spark-nlp VS memory64

I recently had the opportunity to run a workshop at ODSC East, focusing on using PySpark for Natural Language Processing (NLP). Had a great time explaining PySpark's fundamentals and exploring the Spark NLP library.

I'd like to use this transformer model in rust (because it's on the backend, because I can use data munging and it will be faster, and for other reasons). It looks like a good model! But, it doesn't compile on Apple Silicon for wierd linking issues that aren't apparent - https://github.com/guillaume-be/rust-bert/issues/338. I've spent a large part of today and yesterday attempting to find out why. The only other library that I've found for doing this kind of thing programmatically (particularly sentiment analysis) is this (https://github.com/JohnSnowLabs/spark-nlp). Some of the models look a little older, which is OK, but it does mean that I'd have to do this in another language.

Does anyone know of any sentiment analysis software that can be tuned (other than VADER - I'm looking for more along the lines of a transformer model) - like BERT, but is pretrained and can be used in Rust or Python? Otherwise I'll probably using spark-nlp and having to spin another process.

Thanks.

A completed implementation of memory64 for memory-hungry applications.

Indeed, webassembly is moving extremely slowly. I started a project years ago expecting https://github.com/WebAssembly/memory-control/blob/main/prop... and https://github.com/WebAssembly/memory64 to be fixed at some point. Neither are yet, and the project still suffers from it to this day.

I think wasm is still great without these fixes, but I have lost confidence in the idea that wasm will reach its full potential any time soon.

It's in the works: https://github.com/WebAssembly/memory64

Starting with 32bit had some performance advantages because 64bit runtimes can use virtual memory shenanigans to implement bounds checking with zero overhead. In wasm64 they'll have to do explicit bounds checking instead.

Right - currently, everything runs using WASM (32-bit, with 64-bit coming soon [1,2]), and I plan to add support for WebGPU soon!

(WebGPU is the successor to WebGL, which is coming out in April 2023 [3])

[1] https://github.com/WebAssembly/memory64/issues/36#issuecomme...

It shouldn't be a big surprise that a 64-bit pointer extension is out there and being worked on. The great thing about a VM is you can integrate major changes like this when they are needed and with the benefit of experience and hindsight. If the 4GB limit turns out to be restrictive then it can be lifted.

The goal of this proposal is to increase the amount of memory that canisters can access [eventually] bound only by the actual capacity of the subnet. Since, the Memory64 proposal is not standardized 1 yet and its implementation 1 in Wasmtime is not production ready yet, this proposal enables the increase by introducing a new stable memory API.