I am new into DL and pytorch framework, sorry for asking simple questions.
How to write the new custom model when I am using transfer learning?  Does it mean, I won’t be able to use these lines
model = nn.Sequential(*list(model.children())[:-22])
model_new = nn.Sequential(model, PtConv(64, 64, 16, 3, use_bias=False), Flatten(), nn.Linear(64+64, 10), nn.ReLU(),  nn.Dropout(0.4))
train_dir = os.path.join('./training_10')


as both of them has nn.Sequential()?
Is there any example that I can go through to understand the concept?
I thought I had to use nn.Sequential() to add the previous model with the new layers to create a new network.
Thanks