How to use the lpips.base_model.BaseModel function in lpips

import numpy as np
import torch
from torch import nn
import os
from collections import OrderedDict
from torch.autograd import Variable
import itertools
import lpips.util.util as util
from .base_model import BaseModel
from . import networks_basic as networks
from scipy.ndimage import zoom

class DistModel(BaseModel):
    def name(self):
        return self.model_name

    def initialize(self, model='net-lin', net='squeeze', colorspace='Lab', use_gpu=True, printNet=False):
        '''
        INPUTS
            model - ['net-lin'] for linearly calibrated network
                    ['net'] for off-the-shelf network
                    ['L2'] for L2 distance in Lab colorspace
                    ['SSIM'] for ssim in RGB colorspace
            net - ['squeeze','alex','vgg']
            colorspace - ['Lab','RGB'] colorspace to use for L2 and SSIM
            use_gpu - bool - whether or not to use a GPU
            printNet - bool - whether or not to print network architecture out
        '''
        BaseModel.initialize(self, use_gpu=use_gpu)