def __init__(self,
kernel_size: int,
stride: int = None,
signed: bool = True,
min_overall_bit_width: Optional[int] = 2,
max_overall_bit_width: Optional[int] = 32,
quant_type: QuantType = QuantType.FP,
lsb_trunc_bit_width_impl_type=BitWidthImplType.CONST):
QuantLayer.__init__(self,
compute_output_scale=True,
compute_output_bit_width=True,
return_quant_tensor=True)
AvgPool2d.__init__(self, kernel_size=kernel_size, stride=stride)
ls_bit_width_to_trunc = math.ceil(math.log2(kernel_size * kernel_size))
self.signed = signed
self.quant_type = quant_type
explicit_rescaling = True # we are explicitly rescaling as we are replacing the div in avg with trunc
self.accumulator_quant = TruncQuantProxy(
signed=signed,
quant_type=quant_type,
trunc_at_least_init_val=True,
ls_bit_width_to_trunc=ls_bit_width_to_trunc,
min_overall_bit_width=min_overall_bit_width,
max_overall_bit_width=max_overall_bit_width,
lsb_trunc_bit_width_impl_type=lsb_trunc_bit_width_impl_type,
explicit_rescaling=explicit_rescaling,
override_pretrained_bit_width=False)
def __init__(self,
kernel_size: Union[int, Tuple[int, int]],
stride: Union[int, Tuple[int, int]] = None,
trunc_quant: Optional[AccQuantType] = TruncTo8bit,
return_quant_tensor: bool = True,
**kwargs):
AvgPool2d.__init__(self, kernel_size=kernel_size, stride=stride)
QuantLayerMixin.__init__(self, return_quant_tensor)
QuantTruncMixin.__init__(self, trunc_quant=trunc_quant, **kwargs)
def __init__(self,
kernel_size: Union[int, Tuple[int, int]],
stride: Union[int, Tuple[int, int]] = None,
trunc_quant: Union[AccQuantProxyProtocol,
Type[Injector]] = TruncTo8bit,
return_quant_tensor: bool = True,
update_injector: Callable = update_trunc_quant_injector,
**kwargs):
AvgPool2d.__init__(self, kernel_size=kernel_size, stride=stride)
QuantLayerMixin.__init__(self, return_quant_tensor)
QuantTruncMixin.__init__(self,
trunc_quant=trunc_quant,
update_injector=update_injector,
**kwargs)
def __init__(self,
kernel_size: int,
stride: int = None,
trunc_quant: Union[AccQuantProxyProtocol,
Type[Injector]] = DefaultTruncQI,
return_quant_tensor: bool = True,
update_injector: Callable = update_trunc_quant_injector,
**kwargs):
AvgPool2d.__init__(self, kernel_size=kernel_size, stride=stride)
QuantLayerMixin.__init__(self, return_quant_tensor)
QuantTruncMixin.__init__(self,
trunc_quant=trunc_quant,
update_injector=update_injector,
ls_bit_width_to_trunc=math.ceil(
math.log2(kernel_size * kernel_size)),
**kwargs)
