ptrblck:

RE


my use case is compute intermediate layer Output result and send to another server when another half of execution will be done something like client server environment. For example if an alexnet has 12 layers first machine will be having 6 layers running in it which will take the image input and we will get the intermediate output (tensor object) of it and then sent it through network and use it as input for next half of the model. Is there any way to do it? Even in my current scenario the numpy array is intact only the grad_fn is missing for future prediciton