PyTorch – Tensor computation with strong GPU acceleration(pytorch.org)
pytorch.org
PyTorch – Tensor computation with strong GPU acceleration
https://pytorch.org/
5 comments
> decreased overhead for the practical lessons by a lot.
What do they mean by that?
What do they mean by that?
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.
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.
Thank god you weren’t around when keras was released.
Use fastai if you want your code to be unreadable, unmaintable and prone to mysterious bugs.
The framework which put my trust back into frameworks. Very good!
Apart from the official tutorials what are the best resources out there for learning PyTorch?
I really enjoyed this book for RL. https://www.packtpub.com/gb/big-data-and-business-intelligen...
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
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
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.
This is really old, it came out in 2016.
Why did you reshare it ?
Why did you reshare it ?
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.