mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
38c4d05535
In a precompiled bytecode, it looks like the following:
```
pre-graph bytecode
...
compiled graph code
...
post-graph bytecode
```
In pre-graph bytecode we have calls into helper functions like torch._dynamo.utils.call_size which will invoke @disable inside the bytecode.
Normally torch.compile() will handle these frames fine, but for precompile we will load bytecode from a clean state of dynamo and we want a way to assert recompile never happen, so the current way to ensure this is by doing set_stance("fail_on_recompile") (open to any other idea to test this, but IMO this is the closest thing we have today).
This approach doesn't work when util functions like call_size() is involved and this PR fixes a bunch of places to make sure "fail_on_recompile" can skip through the functions meant to be skipped during compilation.
Differential Revision: [D76156867](https://our.internmc.facebook.com/intern/diff/D76156867/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/155363
Approved by: https://github.com/jamesjwu, https://github.com/jansel
ghstack dependencies: #155329
60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
"""
|
|
APIs related to torch.compile which lazily import torch._dynamo to avoid
|
|
circular dependencies.
|
|
"""
|
|
|
|
import functools
|
|
from typing import Callable, Literal, Optional, overload, TypeVar, Union
|
|
from typing_extensions import ParamSpec
|
|
|
|
|
|
_T = TypeVar("_T")
|
|
_P = ParamSpec("_P")
|
|
|
|
|
|
@overload
|
|
def _disable_dynamo(
|
|
fn: Callable[_P, _T], recursive: bool = True
|
|
) -> Callable[_P, _T]: ...
|
|
|
|
|
|
@overload
|
|
def _disable_dynamo(
|
|
fn: Literal[None] = None, recursive: bool = True
|
|
) -> Callable[[Callable[_P, _T]], Callable[_P, _T]]: ...
|
|
|
|
|
|
def _disable_dynamo(
|
|
fn: Optional[Callable[_P, _T]] = None, recursive: bool = True
|
|
) -> Union[Callable[_P, _T], Callable[[Callable[_P, _T]], Callable[_P, _T]]]:
|
|
"""
|
|
This API should be only used inside torch, external users should still use
|
|
torch._dynamo.disable. The main goal of this API is to avoid circular
|
|
imports issues that is common while using _dynamo.disable inside torch
|
|
itself.
|
|
|
|
This API avoids it by lazily importing torch._dynamo from the import time to
|
|
the invocation of the decorated function.
|
|
"""
|
|
if fn is not None:
|
|
|
|
@functools.wraps(fn)
|
|
def inner(*args: _P.args, **kwargs: _P.kwargs) -> _T:
|
|
# cache this on the first invocation to avoid adding too much overhead.
|
|
disable_fn = getattr(fn, "__dynamo_disable", None)
|
|
if disable_fn is None:
|
|
import torch._dynamo
|
|
|
|
# We can safely turn off functools.wraps here because the inner
|
|
# already wraps fn in the outer scope.
|
|
disable_fn = torch._dynamo.disable(fn, recursive, wrapping=False)
|
|
fn.__dynamo_disable = disable_fn # type: ignore[attr-defined]
|
|
|
|
return disable_fn(*args, **kwargs)
|
|
|
|
return inner
|
|
else:
|
|
# decorator usage like @_disable_dynamo(recursive=False). The resulting
|
|
# object expects the original decorated function as the arg.
|
|
return functools.partial(_disable_dynamo, recursive=recursive)
|