you question is vague.
If you want to know about a network you must print your model after loading it.
vgg_model = torchvision.models.vgg16()
print(vgg_model)
the print command shows all layers in network.
Regarding input layer and output layer, you must know that the input data is considered as input layer and the last layer is considered as output layer. But, convolution networks own two sections: feature map and classification
usually in feature map section, some layers like conv2d, maxpooling are used. Also, in classification layer fully connected layers (MLP) are used; however, in some works other methods of classifications like SVM is used.
No layer generates tensor. Before feeding input data to a network you must use transformation. In the line where you define transformation, the function for converting input data to tensor is added.
I hope I could see what was your mean and answered correctly