Tensorflow-probability

This is RC0 of the TensorFlow Probability 0.11 release. It is tested against TensorFlow 2.3.0-rc1.

This is a patch release to pin the CloudPickle version to 1.3 to address 991 . It is tested and stable against TensorFlow version 2.2.0.

Release notes

This is the 0.10 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.2.0.

Change notes
- Distributions
- Beta-Binomial distribution.
- Add new `AutoBatched` joint distribution variants that treat a joint sample as a single probabilistic event.
- XLA-able Python TF Gamma sampler.
- XLA-able binomial sampler. Replaces the existing sampler, which implements binomial using one-hot categoricals via multinomial, with a batched rejection sampler. The new sampler is 4-6 times slower for very small problems, but an unbounded amount faster on large problems, since it removes a linear dependency on `total_count`. Additionally, since the previous solver required memory proportional to total_count*num_samples, many problems which OOM'd before are now feasible.
- Enable use of joint bijectors in TransformedDistribution.
- Remove unused `get_logits_and_probs` from internal/distribution_util.
- Batched rejection sampling utilities.
- Update batched_rejection_sampler to use prefer_static.shape to handle possibly-dynamic shape.

- Bijectors
- Add Lambert W transform bijectors.

- MCMC
- EllipticalSliceSampler in tfp.experimental.mcmc
- Add cross-chain ESS, following Vehtari et al. 2019.

- Optimizer
- Add convergence criteria for optimizations.

- Stats
- Add `tfp.stats.expected_calibration_error_quantiles`.

- Math
- Add a 'special' module to tfp.math - a TF version of scipy.special.
- Add `scan_associative` function, implementing parallel prefix scan of tensors with a user-provided binary operation.

- Breaking change: Removed a number of functions, methods, and classes that were deprecated in TensorFlow Probability 0.9.0 or earlier.
- Removed deprecated tfb.Weibull -- use tfb.WeibullCDF.
- Remove VectorLaplaceLinearOperator
- Remove deprecated method `tfp.sts.build_factored_variational_loss`.
- Remove deprecated tfb.Kumaraswamy -- use tfb.Invert(tfb.KumaraswamyCDF).
- Remove deprecated tfd.VectorSinhArcsinhDiag, tfd.VectorLaplaceDiag.
- Remove deprecated `tfb.Gumbel` -- use `tfb.GumbelCDF`.

- Other
- Python 3.8 compatibility.
- TensorFlow now requires gast version 0.3.2 and is no longer compatible with 0.2.2.
- Moving TF Session C++ to Python code and functionality from swig to pybind11.
- Update TFP examples to Python 3.

Huge thanks to all the contributors to this release!

- Alexander Ivanov
- Alexey Radul
- Amanda
- Amelio Vazquez-Reina
- Amit Patankar
- Anudhyan Boral
- Artem Belevich
- Brian Patton
- Christopher Suter
- Colin Carroll
- Dan Moldovan
- Dave Moore
- Demetri Pananos
- Dmitrii Kochkov
- Emily Fertig
- gameshamilton
- Georg M. Goerg
- Ian Langmore
- Jacob Burnim
- jeffpollock9
- Joshua V. Dillon
- Junpeng Lao
- kovak1
- Kristian Hartikainen
- Liam
- Martin Jul
- Matt Hoffman
- nbro
- Olli Huotari
- Pavel Sountsov
- Pyrsos
- Rif A. Saurous
- Rushabh Vasani
- Sayam753
- Sharad Vikram
- Spyros
- Srinivas Vasudevan
- Taylor Robie
- Xiaojing Wang
- Zichun Ye

This is RC1 of the TensorFlow Probability 0.10 release. It is tested against TensorFlow 2.2.0-rc4.

This is the RC0 release candidate of the Tensorflow Probability 0.10 release. It is tested against Tensorflow 2.2.0-rc3.

Release notes

This is the 0.9 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.1.0.

NOTE: The 0.9 releases of TensorFlow Probability will be the last to support Python 2. Future versions of TensorFlow Probability will require Python 3.5 or later.

Change notes

- Distributions
- Add Pixel CNN++ distribution.
- Breaking change: Remove deprecated behavior of `Poisson.rate` and `Poisson.log_rate`.
- Breaking change: Remove deprecated behavior of `logits`, `probs` properties.
- Add `_default_event_space_bijector` to distributions.
- Add validation that samples are within the support of the distribution.
- Support positional and keyword args to `JointDistribution.prob` and `JointDistribution.log_prob`.
- Support `OrderedDict` dtype in `JointDistributionNamed`.
- `tfd.BatchReshape` is tape-safe
- More accurate survival function and CDF for the generalized Pareto distribution.
- Added Plackett-Luce distribution over permutations.
- Fix long-standing bug with `cdf`, `survival_function`, and `quantile` for `TransformedDistribution`s having decreasing bijectors.
- Export the DoubleMaxwell distribution.
- Add method for analytic Bayesian linear regression with LinearOperators.

- Bijectors
- Breaking change: Scalar bijectors must implement `_is_increasing` if using `cdf`/`survival_function`/`quantile` on `TransformedDistribution`. This supports resolution of a long-standing bug, e.g. `tfb.Scale(scale=-1.)(tfd.HalfNormal(0,1)).cdf` was incorrect.
- Deprecate tfb.masked_autoregressive_default_template.
- Fixed inverse numerical stability bug in `tfb.Softfloor`
- Tape-safe Reshape bijector.

- MCMC
- Optimize tfp.mcmc.ReplicaExchangeMonteCarlo by replacing TF control flow and
- ReplicaExchangeMC now can trace exchange proposals/acceptances.
- Correct implementation of log_accept_ratio in NUTS
- Return non-cumulated leapfrogs_taken in nuts kernel_result.
- Make unrolled NUTS reproducible.
- Bug fix of Generalized U-turn in NUTS.
- Reduce NUTS test flakiness.
- Fix convergence test for NUTS.
- Switch back to original U turn criteria in Hoffman & Gelman 2014.
- Make autobatched NUTS reproducible.

- STS
- Update example "Structural Time Series Modeling Case Studies" to TF2.0 API.
- Add fast path for sampling STS LocalLevel models.
- Support posterior sampling in linear Gaussian state space models.
- Add a fast path for Kalman smoothing with scalar latents.
- Add option to disallow drift in STS Seasonal models.

- Breaking change: Removed a number of functions, methods, and classes that were deprecated in TensorFlow Probability 0.8.0 or earlier.
- Remove deprecated `trainable_distributions_lib`.
- Remove deprecated property Dirichlet.total_concentration.
- Remove deprecated `tfb.AutoregressiveLayer` -- use `tfb.AutoregressiveNetwork`.
- Remove deprecated `tfp.distributions.*` methods.
- Remove deprecated `tfp.distributions.moving_mean_variance`.
- Remove two deprecated `tfp.vi` functions.
- Remove deprecated `tfp.distributions.SeedStream` -- use `tfp.util.SeedStream`.
- Remove deprecated properties of `tfd.Categorical`.

- Other
- Add `make_rank_polymorphic` utility, which lifts a callable to a vectorized callable.
- Dormand-Prince solver supports nested structures. Implemented adjoint sensitivity method for Dormand-Prince solver gradients.
- Run Travis tests against latest tf-estimator-nightly.
- Supporting gast 0.3 +
- Add `tfp.vi.build_factored_surrogate_posterior` utility for automatic black-box variational inference.


Huge thanks to all the contributors to this release!

- Aditya Grover
- Alexey Radul
- Anudhyan Boral
- Arthur Lui
- Billy Lamberta
- Brian Patton
- Christopher Suter
- Colemak
- Dan Moldovan
- Dave Moore
- Dmitrii Kochkov
- Edward Loper
- Emily Fertig
- Ian Langmore
- Jacob Burnim
- Joshua V. Dillon
- Junpeng Lao
- Katherine Wu
- Kibeom Kim
- Kristian Hartikainen
- Mark Daoust
- Pavel Sountsov
- Peter Hawkins
- refraction-ray
- RJ Skerry-Ryan
- Sanket Kamthe
- Sergei Lebedev
- Sharad Vikram
- Srinivas Vasudevan
- Yanhua Sun
- Yash Katariya
- Zachary Nado