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View Code? Open in Web Editor NEWAn gradient-free optimization suite written in JAX. We conform to the optax interface and provide ensemble-based optimizers.
License: Other
An gradient-free optimization suite written in JAX. We conform to the optax interface and provide ensemble-based optimizers.
License: Other
We need to add an example with a simple normalizing flow.
We need
context
In order to achieve full compatibility with JAX we need to make sure that all ensemble gradient estimators actually work with nested parameter containers.
ideas
The main problem lies in building parameter covariance matrices for the model parameters. This should be equivalent to building covariance matrices with blocks structure, assembling the larger covariance matrix, disassembling it, etc. Perhaps it is possible to leverage JAX's ability to compute on pytrees directly?
next step
deep dive into pytree datastructure, computing with pytree in jax, and recasting the problem of addition and matrix multiplication in terms of pytrees
We need to implement the first version of an optimizer class. Test need to be implemented to compare against existing codebases.
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