@classmethod
def next_conv_block(cls, inputs, layout, filters, bottleneck,
    resnext_factor, **kwargs):
    """ ResNeXt convolution block

        Parameters
        ----------
        inputs
            input tensor
        filters : int
            number of output filters
        bottleneck : bool
            whether to use a simple or a bottleneck block
        resnext_factor : int
            cardinality for ResNeXt model
        kwargs : dict
            `ConvBlock` parameters

        Returns
        -------
        nn.Module
        """
    if bottleneck:
        filters = filters * kwargs['bottleneck_factor']
        filters = [filters // 2, filters // 2, filters]
        kwargs['groups'] = [1, resnext_factor, 1]
    else:
        filters = [resnext_factor * 4, filters]
    x = cls.conv_block(inputs, layout, filters=filters, bottleneck=
        bottleneck, **kwargs)
    return x
