> So, over the years, I absorbed and appreciated that Torch was a user-centric product, which stood for immediate-mode, easy-to-debug, stay-out-of-the-way explicitness. It was targeted at people somewhat familiar with programming matters, and who could reason about things like performance, and if needed, write a C function and bind it in quickly.
This paragraph sort of surprises me. In my experience if you want to do anything other than calling out to numeric libraries, you can do it in Lua and it will work, or you can do it in Python and suddenly your machine learning pipeline will spend 95% of its time running Python while your GPU idles. So the need to be able to drop down to C is much more severe in Python, and the difficulty of calling out to C is much greater.
This paragraph sort of surprises me. In my experience if you want to do anything other than calling out to numeric libraries, you can do it in Lua and it will work, or you can do it in Python and suddenly your machine learning pipeline will spend 95% of its time running Python while your GPU idles. So the need to be able to drop down to C is much more severe in Python, and the difficulty of calling out to C is much greater.