_record_function_exit(rf);
|
|
return result;
|
|
}
|
|
|
|
static PyObject* _custom_eval_frame_shim(
|
|
PyThreadState* tstate,
|
|
THP_EVAL_API_FRAME_OBJECT* frame,
|
|
int throw_flag) {
|
|
// Shims logic into one of three states. Can probably be refactored into a
|
|
// single func, later:
|
|
// - None: disables TorchDynamo
|
|
// - False: run-only mode (reuse existing compiles)
|
|
// - Python callable(): enables TorchDynamo
|
|
PyObject* callback = eval_frame_callback_get();
|
|
|
|
if (callback == Py_None) {
|
|
return eval_frame_default(tstate, frame, throw_flag);
|
|
}
|
|
|
|
int should_clear_frame = 0;
|
|
PyObject* result = _custom_eval_frame(tstate, frame, throw_flag, callback, &should_clear_frame);
|
|
if (should_clear_frame) {
|
|
clear_old_frame_if_python_312_plus(tstate, frame);
|
|
}
|
|
return result;
|
|
}
|
|
|
|
// NOTE: In 3.12+, the frame evaluation function (callee) is responsible for clearing/popping
|
|
// the frame, meaning that unless we default evaluate the original frame,
|
|
// we are responsible for clearing it - via clear_old_frame_if_python_312_plus.
|
|
// The should_clear_frame flag is used to indicate whether the frame should be
|
|
// cleared by _custom_eval_frame's caller.
|
|
static PyObject* _custom_eval_frame(
|
|
PyThreadState* tstate,
|
|
THP_EVAL_API_FRAME_OBJECT* frame,
|
|
int throw_flag,
|
|
PyObject* callback,
|
|
int* should_clear_frame) {
|
|
#if IS_PYTHON_3_11_PLUS
|
|
DEBUG_TRACE(
|
|
"begin %s %s %i %i",
|
|
get_frame_name(frame),
|
|
PyUnicode_AsUTF8(F_CODE(frame)->co_filename),
|
|
F_CODE(frame)->co_firstlineno,
|
|
_PyInterpreterFrame_LASTI(frame));
|
|
#else
|
|
DEBUG_TRACE(
|
|
"begin %s %s %i %i %i",
|
|
get_frame_name(frame),
|
|
PyUnicode_AsUTF8(F_CODE(frame)->co_filename),
|
|
frame->f_lineno,
|
|
frame->f_lasti,
|
|
frame->f_iblock);
|
|
#endif
|
|
|
|
if (throw_flag) {
|
|
// When unwinding generators, eval frame is called with throw_flag ==
|
|
// true. Frame evaluation is supposed to continue unwinding by propagating
|
|
// the exception. Dynamo doesn't really know how to do this, nor does it
|
|
// really want to do this, because there's unlikely any code to capture
|
|
// (you're going to immediately quit out of the frame, perhaps running
|
|
// some unwinding logic along the way). So we just run the default
|
|
// handler in this case.
|
|
//
|
|
// NB: A previous version of this patch returned NULL. This is wrong,
|
|
// because returning NULL is *different* from unwinding an exception.
|
|
// In particular, you will not execute things like context manager
|
|
// __exit__ if you just return NULL.
|
|
//
|
|
// NB: It's /conceivable/ that you might want to actually still call the
|
|
// Dynamo callback when throw_flag == TRUE, to give Dynamo a chance to
|
|
// do any stack unwinding code. But this is not really useful because
|
|
// (1) Dynamo doesn't actually know how to do stack unwinding, so it would
|
|
// immediately skip the frame, and (2) even if it did, this would only
|
|
// be profitable if there was tensor code in the unwinding code. Seems
|
|
// unlikely.
|
|
DEBUG_TRACE("throw %s", get_frame_name(frame));
|
|
return eval_frame_default(tstate, frame, throw_flag);
|
|
}
|
|
|
|
ExtraState* extra = get_extra_state(F_CODE(frame));
|
|
if (extra == SKIP_CODE || (callback == Py_False && extra == NULL)) {
|
|
DEBUG_TRACE("skip %s", get_frame_name(frame));
|
|
return eval_frame_default(tstate, frame, throw_flag);
|
|
}
|
|
|
|
if (extra == NULL) {
|
|
extra = init_and_set_extra_state(F_CODE(frame));
|
|
}
|
|
|
|
// TODO(jansel): investigate directly using the "fast" representation
|
|
int free_vars_copied = 0;
|
|
if (THP_PyFrame_FastToLocalsWithError(frame, &free_vars_copied) < 0) {
|
|
DEBUG_TRACE("error %s", get_frame_name(frame));
|
|
*should_clear_frame = 1;
|
|
return NULL;
|
|
}
|
|
|
|
PyObject* backend = get_backend(callback);
|
|
|
|
// A callback of Py_False indicates "run only" mode, the cache is checked, but
|
|
// we never compile.
|
|
if (callback == Py_False) {
|
|
DEBUG_TRACE("In run only mode %s", get_frame_name(frame));
|
|
_PytorchRecordFunctionState* rf = _pytorch_record_function_enter(cache_lookup_profiler_str);
|
|
PyObject* maybe_cached_code = lookup(extra, frame->f_locals, backend);
|
|
_pytorch_record_function_exit(rf);
|
|
|
|
if (maybe_cached_code == NULL) {
|
|
// guard eval failed, keep propagating
|
|
*should_clear_frame = 1;
|
|
return NULL;
|
|
} else if (maybe_cached_code == Py_None) {
|
|
DEBUG_TRACE("cache miss %s", get_frame_name(frame));
|
|
return eval_frame_default(tstate, frame, throw_flag);
|
|
}
|
|
PyCodeObject* cached_code = (PyCodeObject*)maybe_cached_code;
|
|
// used cached version
|
|
DEBUG_TRACE("cache hit %s", get_frame_name(frame));
|
|
*should_clear_frame = 1;
|
|
return eval_custom_code(tstate, frame, cached_code, throw_flag, free_vars_copied);
|
|
}
|
|
DEBUG_CHECK(PyDict_CheckExact(frame->f_locals));
|
|
DEBUG_CHECK(PyDict_CheckExact(frame->f_globals));
|
|
DEBUG_CHECK(PyDict_CheckExact(frame->f_builtins));
|
|
|
|
// We don't run the current custom_eval_frame behavior for guards.
|
|
// So we temporarily set the callback to Py_None to drive the correct behavior
|
|
// in the shim.
|
|
eval_frame_callback_set(Py_None);
|
|
|
|
_PytorchRecordFunctionState* rf = _pytorch_record_function_enter(cache_lookup_profiler_str);
|
|
PyObject* maybe_cached_code = lookup(extra, frame->f_locals, backend);
|
|
_pytorch_record_function_exit(rf);
|
|
if (maybe_cached_code == NULL) {
|
|
// Python error
|
|
*should_clear_frame = 1;
|
|
return NULL;
|
|
} else if (maybe_cached_code != Py_None) {
|
|
PyCodeObject* cached_code = (PyCodeObject*)maybe_cached_code;
|
|
// used cached version
|
|
DEBUG_TRACE("cache hit %s", get_frame_name(frame));
|
|
// Re-enable custom behavior
|
|
eval_frame_callback_set(callback);
|
|
*should_clear_frame = 1;
|
|
return eval_custom_code(tstate, frame, cached_code, throw_flag, free_vars_copied);
|
|
}
|
|
// cache miss
|
|
CacheEntry* cache_entry = extract_cache_entry(extra);
|
|
FrameState* frame_state = extract_frame_state(extra);
|
|
PyObject* result =
|
|
call_callback(callback, frame, cache_entry, frame_state);
|
|
if (result == NULL) {
|
|
// internal exception, returning here will leak the exception into user code
|
|
// this is useful for debugging -- but we dont want it to happen outside of
|
|
// testing
|
|
// NB: we intentionally DO NOT re-enable custom behavior to prevent
|
|
// cascading failure from internal exceptions. The upshot is if
|
|
// Dynamo barfs, that's it for Dynamo, even if you catch the exception
|
|
// inside the torch.compile block we won't try to Dynamo anything else.
|
|
*should_clear_frame = 1;
|
|
return NULL;
|
|
} else if (result != Py_None) {
|
|
DEBUG_TRACE("create cache %s", get_frame_name(frame));
|
|
|
|
// NB: We could use extract_cache_entry to get the cache_entry, but
|
|
// extract_cache_entry returns a borrowed reference. Modifying a borrowed
|
|
// reference seems wrong. Therefore, we directly access the
|
|
// extra->cache_entry. extra wont be NULL here.
|
|
CacheEntry* new_cache_entry = create_cache_entry(extra, result, backend);
|
|
Py_DECREF(result);
|
|
|
|
// Update the existing cache_entry on the extra object. This extra object is
|
|
// sitting on the extra scratch space, we are just changing the cache_entry
|
|
// ptr. As a result, extra now becomes the owner of CacheEntry object. This
|
|
// will be cleaned up when set_extra_state is called.
|
|
// Re-enable custom behavior
|
|
eval_frame_callback_set(callback);
|
|
*should_clear_frame = 1;
|
|
return eval_custom_code(tstate, frame, CacheEntry_get_code(new_cache_entry), throw_flag, free_vars_copied);
|
|
} else {
|
|
DEBUG_TRACE("create skip %s", get_frame_name(frame));
|
|
Py_DECREF(result);
|
|
set_extra_state(F_CODE(frame), SKIP_CODE);
|
|
// Re-enable custom behavior
|
|
eval_frame_callback_set(callback);
|
|
return eval_frame_default(tstate, frame, throw_flag);
|
|
}
|
|
}
|
|
|
|
#else // IS_PYTHON_3_14_PLUS
|
|
|
|
// Fake definitions for everything we removed
|
|
|
|
typedef struct THPPyInterpreterFrame {
|
|
PyObject_HEAD
|
|
_PyInterpreterFrame* frame; // Borrowed reference
|
|
} THPPyInterpreterFrame;
|
|
|
|
inline static void enable_eval_frame_shim(PyThreadState* tstate) {}
|
|
inline static void enable_eval_frame_default(PyThreadState* tstate) {}
|
|
|
|
static struct PyGetSetDef THPPyInterpreterFrame_properties[] = {NULL};
|
|
|
|
static PyTypeObject THPPyInterpreterFrameType = {
|
|
PyVarObject_HEAD_INIT(NULL, 0)
|
|
.tp_name = "torch._C.dynamo.eval_frame._PyInterpreterFrame",
|
|
.tp_basicsize = sizeof(THPPyInterpreterFrame),
|
|
.tp_flags = Py_TPFLAGS_DEFAULT,
|
|
.tp_getset = THPPyInterpreterFrame_properties,
|
|
};
|
|
|
|
#endif // CPython 3.14
|
|
|
|
static PyObject* increment_working_threads(PyThreadState* tstate) {
|
|
active_dynamo_threads = active_dynamo_threads + 1;
|
|
if (active_dynamo_threads > 0) {
|
|
enable_eval_frame_shim(tstate);
|
|
}
|
|
Py_RETURN_NONE;
|
|
}
|
|
|
|
static PyObject* decrement_working_threads(PyThreadState* tstate) {
|
|
if (active_dynamo_threads > 0) {
|
|
active_dynamo_threads = active_dynamo_threads - 1;
|
|
if (active_dynamo_threads == 0) {
|
|
enable_eval_frame_default(tstate);
|
|
}
|
|
}
|
|
Py_RETURN_NONE;
|
|
}
|
|
|
|
static PyObject* set_eval_frame(PyObject* new_callback, PyThreadState* tstate) {
|
|
// Change the eval frame callback and return the old one
|
|
// - None: disables TorchDynamo
|
|
// - False: run-only mode (reuse existing compiles)
|
|
// - Python callable(): enables TorchDynamo
|
|
PyObject* old_callback = eval_frame_callback_get();
|
|
|
|
// owned by caller
|
|
Py_INCREF(old_callback);
|
|
|
|
if (old_callback != Py_None && new_callback == Py_None) {
|
|
decrement_working_threads(tstate);
|
|
} else if (old_callback == Py_None && new_callback != Py_None) {
|
|
increment_working_threads(tstate);
|
|
}
|
|
|
|
Py_INCREF(new_callback);
|
|
Py_DECREF(old_callback);
|
|
|
|
// Set thread local callback. This will drive behavior of our shim, if/when it
|
|
// is installed.
|
|
eval_frame_callback_set(new_callback);
|
|
|
|
return old_callback;
|
|
}
|
|
|
|
static PyObject* set_eval_frame_py(PyObject* dummy, PyObject* callback) {
|
|
if (callback != Py_None && callback != Py_False &&
|
|
!PyCallable_Check(callback)) {
|
|
DEBUG_TRACE0("arg error");
|
|
PyErr_SetString(PyExc_TypeError, "expected a callable");
|
|
return NULL;
|
|
}
|
|
DEBUG_TRACE(
|
|
"python enabled=%d and is run_only=%d",
|
|
callback != Py_None,
|
|
callback == Py_False);
|
|
return set_eval_frame(callback, PyThreadState_GET());
|
|
}
|
|
|
|
static PyObject* reset_code(PyObject* dummy, PyObject* code) {
|
|
if (!PyCode_Check(code)) {
|
|
DEBUG_TRACE0("arg error");
|
|
PyErr_SetString(PyExc_TypeError, "expected a code object");
|
|
return NULL;
|
|
}
|
|
|
|
// set_extra_state destroys the existing object on extra scratch space.
|
|
set_extra_state((PyCodeObject*)code, NULL);
|
|
Py_RETURN_NONE;
|
|
}
|
|
|
|
static PyObject* unsupported(PyObject* dummy, PyObject* args) {
|
|
// a dummy C function used in testing
|
|
PyObject* obj1 = NULL;
|
|
PyObject* obj2 = NULL;
|
|
if (!PyArg_ParseTuple(args, "OO", &obj1, &obj2)) {
|
|
return NULL;
|
|
}
|
|
Py_INCREF(obj2);
|
|
return obj2;
|
|
}
|
|
|
|
static PyObject* skip_code(PyObject* dummy, PyObject* obj) {
|
|
if (!PyCode_Check(obj)) {
|
|
PyErr_SetString(PyExc_TypeError, "expected a code object");
|
|
return NULL;
|
|
}
|
|
|
|
// set_extra_state destroys the existing object on extra scratch space.
|
|
set_extra_state((PyCodeObject*)obj, SKIP_CODE);
|
|
Py_RETURN_NONE;
|
|
}
|
|
|
|
static PyObject* set_guard_error_hook(PyObject* dummy, PyObject* obj) {
|
|
if (obj == Py_None) {
|
|
obj = NULL;
|
|
}
|
|
Py_XSETREF(guard_error_hook, Py_XNewRef(obj));
|
|
Py_RETURN_NONE;
|
|
}
|
|
|
|
static PyMethodDef _methods[] = {
|
|
{"set_eval_frame", set_eval_frame_py, METH_O, NULL},
|
|
{"reset_code", reset_code, METH_O, NULL},
|
|
{"unsupported", unsupported, METH_VARARGS, NULL},
|
|
{"skip_code", skip_code, METH_O, NULL},
|
|
{"set_guard_error_hook", set_guard_error_hook, METH_O, NULL},
|
|
{NULL, NULL, 0, NULL}};
|
|
|
|
static struct PyModuleDef _module = {
|
|
PyModuleDef_HEAD_INIT,
|
|
"torch._C._dynamo.eval_frame",
|
|
"Module containing hooks to override eval_frame",
|
|
-1,
|
|
_methods};
|
|
|
|
#if IS_PYTHON_3_12_PLUS
|
|
#define _PyEval_RequestCodeExtraIndex PyUnstable_Eval_RequestCodeExtraIndex
|
|
#endif
|
|
|
|
PyObject* torch_c_dynamo_eval_frame_init(void) {
|
|
extra_index = _PyEval_RequestCodeExtraIndex(destroy_extra_state);
|
|
if (extra_index < 0) {
|
|
PyErr_SetString(PyExc_RuntimeError,
|
|
"dynamo: unable to register extra index");
|
|
return NULL;
|
|
}
|
|
|
|
int result = PyThread_tss_create(&eval_frame_callback_key);
|
|
CHECK(result == 0);
|
|
|
|
Py_INCREF(Py_None);
|
|
eval_frame_callback_set(Py_None);
|
|
|
|
PyObject* module = PyModule_Create(&_module);
|
|
if (module == NULL) {
|
|
return NULL;
|
|
}
|
|
|
|
#if IS_PYTHON_3_11_PLUS
|
|
if (PyType_Ready(&THPPyInterpreterFrameType) < 0) {
|
|
return NULL;
|
|
}
|
|
Py_INCREF(&THPPyInterpreterFrameType);
|
|
if (PyModule_AddObject(module, "_PyInterpreterFrame", (PyObject*)&THPPyInterpreterFrameType) != 0) {
|
|
return NULL;
|
|
}
|
|
#endif
|
|
|
|
return module;
|
|
}
|