I have another question
I am trying to train Resnet50 and Inception_v3 simultaneously
I make the following class
class TwoInputsNet(nn.Module):
  def __init__(self):
    super(TwoInputsNet, self).__init__()
    self.model1 = torchvision.models.resnet50(pretrained=True)
    self.model1.fc = nn.Linear(2048, 1024)        
    self.model2 = torchvision.models.inception_v3(pretrained=True)
    self.model2.fc = nn.Linear(2048, 1024)
    self.fc2 = nn.Linear(2048, 1)


  def forward(self, input1, input2):
    c = self.model1(input1)
    f = self.model2(input2)
    combined = torch.cat((c,torch.Tensor(f)), dim=1)

    out = self.fc2(combined)
    return out

and I am getting the following error:
  File "D:/Face Beauty Pytorch/transfer_learning_inception_resnet50_regression.py", line 152, in <module>
    preds = model(images1, images2)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)

  File "D:/Face Beauty Pytorch/transfer_learning_inception_resnet50_regression.py", line 82, in forward
    f = self.model2(input2)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torchvision\models\inception.py", line 132, in forward
    aux = self.AuxLogits(x)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torchvision\models\inception.py", line 332, in forward
    x = self.conv1(x)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torchvision\models\inception.py", line 353, in forward
    x = self.bn(x)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\module.py", line 541, in __call__
    result = self.forward(*input, **kwargs)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\modules\batchnorm.py", line 81, in forward
    exponential_average_factor, self.eps)

  File "c:\users\fares\appdata\local\programs\python\python37\lib\site-packages\torch\nn\functional.py", line 1666, in batch_norm
    raise ValueError('Expected more than 1 value per channel when training, got input size {}'.format(size))

ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 768, 1, 1])

Could you suggest any solution to this issue ??