https://github.com/blue-season/pywarm
PyWarm is a lightweight, high-level neural network construction API for PyTorch. It enables defining all parts of NNs in the functional way.
I don't see much of a reason you want to clutter your code with that, if you need a wrapper around pytorch use fastai not some obscure library nobody has ever heard about.
What exactly are you looking for? I think Pytorch is so ergonomic that there is no need for other resources. The only gotchas I found were in the data loading utilities.
If you learn well from videos many rave about the free fast.ai courses which now use PyTorch I believe. Seems to start with image classification. http://fast.ai
>We’ll still use @PyTorch but more for research lessons, I’ll post more on this decision soon! I did deliberate for several weeks on this though but ultimately it sped up development and decreased overhead for the practical lessons by a lot.
Presumably that it was easier to use to illustrate the actual content as opposed to implementation details. This is definitely the case, at least in TensorFlow 1.x there were a lot of details which made converting from [the way we think about the problem] to [practical implementation] more cumbersome. Some of these existed for good reason (eg. performance) while others were simply architectural cruft which the benefit of hindsight makes unnecessary.
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[ 2.8 ms ] story [ 40.1 ms ] threadIf you learn well from videos many rave about the free fast.ai courses which now use PyTorch I believe. Seems to start with image classification. http://fast.ai
https://twitter.com/GokuMohandas/status/1174497967232782336
>We’ll still use @PyTorch but more for research lessons, I’ll post more on this decision soon! I did deliberate for several weeks on this though but ultimately it sped up development and decreased overhead for the practical lessons by a lot.
What do they mean by that?
Why did you reshare it ?