def _conv_bn(self, kernel_size: int, padding: int) -> nn.Sequential:
        """Construct conv-batchnorm layers.

        :param kernel_size: Size of the convolution kernel.
        :param padding: Zero-padding size.
        :return: Conv-BN module.
        """
        mod_list = nn.Sequential()
        mod_list.add_module(
            "conv",
            nn.Conv2d(
                in_channels=self.in_channels,
                out_channels=self.out_channels,
                kernel_size=kernel_size,
                stride=self.stride,
                padding=padding,
                groups=self.groups,
                bias=False,
            ),
        )
        mod_list.add_module("bn", nn.BatchNorm2d(num_features=self.out_channels))
        return mod_list
Construct conv-batchnorm layers.

        :param kernel_size: Size of the convolution kernel.
        :param padding: Zero-padding size.
        :return: Conv-BN module.
        
segmentation_models_pytorch/encoders/mobileone.py