is it possible to resize the input layer of an engine at the start of the inference?
And is it possible to get the output dimensions of the same engine?
For example i want to run alexnet, only the first layers until the first maxpooling. Now it would support any image size, but because i load the engine from a trained caffe model i takes the image size from the .prototxt.
For clearity: I want to change the input size when i have the optimized engine not before (otherwise training would take ages.)
I can change the input size in the prototxt, but it would be way easier in code. If it would be poosible to change the input size “dynamically”, is there a way to extract the output size?
I could be:
but in python this gives me c pointer (?) which i can’t dereference…