In the screenshot given y1 and y2 are two models
at the end of model code, input is mentioned as input layer and output as output layer (y1 and y2)
So my doubt is won’t model mistake input layer of y2 with output layers of y1 or vice versa???
I am a learner if you find this doubt silly, I am sorry!!!
If answer is no for my doubt then please explain…\
Thank You
Hello,
There is one input with 2 outputs, imagine like a tree with one root and 2 branches.
yes I understood that part but here the input for y1 and y 2 are different, so it cannot be from same root.
like for y2 input is ?,64 where as y2 input is ?,128, so can reading together in model lead to two separate models if the code is return in one?
I am sorry again I want to know how the model identifies input for y2 and y1 separately?? Just want to know reason towards this code!!!
If you follow the diagram you can see the arrows from one branch to the 2 outputs.
Be clear, the input to the model is only input_2, the input and output for each layer is only related to that layer and its connection to the previous and next layer.
These are not 2 separate models as I said imagine one tree with 2 branches.
yes that is clearly explained in the video. O ok so I was taking input for y1 from dense_4 and y2 from dense_5 that what confused me as he told in this it is not sequential API but functional API so that’s why the model will read based on any layering pattern right???
I just saw Siamese network where model was mentioned model=input_a and input_b, output because both have different base network.
I hope I am getting it right!!!
