Files
pytorch/torch/_compile.py
Aaron Orenstein 45ef3309e3 [BE] typing for decorators (#144161)
Summary:
Untyped decorators strip annotations from the decorated items.

- _compile
- _inductor/fx_passes/post_grad
- _inductor/lowering
- _library/custom_ops
- _meta_registrations
- _ops
- _refs/nn/functional
- ao/quantization/quantizer/xnnpack_quantizer_utils
- distributed/_composable/contract
- fx/experimental/graph_gradual_typechecker
- fx/experimental/migrate_gradual_types/constraint_generator
- optim/optimizer
- signal/windows/windows
- testing/_internal/common_device_type
- torch/_inductor/decomposition
- utils/flop_counter

Test Plan: unit tests

Differential Revision: D62302684

Pull Request resolved: https://github.com/pytorch/pytorch/pull/144161
Approved by: https://github.com/Skylion007, https://github.com/albanD
2025-01-04 16:40:09 +00:00

58 lines
1.8 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
disable_fn = torch._dynamo.disable(fn, recursive)
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)