By directly making use of an optimizer, we can write very short code to train a model. But in some extreme case, we have to write a code flow which needs to manually control forward and backward such as calling zero gradients, calculateGradients, update, etc… in a loop. How to write this flow? Could please provide code?
What is the basic code flow of manually forward and backward instead of directly using an optimizer?
@TempKonduitUser1 take a look at this for workign with external gradients: deeplearning4j-examples/MultiLayerNetworkExternalErrors.java at master · deeplearning4j/deeplearning4j-examples · GitHub