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mmcls.models.utils.InvertedResidual

class mmcls.models.utils.InvertedResidual(in_channels, out_channels, mid_channels, kernel_size=3, stride=1, se_cfg=None, conv_cfg=None, norm_cfg={'type': 'BN'}, act_cfg={'type': 'ReLU'}, drop_path_rate=0.0, with_cp=False, init_cfg=None)

Inverted Residual Block.

参数

• in_channels (int) – The input channels of this module.

• out_channels (int) – The output channels of this module.

• mid_channels (int) – The input channels of the depthwise convolution.

• kernel_size (int) – The kernel size of the depthwise convolution. Defaults to 3.

• stride (int) – The stride of the depthwise convolution. Defaults to 1.

• se_cfg (dict, optional) – Config dict for se layer. Defaults to None, which means no se layer.

• conv_cfg (dict) – Config dict for convolution layer. Defaults to None, which means using conv2d.

• norm_cfg (dict) – Config dict for normalization layer. Defaults to dict(type='BN').

• act_cfg (dict) – Config dict for activation layer. Defaults to dict(type='ReLU').

• drop_path_rate (float) – stochastic depth rate. Defaults to 0.

• with_cp (bool) – Use checkpoint or not. Using checkpoint will save some memory while slowing down the training speed. Defaults to False.

• init_cfg (dict | list[dict], optional) – Initialization config dict.