Compare commits

...

1 Commits

Author SHA1 Message Date
73c49ee963 Speed up fx graph iteration by implementing it in C++
ghstack-source-id: af7493f6f73baf00e30a6d5790a601729bd9c900
Pull Request resolved: https://github.com/pytorch/pytorch/pull/128288
2024-06-08 17:12:47 -07:00
7 changed files with 277 additions and 18 deletions

View File

@ -827,6 +827,7 @@ libtorch_python_core_sources = [
"torch/csrc/dynamo/guards.cpp",
"torch/csrc/dynamo/init.cpp",
"torch/csrc/functorch/init.cpp",
"torch/csrc/fx/node.cpp",
"torch/csrc/mps/Module.cpp",
"torch/csrc/mtia/Module.cpp",
"torch/csrc/inductor/aoti_runner/pybind.cpp",

View File

@ -2331,3 +2331,14 @@ def _save_pickle(obj: Any) -> bytes: ...
# Defined in torch/csrc/jit/runtime/static/init.cpp
def _jit_to_static_module(graph_or_module: Union[Graph,ScriptModule]) -> Any: ...
def _fuse_to_static_module(graph_or_module: Union[Graph,ScriptModule], min_size: _int) -> Any: ...
# Defined in torch/csrc/fx/node.cpp
class _NodeBase:
_erased
_prev: "_NodeBase"
_next: "_NodeBase"
class _NodeIter:
def __init__(self, root, reversed) -> None: ...
def __iter__(self): ...
def __next__(self) -> _NodeBase: ...

View File

@ -67,6 +67,7 @@
#include <torch/csrc/cpu/Module.h>
#include <torch/csrc/dynamo/init.h>
#include <torch/csrc/functorch/init.h>
#include <torch/csrc/fx/node.h>
#include <torch/csrc/inductor/aoti_runner/pybind.h>
#include <torch/csrc/jit/python/init.h>
#include <torch/csrc/jit/python/python_ir.h>
@ -1602,6 +1603,8 @@ PyObject* initModule() {
THPDevice_init(module);
THPStream_init(module);
THPEvent_init(module);
NodeBase_init(module);
NodeIter_init(module);
ASSERT_TRUE(THPVariable_initModule(module));
ASSERT_TRUE(THPFunction_initModule(module));
ASSERT_TRUE(THPEngine_initModule(module));

241
torch/csrc/fx/node.cpp Normal file
View File

@ -0,0 +1,241 @@
#include <torch/csrc/fx/node.h>
#include <structmember.h>
////////////////////////////////
// NodeBase
///////////////////////////////
struct NodeBase {
PyObject_HEAD bool _erased;
NodeBase* _prev;
NodeBase* _next;
};
static PyObject* NodeBase_new(
PyTypeObject* type,
PyObject* args,
PyObject* kwds) {
PyObject* self = type->tp_alloc(type, 0);
if (!self)
return nullptr;
return self;
}
static int NodeBase_init_fn(NodeBase* self, PyObject* args, PyObject* kwds) {
self->_erased = false;
Py_INCREF(self);
self->_prev = self;
Py_INCREF(self);
self->_next = self;
return 0;
}
static void NodeBase_dealloc(NodeBase* self) {
Py_XDECREF(self->_prev);
Py_XDECREF(self->_next);
Py_TYPE(self)->tp_free((PyObject*)self);
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
static struct PyMemberDef NodeBase_members[] = {
{"_erased", T_BOOL, offsetof(NodeBase, _erased), 0, nullptr},
{"_prev", T_OBJECT, offsetof(NodeBase, _prev), 0, nullptr},
{"_next", T_OBJECT, offsetof(NodeBase, _next), 0, nullptr},
{nullptr} /* Sentinel */
};
static PyTypeObject NodeBaseType = {
PyVarObject_HEAD_INIT(nullptr, 0) "torch._C._NodeBase", /* tp_name */
sizeof(NodeBase), /* tp_basicsize */
0, /* tp_itemsize */
(destructor)NodeBase_dealloc, /* tp_dealloc */
0, /* tp_vectorcall_offset */
nullptr, /* tp_getattr */
nullptr, /* tp_setattr */
nullptr, /* tp_reserved */
nullptr, /* tp_repr */
nullptr, /* tp_as_number */
nullptr, /* tp_as_sequence */
nullptr, /* tp_as_mapping */
nullptr, /* tp_hash */
nullptr, /* tp_call */
nullptr, /* tp_str */
nullptr, /* tp_getattro */
nullptr, /* tp_setattro */
nullptr, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /* tp_flags */
nullptr, /* tp_doc */
nullptr, /* tp_traverse */
nullptr, /* tp_clear */
nullptr, /* tp_richcompare */
0, /* tp_weaklistoffset */
nullptr, /* tp_iter */
nullptr, /* tp_iternext */
nullptr, /* tp_methods */
NodeBase_members, /* tp_members */
nullptr, /* tp_getset */
nullptr, /* tp_base */
nullptr, /* tp_dict */
nullptr, /* tp_descr_get */
nullptr, /* tp_descr_set */
0, /* tp_dictoffset */
(initproc)NodeBase_init_fn, /* tp_init */
nullptr, /* tp_alloc */
NodeBase_new, /* tp_new */
};
bool NodeBase_init(PyObject* module) {
if (PyType_Ready(&NodeBaseType) < 0) {
return false;
}
Py_INCREF(&NodeBaseType);
if (PyModule_AddObject(module, "_NodeBase", (PyObject*)&NodeBaseType) != 0) {
return false;
}
return true;
}
////////////////////////////////
// NodeIter
////////////////////////////////
struct NodeIter {
PyObject_HEAD bool _reversed;
NodeBase* _root;
NodeBase* _cur;
};
static PyObject* NodeIter_new(
PyTypeObject* type,
PyObject* args,
PyObject* kwds) {
PyObject* self = type->tp_alloc(type, 0);
if (!self)
return nullptr;
return self;
}
static int NodeIter_init_fn(NodeIter* self, PyObject* args, PyObject* kwargs) {
NodeBase* root = nullptr;
bool reversed = false;
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
constexpr const char* keywords[] = {"root", "reversed", nullptr};
if (!PyArg_ParseTupleAndKeywords(
args,
kwargs,
"Ob|",
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
const_cast<char**>(keywords),
&root,
&reversed)) {
return -1;
}
self->_reversed = reversed;
Py_INCREF(root);
self->_root = root;
Py_INCREF(root);
self->_cur = root;
return 0;
}
static void NodeIter_dealloc(NodeIter* self) {
Py_XDECREF(self->_root);
Py_XDECREF(self->_cur);
Py_TYPE(self)->tp_free((PyObject*)self);
}
PyObject* NodeIter_iter(PyObject* self) {
Py_INCREF(self);
return self;
}
template <bool reversed>
PyObject* NodeIter_iternext_helper(NodeIter* self) {
if constexpr (reversed) {
Py_INCREF(self->_cur->_prev);
Py_XDECREF(self->_cur);
self->_cur = self->_cur->_prev;
} else {
Py_INCREF(self->_cur->_next);
Py_XDECREF(self->_cur);
self->_cur = self->_cur->_next;
}
while (self->_cur != self->_root) {
if (!self->_cur->_erased) {
Py_INCREF(self->_cur);
return (PyObject*)self->_cur;
}
if constexpr (reversed) {
Py_INCREF(self->_cur->_prev);
Py_XDECREF(self->_cur);
self->_cur = self->_cur->_prev;
} else {
Py_INCREF(self->_cur->_next);
Py_XDECREF(self->_cur);
self->_cur = self->_cur->_next;
}
}
PyErr_SetNone(PyExc_StopIteration);
return nullptr;
}
PyObject* NodeIter_iternext(PyObject* _self) {
NodeIter* self = (NodeIter*)_self;
if (self->_reversed) {
return NodeIter_iternext_helper<true>(self);
} else {
return NodeIter_iternext_helper<false>(self);
}
}
static PyTypeObject NodeIterType = {
PyVarObject_HEAD_INIT(nullptr, 0) "torch._C._NodeIter", /* tp_name */
sizeof(NodeIter), /* tp_basicsize */
0, /* tp_itemsize */
(destructor)NodeIter_dealloc, /* tp_dealloc */
0, /* tp_vectorcall_offset */
nullptr, /* tp_getattr */
nullptr, /* tp_setattr */
nullptr, /* tp_reserved */
nullptr, /* tp_repr */
nullptr, /* tp_as_number */
nullptr, /* tp_as_sequence */
nullptr, /* tp_as_mapping */
nullptr, /* tp_hash */
nullptr, /* tp_call */
nullptr, /* tp_str */
nullptr, /* tp_getattro */
nullptr, /* tp_setattro */
nullptr, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT, /* tp_flags */
nullptr, /* tp_doc */
nullptr, /* tp_traverse */
nullptr, /* tp_clear */
nullptr, /* tp_richcompare */
0, /* tp_weaklistoffset */
NodeIter_iter, /* tp_iter */
NodeIter_iternext, /* tp_iternext */
nullptr, /* tp_methods */
nullptr, /* tp_members */
nullptr, /* tp_getset */
nullptr, /* tp_base */
nullptr, /* tp_dict */
nullptr, /* tp_descr_get */
nullptr, /* tp_descr_set */
0, /* tp_dictoffset */
(initproc)NodeIter_init_fn, /* tp_init */
nullptr, /* tp_alloc */
NodeIter_new, /* tp_new */
};
bool NodeIter_init(PyObject* module) {
if (PyType_Ready(&NodeIterType) < 0) {
return false;
}
Py_INCREF(&NodeIterType);
if (PyModule_AddObject(module, "_NodeIter", (PyObject*)&NodeIterType) != 0) {
return false;
}
return true;
}

6
torch/csrc/fx/node.h Normal file
View File

@ -0,0 +1,6 @@
#pragma once
#include <torch/csrc/python_headers.h>
bool NodeBase_init(PyObject* module);
bool NodeIter_init(PyObject* module);

View File

@ -3,6 +3,7 @@ from .node import Node, Argument, Target, map_arg, _type_repr, _get_qualified_na
import torch.utils._pytree as pytree
from . import _pytree as fx_pytree
from ._compatibility import compatibility
from torch._C import _NodeIter
import os
import contextlib
@ -270,20 +271,7 @@ class _node_list:
return self.graph._len
def __iter__(self):
root = self.graph._root
if self.direction == "_next":
cur = root._next
while cur is not root:
if not cur._erased:
yield cur
cur = cur._next
else:
assert self.direction == "_prev"
cur = root._prev
while cur is not root:
if not cur._erased:
yield cur
cur = cur._prev
yield from _NodeIter(self.graph._root, self.direction == "_prev")
def __reversed__(self):
return _node_list(self.graph, '_next' if self.direction == '_prev' else '_prev')

View File

@ -11,6 +11,7 @@ import inspect
import warnings
from torch.fx.operator_schemas import normalize_function, normalize_module, ArgsKwargsPair
from .._ops import ops as _ops
from torch._C import _NodeBase
if TYPE_CHECKING:
from .graph import Graph
@ -139,7 +140,7 @@ def _format_arg(arg, max_list_len=float('inf')) -> str:
return str(arg)
@compatibility(is_backward_compatible=True)
class Node:
class Node(_NodeBase):
"""
``Node`` is the data structure that represents individual operations within
a ``Graph``. For the most part, Nodes represent callsites to various entities,
@ -197,6 +198,7 @@ class Node:
annotation of values in the generated code or for other types
of analyses.
"""
super().__init__()
self.graph = graph
self.name = name # unique name of value being created
assert op in ['placeholder', 'call_method', 'call_module', 'call_function', 'get_attr', 'output', 'root']
@ -235,9 +237,6 @@ class Node:
# does not produce a value, it's more of a notation. Thus, this value
# describes the type of args[0] in the ``return`` node.
self.type : Optional[Any] = return_type
self._prev = self
self._next = self
self._erased = False
self._sort_key: Any = ()
# If set, use this fn to print this node
@ -247,6 +246,16 @@ class Node:
# transformations. This metadata is preserved across node copies
self.meta : Dict[str, Any] = {}
def __getstate__(self):
return self.__dict__, self._erased, self._prev, self._next
def __setstate__(self, state):
d, erased, prev, next = state
self.__dict__.update(d)
self._erased = erased
self._prev = prev
self._next = next
@property
def next(self) -> 'Node':
"""