Hi, I’m really interested in participating in Project: Dynamic_DeepChem via GSoC.
I have some questions about this project and I seem other people are also interested like following a gitter comment.
out of curiosity, why do you want to migrate to JAX? I thought migration from TF1 > TF2 would be enough. Then I remember there were some mentions of using PyTorch, and now JAX. Isn’t it going to be a massive pain to reimplement every Keras/TF/Pytorch model out there in JAX, as well as adding new ones?
I m strongly pro PyTorch, in Pytorch vs JAX, especially seeing how popular the former is in the research community and how new JAX is
So, I post this topic. I mainly have the same opinion as the above comments.
My main question is why do you want to migrate to JAX or Pytorch?
As mentioned above, I also think TF2 may be enough. Many GCN libraries like dgl are written by Pytorch. I think deepchem will be appreciated by TF users if deepchem is written by TF.
On the other hand, I know many new GCN models are written by Pytorch. I could understand the necessity of reimplementation by Pytorch if deepchem want to attract more attention, especially from research community.
In the case of JAX, I think JAX is a good framework. JAX is fast and readable because of Define and Run and numpy like API. However, I seem that JAX is early stage. Even installation is difficult and NN framework based on JAX are under development like flax.
In summry, I just want to know your opinions
- Why do you want to migrate? (TF2 is enough?)
- Which is better for migration, JAX or Pytorch ?