Release 0.5.0 · pyro-ppl/numpyro

New documentation page with galleries of tutorials and examples num.pyro.ai.

New Features

New primitive: prng_key to draw a random key under seed handler.
New autoguide: AutoDelta
New samplers:
- HMCGibbs: a general HMC/NUTS-within-Gibbs interface.
- DiscreteHMCGibbs: HMC/NUTS-within-Gibbs for models with discrete latent variables.
- HMCECS: HMC/NUTS with energy conserving subsampling.
New example:
- CJS capture-recapture model for ecological data
New kernels module in numpyro.contrib.einstein, in preparing for (Ein)Stein VI inference in future releases.
New user-friendly SVI.run method to simplify the training phase of SVI inference.
New feasible_like method in constraints.
New methods forward_shape and inverse_shape in Transform to infer output shape given input shape.
Transform.inv now returns an inversed transform, hence enables many new (inversed) transforms.
Support thinning in MCMC.
Add post_warmup_state and last_state to allow sequential sampling strategy in MCMC: allow to keep calling .run method to get more samples.
New history argument to support for Markov models with history > 1 in scan.
New forward_model_differentiation argument in HMC/NUTS kernels to allow to use forward mode differentiation.

#886 Make TransformReparam compatible with .to_event()
#883 Improve gradient computation of Euclidean kinetic energy.
#872 Enhance masked distribution to allow gradient propagate properly when using mask handler for invalid data.
#865 Make subsample faster in CPU.
#860 Fix for memory leak in MCMC.
#849 Expose logits attribute to some discrete distributions
#848 Add has_rsample and rsample attribute to distributions
#832 Allow a callable to return an init value in param primitive
#824 Fix for cannot using sample method of TFP distributions in sample primitive.
#823 Demo on how to use various init strategies in Gaussian Process example.
#822 Allow haiku/flax modules to take general args/kwargs in init.
#821 Better error messages when rng_key is missing.
#818 Better error messages when an error happens in the middle of inference.
#805 Display correct progress bar message after running MCMC.warmup.
#801 Raise an error early if missing plates for models with discrete latent variables.
#797 MCMC vectorized chain method works for models with deterministic sites.
#796 Bernoulli distribution returns an int instead of a boolean.
#795 Reveal signature for help(Distribution).

Thanks Ola Ronning @OlaRonning, Armin Stepanjan @ab-10, @cerbelaut, Xi Wang @xidulu, Wouter van Amsterdam @vanAmsterdam, @loopylangur, and many others for your contributions and helpful feedback!