> Does this show that in general the most used ML frameworks are a mess? Yes. Not really ... there is little to no overlap with what a framework like PyTorch d

> Does this show that in general the most used ML frameworks are a mess? Yes. Not really ... there is little to no overlap with what a framework like PyTorch does. There is no tensor class, no autograd, etc. Just malloc, a bunch of hand calculated pointers into that chunk of memory, and hand written gradient functions. I assume the intent here is to be educational by stripping away the layers of abstraction to make it clearer what is going on. Frankly though, this code (all that pointer math!) is a mess too, maybe written this way to make it easy to port to cuDNN which is at a similarly low level (other than having tensor descriptors which make the memory layout more flexible). If you want to write your own tensor class and reusable NN framework, then the lines of code go up very rapidly. I did one in C++ a while back, and the tensor class alone was 20K LOC.