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Neat, I love projects like these. The next level down is to do it directly in numpy. And then from there, write a minimal numpy work-a-like to support the mod
by sitkack 2y ago
Neat, I love projects like these.
The next level down is to do it directly in numpy.
And then from there, write a minimal numpy work-a-like to support the model above.
You start with a working system using the most powerful abstractions. Then you iteratively remove abstractions, lowering your solution, then when you get low enough but still riding on an external abstraction, you rewrite that, but ONLY to support the layers above you.
Following the above pattern, you can bootstrap yourself to have full system understanding. This is not unlike RL+distillation that human persons do learn complex topics.
- lagrange77 2y ago> but still riding on an external abstraction, you rewrite that, but ONLY to support the layers above you. i don't get it. Why do i stop before stripping all abstractions?
- byteknight 2y agoWhere do you get that? He is postulating the external abstraction you are using has more features than you use. He is saying implement only the parts you use.
- lagrange77 2y ago> Where do you get that? From "when you get low enough but still riding on an external abstraction". > He is saying implement only the parts you use. Thanks.
- sitkack 2y agoCorrect, I should proof read my posts.
- tomrod 2y agoLikewise. And your comment reminded me of real programmers* * https://xkcd.com/378/ https://xkcd.com/378/
- bee_rider 2y agoNumpy can use the chipmaker’s BLAS (Intel MKL or AMD’s Blis fork). Trying to replace it could be a good academic exercise but I think most people wisely leave that to the vendors.