In the pytorch demo, there is a DCGAN code

  
      github.com
  
  
    pytorch/examples/blob/master/dcgan/main.py 12
from __future__ import print_function
import argparse
import os
import random
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data
import torchvision.datasets as dset
import torchvision.transforms as transforms
import torchvision.utils as vutils


parser = argparse.ArgumentParser()
parser.add_argument('--dataset', required=True, help='cifar10 | lsun | mnist |imagenet | folder | lfw | fake')
parser.add_argument('--dataroot', required=True, help='path to dataset')
parser.add_argument('--workers', type=int, help='number of data loading workers', default=2)
parser.add_argument('--batchSize', type=int, default=64, help='input batch size')


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In this picture，

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I don’t understand input.data.resize_ and label.data.resize_. Why not use  input.resize_ and label.resize_.
Thanks for help!