How to get a intermediate value from nn.Sequential?

[shadeofplato]

Hi @InnovArul,
The problem I was concerned with was getting output of the hidden layers of AlexNet. It turned out that @fmassa has already provided a simple solution:

How to extract features of an image from a trained model

To complement @apaszke reply, once you have a trained model, if you want to extract the result of an intermediate layer (say fc7 after the relu), you have a couple of possibilities. You can either reconstruct the classifier once the model was instantiated, as in the following example: import torch import torch.nn as nn from torchvision import models model = models.alexnet(pretrained=True) # remove last fully-connected layer new_classifier = nn.Sequential(*list(model.classifier.children())[:-…