# 保存模型示例代码
print('===> Saving models...')
state = {
  'state': model.state_dict(),
  'epoch': epoch          # 将epoch一并保存
}
if not os.path.isdir('checkpoint'):
  os.mkdir('checkpoint')
torch.save(state, './checkpoint/autoencoder.t7')

print('===> Try resume from checkpoint')
if os.path.isdir('checkpoint'):
  try:
    checkpoint = torch.load('./checkpoint/autoencoder.t7')
    model.load_state_dict(checkpoint['state'])    # 从字典中依次读取
    start_epoch = checkpoint['epoch']
    print('===> Load last checkpoint data')
  except FileNotFoundError:
    print('Can\'t found autoencoder.t7')
else:
  start_epoch = 0
  print('===> Start from scratch')

def vgg19(pretrained=False, **kwargs):
  """VGG 19-layer model (configuration "E")
 
  Args:
    pretrained (bool): If True, returns a model pre-trained on ImageNet
  """
  model = VGG(make_layers(cfg['E']), **kwargs)
  if pretrained:
    model.load_state_dict(model_zoo.load_url(model_urls['vgg19']))
  return model

model_dir = '自己的模型地址'
model = VGG()
model.load_state_dict(torch.load(model_dir + 'vgg_conv.pth'))