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@fritzo fritzo released this 16 Nov 03:34
· 715 commits to dev since this release
1.0.0
d216f0d

The objective of this release is to stabilize Pyro's interface and thereby make it safer to build high level components on top of Pyro.

Stability statement

  • Behavior of documented APIs will remain stable across minor releases, except for bug fixes and features marked EXPERIMENTAL or DEPRECATED.
  • Serialization formats will remain stable across patch releases, but may change across minor releases (e.g. if you save a model in 1.0.0, it will be safe to load it in 1.0.1, but not in 1.1.0).
  • Undocumented APIs, features marked EXPERIMENTAL or DEPRECATED, and anything inpyro.contrib may change at any time (though we aim for stability).
  • All deprecated features throw a FutureWarning and specify possible work-arounds. Features marked as deprecated will not be maintained, and are likely to be removed in a future release.
  • If you want more stability for a particular feature, contribute a unit test.

New features

  • pyro.infer.Predictive is a new utility for serving models, supporting jit tracing and serialization.
  • pyro.distributions.transforms has many new transforms, and includes helper functions to easily create a variety of normalizing flows. The transforms library has also been reorganized.
  • pyro.contrib.timeseries is an experimental new module with fast Gaussian Process inference for univariate and multivariate time series and state space models.
  • pyro.nn.PyroModule is an experimental new interface that adds Pyro effects to an nn.Module. PyroModule is already used internally by AutoGuide, EasyGuide pyro.contrib.gp, pyro.contrib.timeseries, and elsewhere.
  • FoldedDistribution is a new distribution factory, essentially equivalent to TransformedDistribution(-, AbsTransform()) but providing a .log_prob() method.
  • A new tutorial illustrates the usage of pyro.contrib.oed in the context of adaptive election polling.

Breaking changes

  • Autoguides have slightly changed interfaces:
    • AutoGuide and EasyGuide are now nn.Modules and can be serialized separately from the param store. This enables serving via torch.jit.trace_module.
    • The Auto*Normal family of autoguides now have init_scale arguments, and init_loc_fn has better support. Autoguides no longer support initialization by writing directly to the param store.
  • Many transforms have been renamed to enforce a consistent interface, such as the renaming of InverseAutoregressiveFlow to AffineAutoregressive.
  • pyro.generic has been moved to a separate project pyroapi.
  • poutine.do has slightly changed semantics to follow Single World Intervention Graph semantics.
  • pyro.contrib.glmm has been moved to pyro.contrib.oed.glmm and will eventually be replaced by BRMP.
  • Existing DeprecationWarnings have been promoted to FutureWarnings.

Deprecated features

  • pyro.random_module: The pyro.random_module primitive has been deprecated in favor of PyroModule which can be used to create Bayesian modules from torch.nn.Module instances.
  • SVI.run: The SVI.run method is deprecated and users are encouraged to use the .step method directly to run inference. For drawing samples from the posterior distribution, we recommend using the Predictive utility class, or directly by using the trace and replay effect handlers.
  • TracePredictive: The TracePredictive class is deprecated in favor of Predictive, that can be used to gather samples from the posterior and predictive distributions in SVI and MCMC.
  • mcmc.predictive: This utility function has been absorbed into the more general Predictive class.
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