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import sys
import torch
import types
from typing import List
# This function should correspond to the enums present in c10/core/QEngine.h
def _get_qengine_id(qengine: str) -> int:
if qengine == 'none' or qengine == '' or qengine is None:
ret = 0
elif qengine == 'fbgemm':
ret = 1
elif qengine == 'qnnpack':
ret = 2
elif qengine == 'onednn':
ret = 3
elif qengine == 'x86':
ret = 4
else:
ret = -1
raise RuntimeError("{} is not a valid value for quantized engine".format(qengine))
return ret
# This function should correspond to the enums present in c10/core/QEngine.h
def _get_qengine_str(qengine: int) -> str:
all_engines = {0 : 'none', 1 : 'fbgemm', 2 : 'qnnpack', 3 : 'onednn', 4 : 'x86'}
return all_engines.get(qengine, '*undefined')
class _QEngineProp(object):
def __get__(self, obj, objtype) -> str:
return _get_qengine_str(torch._C._get_qengine())
def __set__(self, obj, val: str) -> None:
torch._C._set_qengine(_get_qengine_id(val))
class _SupportedQEnginesProp(object):
def __get__(self, obj, objtype) -> List[str]:
qengines = torch._C._supported_qengines()
return [_get_qengine_str(qe) for qe in qengines]
def __set__(self, obj, val) -> None:
raise RuntimeError("Assignment not supported")
class QuantizedEngine(types.ModuleType):
def __init__(self, m, name):
super(QuantizedEngine, self).__init__(name)
self.m = m
def __getattr__(self, attr):
return self.m.__getattribute__(attr)
engine = _QEngineProp()
supported_engines = _SupportedQEnginesProp()
# This is the sys.modules replacement trick, see
# https://stackoverflow.com/questions/2447353/getattr-on-a-module/7668273#7668273
sys.modules[__name__] = QuantizedEngine(sys.modules[__name__], __name__)
engine: str
supported_engines: List[str]
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