QuantDepthwiseConv2d

Bases: QuantBase

Int8-quantized depthwise 2-D convolution with optional BatchNorm and ReLU.

Each input channel is convolved with its own [1, kH, kW] kernel (groups = channels). BN parameters are folded into the weight for schema export.

Parameters:

Name	Type	Description	Default
channels	int	Number of input / output channels.	required
kernel_size	int | tuple[int, int]	Kernel size.	required
stride	int | tuple[int, int]	Convolution stride.	1
padding	int | tuple[int, int] | tuple[int, int, int, int]	Zero-padding. int or 2-tuple (pad_h, pad_w) or 4-tuple (L, R, T, B).	0
bias	bool	Whether to include an additive bias.	True
device	str	Torch device for the underlying parameters.	'cpu'
act_func	str | None	Either "relu" or None.	None
ema_constant	float	EMA smoothing factor for observers.	0.01
bn	bool	If True, append a BatchNorm2d layer and fold it into weights for schema export.	False