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https://github.com/zebrajr/pytorch.git
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as titled, this PR improves the device selection logic when user did not set the device before calling the DeviceMesh constructor, as a device manager, DeviceMesh should try to set the device for users in a good way. The behavior of set_device before: * If user call init_process_group to init a world process group, we assume user already called set_device and we don't set the device for the user * If user does not init a world process group by themselves, we init a world process group for the user and follow a heuristic to set the device. This is ok but sometimes the set_device heuristic wouldn't work well (i.e. if user use TORCH_CUDA_VISBILE_DEVICES So this PR improves the device selection logic to: * If the default cuda context is initialized by the time we init DeviceMesh, then we assume user must called some cuda operation before therefore must have selected the device by themselves * If not the above, then we check if envvars have "LOCAL_RANK" and "WORLD_SIZE" from the launcher (i.e. torchrun), if so, we use "LOCAL_RANK" to set the device for the current process, which is a very standard practice. (This solves the TORCH_CUDA_VISBILE_DEVICES issue) * If not above, then we throw warning to users about situation, and fallback to the old heuristic. Pull Request resolved: https://github.com/pytorch/pytorch/pull/150897 Approved by: https://github.com/tianyu-l ghstack dependencies: #150898
205 lines
4.7 KiB
Python
205 lines
4.7 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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"is_initialized",
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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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def record_event(self) -> None:
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pass
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def wait_event(self, event) -> 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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def is_initialized() -> bool:
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r"""Returns True if the CPU is initialized. Always True.
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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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