def _make_conv_layers(self, in_channels: int,
                          layer_out_channels: Sequence[int],
                          layer_kernel_sizes: Sequence[int]) -> nn.Module:
        """Create convolutional layers by given parameters."""

        layers = []
        for out_channels, kernel_size in zip(layer_out_channels,
                                             layer_kernel_sizes):
            padding = (kernel_size - 1) // 2
            cfg = dict(
                type='Conv2d',
                in_channels=in_channels,
                out_channels=out_channels,
                kernel_size=kernel_size,
                stride=1,
                padding=padding)
            layers.append(build_conv_layer(cfg))
            layers.append(nn.BatchNorm2d(num_features=out_channels))
            layers.append(nn.ReLU(inplace=True))
            in_channels = out_channels

        return nn.Sequential(*layers)
Create convolutional layers by given parameters.
mmpose/projects/skps/models/skps_head.py