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#define PY_SSIZE_T_CLEAN
#include <torch/csrc/dynamo/cache_entry.h>
#include <torch/csrc/dynamo/cpp_shim.h>
#include <torch/csrc/dynamo/cpython_defs.h>
#include <torch/csrc/dynamo/cpython_includes.h>
#include <torch/csrc/dynamo/debug_macros.h>
#include <torch/csrc/dynamo/extra_state.h>
#include <torch/csrc/dynamo/framelocals_mapping.h>
#include <torch/csrc/utils/python_compat.h>
#include <opcode.h>
#include <signal.h>
#include <stdbool.h>
PyObject* guard_error_hook = NULL;
const char* cache_lookup_profiler_str = "TorchDynamo Cache Lookup";
static int active_dynamo_threads = 0;
static Py_tss_t eval_frame_callback_key = Py_tss_NEEDS_INIT;
static PyObject* eval_frame_callback_get(void) {
void* result = PyThread_tss_get(&eval_frame_callback_key);
if (unlikely(result == NULL)) {
return (PyObject*)Py_None;
} else {
return (PyObject*)result;
}
}
static void eval_frame_callback_set(PyObject* obj) {
PyThread_tss_set(&eval_frame_callback_key, obj);
}
// 3.14 Not supported at all. See cpython_defs.c for hints
#if !(IS_PYTHON_3_14_PLUS)
// All the eval APIs change in 3.11 so we need to decide which one to use on the fly
// https://docs.python.org/3/c-api/init.html#c._PyFrameEvalFunction
#if IS_PYTHON_3_11_PLUS
#define THP_EVAL_API_FRAME_OBJECT _PyInterpreterFrame
#else
#define THP_EVAL_API_FRAME_OBJECT PyFrameObject
#endif // IS_PYTHON_3_11_PLUS
// We need to be able to return the _PyInterpreterFrame to python so create
// a python binding for it
typedef struct THPPyInterpreterFrame {
PyObject_HEAD
THP_EVAL_API_FRAME_OBJECT* frame; // Borrowed reference
PyObject* locals;
} THPPyInterpreterFrame;
THPPyInterpreterFrame* THPPyInterpreterFrame_New(THP_EVAL_API_FRAME_OBJECT* frame);
#define DECLARE_PYOBJ_ATTR(name) \
static PyObject* THPPyInterpreterFrame_##name(THPPyInterpreterFrame* self, PyObject* _noargs) { \
PyObject* res = (PyObject*)self->frame->name; \
Py_XINCREF(res); \
return res; \
}
DECLARE_PYOBJ_ATTR(f_globals)
DECLARE_PYOBJ_ATTR(f_builtins)
static PyObject* THPPyInterpreterFrame_f_locals(THPPyInterpreterFrame* self, PyObject* _noargs) {
DEBUG_NULL_CHECK(self->locals);
Py_XINCREF(self->locals);
return self->locals;
}
#if IS_PYTHON_3_13_PLUS
DECLARE_PYOBJ_ATTR(f_executable)
#else
DECLARE_PYOBJ_ATTR(f_code)
#endif
#undef DECLARE_PYOBJ_ATTR
// This is not a true attribute of the class but we do access it in python and it is hard to implement
// on the python side, so do it here:
static PyObject* THPPyInterpreterFrame_f_lasti(THPPyInterpreterFrame* self, PyObject* _noargs) {
#if IS_PYTHON_3_11_PLUS
return PyLong_FromLong(_PyInterpreterFrame_LASTI(self->frame));
#else
return PyLong_FromLong(self->frame->f_lasti);
#endif // IS_PYTHON_3_11_PLUS
}
static PyObject* THPPyInterpreterFrame_f_lineno(THPPyInterpreterFrame* self, PyObject* _noargs) {
#if IS_PYTHON_3_11_PLUS
if (!self->frame->frame_obj) {
return PyLong_FromLong(F_CODE(self->frame)->co_firstlineno);
}
int lineno = PyFrame_GetLineNumber(self->frame->frame_obj);
if (lineno < 0) {
Py_RETURN_NONE;
}
return PyLong_FromLong(lineno);
#else
return PyLong_FromLong(self->frame->f_lineno);
#endif // IS_PYTHON_3_11_PLUS
}
static PyObject* THPPyInterpreterFrame_f_back(THPPyInterpreterFrame* self, PyObject* _noargs) {
#if IS_PYTHON_3_11_PLUS
if (!self->frame->frame_obj) {
Py_RETURN_NONE;
}
return (PyObject*)PyFrame_GetBack(self->frame->frame_obj);
#else
return Py_XNewRef(self->frame->f_back);
#endif // IS_PYTHON_3_11_PLUS
}
static PyObject* THPPyInterpreterFrame_closure(THPPyInterpreterFrame* self, PyObject* _noargs) {
#if IS_PYTHON_3_12_PLUS
PyObject* closure = ((PyFunctionObject*) self->frame->f_funcobj)->func_closure;
return closure == NULL ? PyTuple_New(0) : Py_XNewRef(closure);
#elif IS_PYTHON_3_11_PLUS
PyObject* closure = ((PyFunctionObject*) self->frame->f_func)->func_closure;
return closure == NULL ? PyTuple_New(0) : Py_XNewRef(closure);
#else
PyCodeObject* code = self->frame->f_code;
// Why this check? See
// https://github.com/python/cpython/blob/5f24da9d75bb0150781b17ee4706e93e6bb364ea/Objects/frameobject.c#L1058-L1065
if (code->co_flags & CO_OPTIMIZED) {
int size = PyTuple_GET_SIZE(code->co_freevars);
PyObject* freevars = PyTuple_New(size);
int ncells = PyTuple_GET_SIZE(code->co_cellvars);
PyObject** freevarArr = self->frame->f_localsplus + code->co_nlocals + ncells;
for (int i = 0; i < size; i++) {
PyTuple_SET_ITEM(freevars, i, Py_XNewRef(freevarArr[i]));
}
return freevars;
}
return PyTuple_New(0);
#endif // IS_PYTHON_3_11_PLUS
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables,modernize-avoid-c-arrays)
static struct PyGetSetDef THPPyInterpreterFrame_properties[] = {
{"f_globals", (getter)THPPyInterpreterFrame_f_globals, NULL, NULL, NULL},
{"f_builtins", (getter)THPPyInterpreterFrame_f_builtins, NULL, NULL, NULL},
{"f_locals", (getter)THPPyInterpreterFrame_f_locals, NULL, NULL, NULL},
#if IS_PYTHON_3_13_PLUS
{"f_code", (getter)THPPyInterpreterFrame_f_executable, NULL, NULL, NULL},
#else
{"f_code", (getter)THPPyInterpreterFrame_f_code, NULL, NULL, NULL},
#endif
{"f_lasti", (getter)THPPyInterpreterFrame_f_lasti, NULL, NULL, NULL},
{"f_lineno", (getter)THPPyInterpreterFrame_f_lineno, NULL, NULL, NULL},
{"f_back", (getter)THPPyInterpreterFrame_f_back, NULL, NULL, NULL},
{"closure", (getter)THPPyInterpreterFrame_closure, NULL, NULL, NULL},
{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,
};
THPPyInterpreterFrame* THPPyInterpreterFrame_New(THP_EVAL_API_FRAME_OBJECT* frame) {
PyTypeObject* type = (PyTypeObject*)&THPPyInterpreterFrameType;
THPPyInterpreterFrame* self = (THPPyInterpreterFrame*)type->tp_alloc(type, 0);
if (!self)
return NULL;
self->frame = frame;
self->locals = NULL;
return self;
}
static PyObject* dynamo__custom_eval_frame_shim(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
int throw_flag);
static PyObject* dynamo__custom_eval_frame(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
int throw_flag,
PyObject* callback,
int* should_clear_frame);
static PyObject *(*previous_eval_frame)(PyThreadState *tstate,
THP_EVAL_API_FRAME_OBJECT* frame, int throw_flag) = NULL;
#if PY_VERSION_HEX >= 0x03090000
static PyObject* dynamo_custom_eval_frame_shim(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
int throw_flag) {
return dynamo__custom_eval_frame_shim(tstate, frame, throw_flag);
}
#else
static PyObject* dynamo_custom_eval_frame_shim(THP_EVAL_API_FRAME_OBJECT* frame, int throw_flag) {
PyThreadState* tstate = PyThreadState_GET();
return dynamo__custom_eval_frame_shim(tstate, frame, throw_flag);
}
#endif
static PyObject* dynamo_eval_frame_default(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
int throw_flag) {
#if PY_VERSION_HEX >= 0x03090000
if (tstate == NULL) {
tstate = PyThreadState_GET();
}
if (previous_eval_frame) {
return previous_eval_frame(tstate, frame, throw_flag);
}
else {
return _PyEval_EvalFrameDefault(tstate, frame, throw_flag);
}
#else
return _PyEval_EvalFrameDefault(frame, throw_flag);
#endif
}
static void enable_eval_frame_shim(PyThreadState* tstate) {
#if PY_VERSION_HEX >= 0x03090000
if (_PyInterpreterState_GetEvalFrameFunc(tstate->interp) !=
&dynamo_custom_eval_frame_shim) {
DEBUG_CHECK(previous_eval_frame == NULL);
previous_eval_frame = _PyInterpreterState_GetEvalFrameFunc(tstate->interp);
_PyInterpreterState_SetEvalFrameFunc(tstate->interp,
&dynamo_custom_eval_frame_shim);
}
#else
if (tstate->interp->eval_frame != &custom_eval_frame_shim) {
// First call
tstate->interp->eval_frame = &custom_eval_frame_shim;
}
#endif
}
static void enable_eval_frame_default(PyThreadState* tstate) {
#if PY_VERSION_HEX >= 0x03090000
if (_PyInterpreterState_GetEvalFrameFunc(tstate->interp) !=
previous_eval_frame) {
DEBUG_CHECK(previous_eval_frame != NULL);
_PyInterpreterState_SetEvalFrameFunc(tstate->interp,
previous_eval_frame);
previous_eval_frame = NULL;
}
#else
if (tstate->interp->eval_frame != &_PyEval_EvalFrameDefault) {
// First call
tstate->interp->eval_frame = &_PyEval_EvalFrameDefault;
}
#endif
}
static const char* get_frame_name(THP_EVAL_API_FRAME_OBJECT* frame) {
// Returns the C string name of the current frame.
DEBUG_CHECK(PyUnicode_Check(F_CODE(frame)->co_name));
return PyUnicode_AsUTF8(F_CODE(frame)->co_name);
}
// Remember to update the type signature for DynamoCallbackFn.__call__ in
// torch/_dynamo/types.py if this function's signature changes.
static PyObject* dynamo_call_callback(
PyObject* callable,
THP_EVAL_API_FRAME_OBJECT* _frame,
PyObject* locals,
CacheEntry* cache_entry,
FrameState* frame_state) {
THPPyInterpreterFrame* frame = THPPyInterpreterFrame_New(_frame);
if (frame == NULL) {
return NULL;
}
frame->locals = locals;
PyObject* cache_entry_pyobj = CacheEntry_to_obj(cache_entry);
PyObject* res = PyObject_CallFunction(
callable,
"OOO",
frame,
cache_entry_pyobj,
frame_state);
Py_DECREF(frame);
Py_DECREF(cache_entry_pyobj);
return res;
}
static void clear_old_frame_if_python_312_plus(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame) {
#if IS_PYTHON_3_12_PLUS
THP_PyFrame_Clear(frame);
THP_PyThreadState_PopFrame(tstate, frame);
#endif
}
static PyObject* dynamo_eval_custom_code_impl(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
PyCodeObject* code,
int throw_flag) {
DEBUG_NULL_CHECK(tstate);
DEBUG_NULL_CHECK(frame);
DEBUG_NULL_CHECK(code);
#if IS_PYTHON_3_11_PLUS
// Generate Python function object and _PyInterpreterFrame in a way similar to
// https://github.com/python/cpython/blob/e715da6db1d1d70cd779dc48e1ba8110c51cc1bf/Python/ceval.c#L1130
#if IS_PYTHON_3_12_PLUS
PyFunctionObject* old_func = (PyFunctionObject*) frame->f_funcobj;
size_t size = code->co_framesize;
#else
PyFunctionObject* old_func = frame->f_func;
size_t size = code->co_nlocalsplus + code->co_stacksize + FRAME_SPECIALS_SIZE;
#endif
PyFunctionObject* func = _PyFunction_CopyWithNewCode(old_func, code);
if (func == NULL) {
return NULL;
}
THP_EVAL_API_FRAME_OBJECT* shadow = THP_PyThreadState_BumpFramePointerSlow(tstate, size);
if (shadow == NULL) {
Py_DECREF(func);
return NULL;
}
Py_INCREF(func);
// consumes reference to func
#if IS_PYTHON_3_12_PLUS
_PyFrame_Initialize(shadow, func, NULL, code, 0);
#else
_PyFrame_InitializeSpecials(shadow, func, NULL, code->co_nlocalsplus);
#endif
PyObject** fastlocals_old = frame->localsplus;
PyObject** fastlocals_new = shadow->localsplus;
Py_ssize_t n_old = F_CODE(frame)->co_nlocalsplus;
Py_ssize_t n_new = code->co_nlocalsplus;
// localsplus are XINCREF'd by default eval frame, so all values must be valid.
#if !(IS_PYTHON_3_12_PLUS)
// _PyFrame_Initialize in 3.12 already does this
for (int i = 0; i < code->co_nlocalsplus; i++) {
fastlocals_new[i] = NULL;
}
#endif
#else
THP_EVAL_API_FRAME_OBJECT* shadow = PyFrame_New(tstate, code, frame->f_globals, NULL);
if (shadow == NULL) {
return NULL;
}
PyObject** fastlocals_old = frame->f_localsplus;
PyObject** fastlocals_new = shadow->f_localsplus;
Py_ssize_t n_old = F_CODE(frame)->co_nlocals + PyCode_GetNFreevars(F_CODE(frame)) + PyCode_GetNCellvars(F_CODE(frame));
Py_ssize_t n_new = code->co_nlocals + PyCode_GetNFreevars(code) + PyCode_GetNCellvars(code);
#endif
// ============== Initialize new frame from old frame ============
// Python internal for executing a function:
// 1. CPython interpreter first creates an empty frame according to the code object
// 2. CPython interpreter initializes the frame by filling arguments/free variables into frame and initializing cell variables
// 3. CPython interpreter executes the code object
//
// 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.
// The main task is to copy data in old frame to new frame, concerning a storage space named `localsplus`.
//
// localsplus storage is an array with the following layout:
// | args | new_locals | cell_variables | free_variables |
// | <--- from left to right, index from 0 to n - 1 ---> |
// code.co_varnames == args + new_locals, code.co_nlocals == len(code.co_varnames)
// code.co_freevars == free_variables
// In Python 3.10 and lower, `n == code.co_nlocals + len(code.co_cellvars) + len(code.co_freevars)` (Python expression)
// 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.
// The complexity happens if an argument becomes a cell variable:
// In Python 3.10 and lower, `code.co_cellvars == cell_variables`, and the corresponding slot in args becomes `NULL`.
// 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` .
//
// ideally, we need to look up new localsplus from old localsplus by name:
// for i, name, value in enumerate(localsplusnames_old):
// if value != NULL: (NULL happens for new local variables and arguments that becomes cell variables)
// name_to_idx[name] = i
// for i, name in enumerate(localsplusnames_new):
// if name in name_to_idx:
// fastlocals_new[i] = fastlocals_old[name_to_idx[name]]
//
// The above process of building a `name_to_idx` mapping is expensive.
// Dynamo makes the following assumptions:
// 1. new code has the same arguments as the old code (both the number and the order)
// 2. new code has the same cell variables as the old code (both the number and the order)
// 3. new code has the same free variables as the old code (both the number and the order)
// The only flexibility lies in new local variables: new code can introduce their own variables.
// With these assumptions, Dynamo can copy data directly by index. Dynamo just needs to take care of copying cell variables correctly.
// To avoid runtime cost, the assumptions are checked when we first generate the code object in pytorch/torch/_dynamo/convert_frame.py .
// 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 = dynamo_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
static PyObject* dynamo_eval_custom_code(
PyThreadState* tstate,
THP_EVAL_API_FRAME_OBJECT* frame,
PyCodeObject* code,
const char* trace_annotation,
int throw_flag) {
_PytorchRecordFunctionState* rf = _pytorch_record_function_enter(trace_annotation);
PyObject* result = dynamo_eval_custom_code_impl(
tstate,
frame,
code,
throw_flag
);
_pytorch_record_function_exit(rf);
return result;
}
static PyObject* dynamo__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 dynamo_eval_frame_default(tstate, frame, throw_flag);
}
int should_clear_frame = 0;
PyObject* result = dynamo__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;
}
static PyObject* skip_code_recursive_flag;
static PyObject* cache_limit_hit_flag;
bool is_skip_guard_eval_unsafe = false;
// 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.
// Generally should_clear_frame should be set if and only we don't eval_frame_default.
static PyObject* dynamo__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 dynamo_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 dynamo_eval_frame_default(tstate, frame, throw_flag);
}
if (extra == SKIP_CODE_RECURSIVE) {
DEBUG_TRACE("skip recursive %s", get_frame_name(frame));
eval_frame_callback_set(Py_None);
PyObject* result = dynamo_eval_frame_default(tstate, frame, throw_flag);
eval_frame_callback_set(callback);
return result;
}
if (extra == NULL) {
extra = init_and_set_extra_state(F_CODE(frame));
}
PyObject *locals = get_framelocals_mapping(frame);
PyObject* backend = get_backend(callback);
// 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);
// A callback of Py_False indicates "run only" mode, the cache is checked, but
// we never compile.
// Also, if extra is marked as "cache_limit_hit", run in "run only" mode
// and skip code recursively if no cache entry is found.
if (callback == Py_False || extra_state_cache_limit_hit(extra)) {
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 = NULL;
const char* trace_annotation = "";
lookup(extra, locals, backend, &maybe_cached_code, &trace_annotation, is_skip_guard_eval_unsafe);
_pytorch_record_function_exit(rf);
Py_DECREF(locals);
if (maybe_cached_code == NULL) {
// guard eval failed, keep propagating
*should_clear_frame = 1;
return NULL;
} else if (maybe_cached_code == Py_None) {
if (is_skip_guard_eval_unsafe) {
PyErr_SetString(
PyExc_RuntimeError,
"Recompilation triggered with skip_guard_eval_unsafe stance. "
"This usually means that you have not warmed up your model "
"with enough inputs such that you can guarantee no more recompilations."
);
return NULL;
}
DEBUG_TRACE("cache miss %s", get_frame_name(frame));
if (extra_state_cache_limit_hit(extra)) {
// skip code recursively
DEBUG_TRACE("skip recursive %s", get_frame_name(frame));
eval_frame_callback_set(Py_None);
}
PyObject *ret = dynamo_eval_frame_default(tstate, frame, throw_flag);
if (extra_state_cache_limit_hit(extra)) {
eval_frame_callback_set(callback);
}
return ret;
}
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 dynamo_eval_custom_code(tstate, frame, cached_code, trace_annotation, throw_flag);
}
DEBUG_CHECK(PyDict_CheckExact(locals));
DEBUG_CHECK(PyDict_CheckExact(frame->f_globals));
DEBUG_CHECK(PyDict_CheckExact(frame->f_builtins));
_PytorchRecordFunctionState* rf = _pytorch_record_function_enter(cache_lookup_profiler_str);
PyObject* maybe_cached_code = NULL;
const char* trace_annotation = "";
lookup(extra, locals, backend, &maybe_cached_code, &trace_annotation, is_skip_guard_eval_unsafe);
_pytorch_record_function_exit(rf);
if (maybe_cached_code == NULL) {
// Python error
*should_clear_frame = 1;
Py_DECREF(locals);
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;
Py_DECREF(locals);
return dynamo_eval_custom_code(tstate, frame, cached_code, trace_annotation, throw_flag);
}
if (is_skip_guard_eval_unsafe) {
PyErr_SetString(
PyExc_RuntimeError,
"Recompilation triggered with skip_guard_eval_unsafe stance. "
"This usually means that you have not warmed up your model "
"with enough inputs such that you can guarantee no more recompilations."
);
return NULL;
}
// cache miss
CacheEntry* cache_entry = extract_cache_entry(extra);
FrameState* frame_state = extract_frame_state(extra);
PyObject* result =
dynamo_call_callback(callback, frame, locals, cache_entry, frame_state);
Py_DECREF(locals);
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 == skip_code_recursive_flag) {
// Dynamo returned skip_code_recursive_flag, so we should recursively skip code.
DEBUG_TRACE("create skip recursive %s", get_frame_name(frame));
set_extra_state(F_CODE(frame), SKIP_CODE_RECURSIVE);
PyObject* r = dynamo_eval_frame_default(tstate, frame, throw_flag);
// Re-enable custom behavior
eval_frame_callback_set(callback);
return r;
} else if (result == cache_limit_hit_flag) {
// Dynamo returned cache_limit_hit_flag, so we should recursively skip code.
DEBUG_TRACE("create cache limit hit %s", get_frame_name(frame));
set_extra_state_cache_limit_hit(extra, true);
PyObject* r = dynamo_eval_frame_default(tstate, frame, throw_flag);
// Re-enable custom behavior
eval_frame_callback_set(callback);
return r;
} 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 dynamo_eval_custom_code(tstate, frame, CacheEntry_get_code(new_cache_entry),
CacheEntry_get_trace_annotation(new_cache_entry), throw_flag);
} 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 dynamo_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;
static void enable_eval_frame_shim(PyThreadState* tstate) {}
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 // !(IS_PYTHON_3_14_PLUS)
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* set_skip_guard_eval_unsafe(PyObject* dummy, PyObject* skip_guard_unsafe_flag) {
if (skip_guard_unsafe_flag != Py_False && skip_guard_unsafe_flag != Py_True) {
DEBUG_TRACE0("arg error");
PyErr_SetString(PyExc_TypeError, "expected True/False");
return NULL;
}
bool old_skip_guard_eval_unsafe = is_skip_guard_eval_unsafe;
is_skip_guard_eval_unsafe = skip_guard_unsafe_flag == Py_True;
if (old_skip_guard_eval_unsafe) {
Py_RETURN_TRUE;
}
Py_RETURN_FALSE;
}
static PyObject* get_eval_frame_callback_py(PyObject* dummy, PyObject* args) {
return eval_frame_callback_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;
}
// Debugging function for GNU C only.
// Used to set gdb breakpoints in hot CPython sites from Python.
// Code example:
//
// def foo(x):
// x = x + 1
// torch._dynamo.eval_frame.raise_sigtrap()
// # (gdb) b bytecodes.c:1234 (whatever line CALL is handled)
// x = torch.sin(x) # gdb breakpoint hit when sin is called
//
// In this example, we want to breakpoint on CALL in bytecodes.c only when
// running foo. Otherwise, we would need to breakpoint before running the program,
// and that breakpoint would be hit every time Python makes a function call,
// leading to a spammy debugging experience.
static PyObject* raise_sigtrap(PyObject* dummy, PyObject* obj) {
#ifdef __GNUC__
raise(SIGTRAP);
#endif
Py_RETURN_NONE;
}
static PyMethodDef _methods[] = {
{"set_eval_frame", set_eval_frame_py, METH_O, NULL},
{"set_skip_guard_eval_unsafe", set_skip_guard_eval_unsafe, METH_O, NULL},
{"get_eval_frame_callback", get_eval_frame_callback_py, METH_NOARGS, 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},
{"raise_sigtrap", raise_sigtrap, METH_NOARGS, 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;
}
#ifdef Py_GIL_DISABLED
PyUnstable_Module_SetGIL(module, Py_MOD_GIL_NOT_USED);
#endif
if (PyType_Ready(&THPPyInterpreterFrameType) < 0) {
return NULL;
}
Py_INCREF(&THPPyInterpreterFrameType);
if (PyModule_AddObject(module, "_PyInterpreterFrame", (PyObject*)&THPPyInterpreterFrameType) != 0) {
return NULL;
}
skip_code_recursive_flag = PyObject_New(PyObject, &PyBaseObject_Type);
if (skip_code_recursive_flag == NULL) {
return NULL;
}
if (PyModule_AddObject(module, "skip_code_recursive_flag", skip_code_recursive_flag) != 0) {
return NULL;
}
cache_limit_hit_flag = PyObject_New(PyObject, &PyBaseObject_Type);
if (cache_limit_hit_flag == NULL) {
return NULL;
}
if (PyModule_AddObject(module, "cache_limit_hit_flag", cache_limit_hit_flag) != 0) {
return NULL;
}
return module;
}
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