text: from data.data_loader import CreateDataLoader
  from options.test_options import TestOptions
  from models.recycle_gan_model import RecycleGANModel
  from tensorboardX import SummaryWriter
  from util.util import tensor2im
  import torch
  
  opt = TestOptions().parse()
  opt.nThreads = 1  # test code only supports nThreads = 1
  opt.batchSize = 1  # test code only supports batchSize = 1
  opt.serial_batches = True  # no shuffle
  opt.no_flip = True  # no flip
  
  data_loader = CreateDataLoader(opt)
  dataset = data_loader.load_data()
  model = RecycleGANModel()
  model.initialize(opt)
  model.netG_A.eval()
  writer = SummaryWriter('tbx/videotest')
  # create website
  # test
  real_A_vid = []
  fake_B_vid = []
  for i, data in enumerate(dataset):
  	if i == 3:
  		break
  	fakeB = model.netG_A(data['A'].cuda())
  	real_A_vid.append(tensor2im(data['A']))
  	fake_B_vid.append(tensor2im(fakeB))
  
  writer.add_video('A/real_A', torch.stack(real_A_vid, dim=0).unsqueeze(0).permute(0, 2, 1, 3, 4), 0)
  writer.add_video('A/fake_B', torch.stack(fake_B_vid, dim=0).unsqueeze(0).permute(0, 2, 1, 3, 4), 0)
  
  