Closed forgi86 closed 1 month ago
Hi @forgi86,
Could you please make a PR request with these new changes?
Thanks!
Hello @gerdm,
I opened a PR, but only fixed the bayesian-neural-network example. I was trying to fix the bnn-hierarchical-flax example (that is the most interesting for my current activities), but there seems to be another bug there.
I can't evaluate the potential, if I run
potential(params_all)
it throws a ValueError: Arity mismatch between trees
Unfortunately I don't have time to look into it at the moment...
OK, I also fixed the bug in the hbnn potential. Variable params_sigma_tree in build_sigma_tree had one more singletone initial dimension than needed (perhaps a change in linen's pytree structure?)
All fixed in my fork (https://github.com/forgi86/bayes). I also made a few changes to remove warnings for deprecated stuff.
Thanks for your contribution @forgi86!
I'll take a look at this tonight.
Closed by #3
Hello, I an new to blackjax and recently came across your nice examples. However, I had to change a few line of codes to use recent versions of the jax/blackjax ecosystem, in particular the adaptation algorithm. For instance, in bayesian-neural-network.ipynb, I had to change the lines below the definition of the "potential" to: