Multiprocessing Debugging for Neural Network Propagation

You are building a system to speed up neural network training by distributing forward and backward propagation across multiple processes. Given a description of a feed‑forward network and a dataset of labeled examples, your task is to compute the model's predictions on every data point and the average gradients of the cross‑entropy loss with respect to all weight matrices and bias vectors. The computation should be carried out using the number of worker processes specified…