mmagic.models.archs.separable_conv_module

Module Contents

Classes

DepthwiseSeparableConvModule

Depthwise separable convolution module.

class mmagic.models.archs.separable_conv_module.DepthwiseSeparableConvModule(in_channels: int, out_channels: int, kernel_size: Union[int, Tuple[int, int]], stride: Union[int, Tuple[int, int]] = 1, padding: Union[int, Tuple[int, int]] = 0, dilation: Union[int, Tuple[int, int]] = 1, norm_cfg: Optional[dict] = None, act_cfg: Optional[dict] = dict(type='ReLU'), dw_norm_cfg: Union[dict, str] = 'default', dw_act_cfg: Union[dict, str] = 'default', pw_norm_cfg: Union[dict, str] = 'default', pw_act_cfg: Union[dict, str] = 'default', **kwargs)

Bases: torch.nn.Module

Depthwise separable convolution module.

See https://arxiv.org/pdf/1704.04861.pdf for details.

This module can replace a ConvModule with the conv block replaced by two conv block: depthwise conv block and pointwise conv block. The depthwise conv block contains depthwise-conv/norm/activation layers. The pointwise conv block contains pointwise-conv/norm/activation layers. It should be noted that there will be norm/activation layer in the depthwise conv block if norm_cfg and act_cfg are specified.

Parameters

• in_channels (int) – Same as nn.Conv2d.

• out_channels (int) – Same as nn.Conv2d.

• kernel_size (int or tuple[int]) – Same as nn.Conv2d.

• stride (int or tuple[int]) – Same as nn.Conv2d. Default: 1.

• padding (int or tuple[int]) – Same as nn.Conv2d. Default: 0.

• dilation (int or tuple[int]) – Same as nn.Conv2d. Default: 1.

• norm_cfg (dict) – Default norm config for both depthwise ConvModule and pointwise ConvModule. Default: None.

• act_cfg (dict) – Default activation config for both depthwise ConvModule and pointwise ConvModule. Default: dict(type=’ReLU’).

• dw_norm_cfg (dict) – Norm config of depthwise ConvModule. If it is ‘default’, it will be the same as norm_cfg. Default: ‘default’.

• dw_act_cfg (dict) – Activation config of depthwise ConvModule. If it is ‘default’, it will be the same as act_cfg. Default: ‘default’.

• pw_norm_cfg (dict) – Norm config of pointwise ConvModule. If it is ‘default’, it will be the same as norm_cfg. Default: ‘default’.

• pw_act_cfg (dict) – Activation config of pointwise ConvModule. If it is ‘default’, it will be the same as act_cfg. Default: ‘default’.

• kwargs (optional) – Other shared arguments for depthwise and pointwise ConvModule. See ConvModule for ref.

forward(x: torch.Tensor) → torch.Tensor

Forward function.

Parameters

x (Tensor) – Input tensor with shape (N, C, H, W).

Returns

Output tensor.

Return type

Tensor