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72 lines
2.1 KiB
72 lines
2.1 KiB
#!/usr/bin/env python
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from collections import OrderedDict
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from typing import Union
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from .base_accelerator import BaseAccelerator
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from .cpu_accelerator import CpuAccelerator
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from .cuda_accelerator import CudaAccelerator
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from .npu_accelerator import NpuAccelerator
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__all__ = ["set_accelerator", "auto_set_accelerator", "get_accelerator"]
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_ACCELERATOR = None
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# we use ordered dictionary here to associate the
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# order with device check priority
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# i.e. auto_set_accelerator will check cuda first
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_ACCELERATOR_MAPPING = OrderedDict(cuda=CudaAccelerator, npu=NpuAccelerator, cpu=CpuAccelerator)
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def set_accelerator(accelerator: Union[str, BaseAccelerator]) -> None:
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"""
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Set the global accelerator for the current process.
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Args:
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accelerator (Union[str, BaseAccelerator]): the type of accelerator to which the current device belongs.
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"""
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global _ACCELERATOR
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if isinstance(accelerator, str):
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_ACCELERATOR = _ACCELERATOR_MAPPING[accelerator]()
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elif isinstance(accelerator, BaseAccelerator):
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_ACCELERATOR = accelerator
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else:
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raise TypeError("accelerator must be either a string or an instance of BaseAccelerator")
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def auto_set_accelerator() -> None:
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"""
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Automatically check if any accelerator is available.
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If an accelerator is available, set it as the global accelerator.
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"""
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global _ACCELERATOR
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for accelerator_name, accelerator_cls in _ACCELERATOR_MAPPING.items():
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try:
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accelerator = accelerator_cls()
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if accelerator_name == "cpu" or accelerator.is_available():
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_ACCELERATOR = accelerator
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break
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except:
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pass
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if _ACCELERATOR is None:
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raise RuntimeError("No accelerator is available.")
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def get_accelerator() -> BaseAccelerator:
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"""
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Return the accelerator for the current process. If the accelerator is not initialized, it will be initialized
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to the default accelerator type.
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Returns: the accelerator for the current process.
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"""
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global _ACCELERATOR
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if _ACCELERATOR is None:
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auto_set_accelerator()
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return _ACCELERATOR
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