@ptrblck
Hi!
This time, there is little confusion with the fc layer. I followed the finetune tutorial (just want to run with aux_logits=True): for inception as there is only one aux_logit below snippet working fine.
    elif model_name == "inception":
        """ Inception v3 
        Be careful, expects (299,299) sized images and has auxiliary output
        """
        model_ft = models.inception_v3(pretrained=use_pretrained)
        set_parameter_requires_grad(model_ft, feature_extract)
        # Handle the auxilary net
        num_ftrs = model_ft.AuxLogits.fc.in_features
        model_ft.AuxLogits.fc = nn.Linear(num_ftrs, num_classes)
        # Handle the primary net
        num_ftrs = model_ft.fc.in_features
        model_ft.fc = nn.Linear(num_ftrs,num_classes)
        input_size = 299

correspoing inception_v3 net file snippet:
if self.training and self.aux_logits:
aux = self.AuxLogits(x)

and the fc snippet:
self.fc = nn.Linear(768, num_classes)

Whereas for GoogLeNet has two auxilary outputs, the net file snippet has:
if self.training and self.aux_logits:
aux1 = self.aux1(x)
.....
if self.training and self.aux_logits:
aux2 = self.aux2(x)

and the fc snippets:
self.fc1 = nn.Linear(2048, 1024)
self.fc2 = nn.Linear(1024, num_classes)

Now, my confusion is about using the fc in finetuning script, how to embed?
num_ftrs = model_ft.(aux1/aux2).(fc1/fc2).in_features
model_ft.(aux1/aux2).(fc1/fc2) = nn.Linear(num_ftrs, num_classes)

any thoughts?