Hi, I’m looking at the tutorial  TORCHVISION OBJECT DETECTION FINETUNING TUTORIAL 12.
In the 2nd part of the tutorial, the author changes the backbone architecture of the pre-trained model by doing the following:
# load a pre-trained model for classification and return
# only the features
backbone = torchvision.models.mobilenet_v2(pretrained=True).features
...
...

What is .features actually doing? I can’t find its documentation.
Does it just return the final layer before a softmax?