Shortcuts

DepthwiseSeparableConvModule

class mmcv.cnn.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: 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)[源代码]

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.

参数
  • in_channels (int) – Number of channels in the input feature map. Same as that in nn._ConvNd.

  • out_channels (int) – Number of channels produced by the convolution. Same as that in nn._ConvNd.

  • kernel_size (int | tuple[int]) – Size of the convolving kernel. Same as that in nn._ConvNd.

  • stride (int | tuple[int]) – Stride of the convolution. Same as that in nn._ConvNd. Default: 1.

  • padding (int | tuple[int]) – Zero-padding added to both sides of the input. Same as that in nn._ConvNd. Default: 0.

  • dilation (int | tuple[int]) – Spacing between kernel elements. Same as that in nn._ConvNd. 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[源代码]

Defines the computation performed at every call.

Should be overridden by all subclasses.

注解

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

Read the Docs v: stable
Versions
latest
stable
2.x
v2.0.1
v2.0.0
1.x
v1.7.1
v1.7.0
v1.6.2
v1.6.1
v1.6.0
v1.5.3
v1.5.2_a
v1.5.1
v1.5.0
v1.4.8
v1.4.7
v1.4.6
v1.4.5
v1.4.4
v1.4.3
v1.4.2
v1.4.1
v1.4.0
v1.3.18
v1.3.17
v1.3.16
v1.3.15
v1.3.14
v1.3.13
Downloads
pdf
html
epub
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.