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Keras vs PyTorch

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Re: Keras vs PyTorch

#11

Post by formalsystem »

This article echoes my experience as well. I was working on some core NLP models for a larger tech company and wanted to experiment with Keras. I had my models designed within a day and training done within another and had amazing model perf.

I was also told that doing it the real way using Tensorflow would be the way to go and I agree with that sentiment if my problem was Google scale which it wasn't. In fact I would argue that most workloads around the world are not Google scale and neither are most Google workloads.

This attitude of "real deep learning engineers use Tensorflow" is an unhelpful way of saying "I agree that the API is unreadable but I've invested so much time in the ecosystem that I'll refuse to see its usability problems". Kind of reminds me of assembly programmers that thought C wasn't for l33t 10xx pwner programmers.

Re: Keras vs PyTorch

#12

Post by stared »

BTW (from author - of blog post, and this library): for super-simple live training plots in Jupyter Notebook for Keras (and PyTorch): https://github.com/stared/livelossplot

For more advanced training for business or Kaggle competitions (version controlling of code and results, advanced charts): https://neptune.ml/

Re: Keras vs PyTorch

#13

Post by bitL »

Raf_ wrote: post #2

Author here - the article compares Keras and PyTorch as the first Deep Learning framework to learn. It explores the differences between the two in terms of ease of use, flexibility, debugging experience, popularity, and performance, among others. If you have experience with learning, or teaching Deep Learning with PyTorch or Keras, we’d love to hear your thoughts about them.

I agree, I also use Keras for stable complex models (up to 1000 layers) in production and PyTorch for fun (DRL). However, if I want to run a distributed training optimization with minimum setup, whether I like it or not, the simplest way is to use TensorFlow's Estimator model and some pre-baked environment like SageMaker. Horovod or CERNDB/Keras require a bit more setup/devops work. The issue with estimators is that once you start using some bleeding-edge things in Keras, it might be very complicated to translate them back to estimators, despite conversion from Keras model to tf.Estimator being trivial.

Re: Keras vs PyTorch

#14

Post by Ar-Curunir »

formalsystem wrote: post #11

This article echoes my experience as well. I was working on some core NLP models for a larger tech company and wanted to experiment with Keras. I had my models designed within a day and training done within another and had amazing model perf. I was also told that doing it the real way using Tensorflow would be the way to go and I agree with that sentiment if my problem was Google scale which it wasn't. In fact I woul…

> Kind of reminds me of assembly programmers that thought C wasn't for l33t 10xx pwner programmers.

It's funny because this the same attitude C/C++ programmers have towards developers using other languages now...

Re: Keras vs PyTorch

#15

Post by hknd »

formalsystem wrote: post #11

This article echoes my experience as well. I was working on some core NLP models for a larger tech company and wanted to experiment with Keras. I had my models designed within a day and training done within another and had amazing model perf. I was also told that doing it the real way using Tensorflow would be the way to go and I agree with that sentiment if my problem was Google scale which it wasn't. In fact I woul…

From my opinion: Getting started with Tensor Flow, and having a model designed within a day and training within another is also possible. This mostly depends on your model and your data, and (imho) not on the framework of choice.

For all, Keras/PyTorch/Tensorflow, you'll need to learn the API - but if you have any ML background, that should be straight forward.

Re: Keras vs PyTorch

#18

Post by pdyck »

That's what I did for my bachelor's thesis. I didn't take any advanced Maths classes, so I had to learn everything from scratch. Keras helped me to build an intuition for neural networks and made me more interested in learning about the formulas and how it works with TensorFlow in the background. I really enjoyed learning with this top-down approach.

Re: Keras vs PyTorch

#19

Post by phonebucket »

I don't believe I would ever discourage anyone from using any particular framework. The skills learnt from one are highly transferable, so it doesn't matter too much which framework you start with.

Also, with eager execution, Tensorflow has become much more accessible to new users.

Having said that, the world would likely be a better place if everyone just used PyTorch :)

Re: Keras vs PyTorch

#20

Post by laingc »

zerostar07 wrote: post #17

While we are at it, which framework is the easiest to tweak at the low-level, e.g. create modified LSTMs etc ?

Pytorch, by a mile.

If I had to summarise the frameworks in a few words, they would be: Keras for speed, Tensorflow for production, Pytorch for research.

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