def METHOD_NAME(self, inputs, shape):
    """
    args:
        inputs(list): List of tensor to be fused.
        shape(Tensor): A tensor with two elements like (H, W).
    """
    feas = []
    for i, input in enumerate(inputs):
        x = self.pwconvs[i](input)
        x = F.interpolate(
            x, size=shape, mode='bilinear', align_corners=False)
        x = self.dwconvs[i](x)
        feas.append(x)
    atten = helper.avg_max_reduce_channel(feas)
    atten = F.sigmoid(self.conv_atten(atten))
    feas_att = []
    for i, fea in enumerate(feas):
        fea = fea * (atten[:, i, :, :].unsqueeze(1))
        feas_att.append(fea)
    if self.merge_type == 'concat':
        out = paddle.concat(feas_att, axis=1)
    else:
        out = sum(feas_att)
    out = self.conv_out(out)
    return out