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