pytorch/torch/cpu/__init__.py
Nikita Shulga e56dcf2772 [CPUInductor] Fix SVE256 detection (#146207)
This PR removes `torch.cpu._is_arm_sve_supported()` and replaces is with stable `torch.backends.cpu.get_cpu_capability()`

I should have reviewed https://github.com/pytorch/pytorch/pull/134672 more thoroughly, because it introduced duplicate, but slightly different API for detecting CPU architectures, which resulted in runtime crashes on system that do support SVE128, rather than SVE256

Fixes https://github.com/pytorch/pytorch/issues/145441

Pull Request resolved: https://github.com/pytorch/pytorch/pull/146207
Approved by: https://github.com/angelayi
2025-02-01 18:51:34 +00:00

189 lines
4.4 KiB
Python

# mypy: allow-untyped-defs
r"""
This package implements abstractions found in ``torch.cuda``
to facilitate writing device-agnostic code.
"""
from contextlib import AbstractContextManager
from typing import Any, Optional, Union
import torch
from .. import device as _device
from . import amp
__all__ = [
"is_available",
"synchronize",
"current_device",
"current_stream",
"stream",
"set_device",
"device_count",
"Stream",
"StreamContext",
"Event",
]
_device_t = Union[_device, str, int, None]
def _is_avx2_supported() -> bool:
r"""Returns a bool indicating if CPU supports AVX2."""
return torch._C._cpu._is_avx2_supported()
def _is_avx512_supported() -> bool:
r"""Returns a bool indicating if CPU supports AVX512."""
return torch._C._cpu._is_avx512_supported()
def _is_avx512_bf16_supported() -> bool:
r"""Returns a bool indicating if CPU supports AVX512_BF16."""
return torch._C._cpu._is_avx512_bf16_supported()
def _is_vnni_supported() -> bool:
r"""Returns a bool indicating if CPU supports VNNI."""
# Note: Currently, it only checks avx512_vnni, will add the support of avx2_vnni later.
return torch._C._cpu._is_avx512_vnni_supported()
def _is_amx_tile_supported() -> bool:
r"""Returns a bool indicating if CPU supports AMX_TILE."""
return torch._C._cpu._is_amx_tile_supported()
def _is_amx_fp16_supported() -> bool:
r"""Returns a bool indicating if CPU supports AMX FP16."""
return torch._C._cpu._is_amx_fp16_supported()
def _init_amx() -> bool:
r"""Initializes AMX instructions."""
return torch._C._cpu._init_amx()
def is_available() -> bool:
r"""Returns a bool indicating if CPU is currently available.
N.B. This function only exists to facilitate device-agnostic code
"""
return True
def synchronize(device: _device_t = None) -> None:
r"""Waits for all kernels in all streams on the CPU device to complete.
Args:
device (torch.device or int, optional): ignored, there's only one CPU device.
N.B. This function only exists to facilitate device-agnostic code.
"""
class Stream:
"""
N.B. This class only exists to facilitate device-agnostic code
"""
def __init__(self, priority: int = -1) -> None:
pass
def wait_stream(self, stream) -> None:
pass
class Event:
def query(self) -> bool:
return True
def record(self, stream=None) -> None:
pass
def synchronize(self) -> None:
pass
def wait(self, stream=None) -> None:
pass
_default_cpu_stream = Stream()
_current_stream = _default_cpu_stream
def current_stream(device: _device_t = None) -> Stream:
r"""Returns the currently selected :class:`Stream` for a given device.
Args:
device (torch.device or int, optional): Ignored.
N.B. This function only exists to facilitate device-agnostic code
"""
return _current_stream
class StreamContext(AbstractContextManager):
r"""Context-manager that selects a given stream.
N.B. This class only exists to facilitate device-agnostic code
"""
cur_stream: Optional[Stream]
def __init__(self, stream):
self.stream = stream
self.prev_stream = _default_cpu_stream
def __enter__(self):
cur_stream = self.stream
if cur_stream is None:
return
global _current_stream
self.prev_stream = _current_stream
_current_stream = cur_stream
def __exit__(self, type: Any, value: Any, traceback: Any) -> None:
cur_stream = self.stream
if cur_stream is None:
return
global _current_stream
_current_stream = self.prev_stream
def stream(stream: Stream) -> AbstractContextManager:
r"""Wrapper around the Context-manager StreamContext that
selects a given stream.
N.B. This function only exists to facilitate device-agnostic code
"""
return StreamContext(stream)
def device_count() -> int:
r"""Returns number of CPU devices (not cores). Always 1.
N.B. This function only exists to facilitate device-agnostic code
"""
return 1
def set_device(device: _device_t) -> None:
r"""Sets the current device, in CPU we do nothing.
N.B. This function only exists to facilitate device-agnostic code
"""
def current_device() -> str:
r"""Returns current device for cpu. Always 'cpu'.
N.B. This function only exists to facilitate device-agnostic code
"""
return "cpu"