Bump tensorflow-probability from 0.11.1 to 0.12.1

[dependabot]

Bumps tensorflow-probability from 0.11.1 to 0.12.1.

Release notes

Sourced from tensorflow-probability's releases.

TensorFlow Probability 0.12.1

Release notes

This is the 0.12.1 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.4.0.

Change notes

NOTE: Links point to examples in the TFP 0.12.1 release Colab.

Bijectors:

• Add implementation of GLOW at tfp.bijectors.Glow.
• Add RayleighCDF bijector.
• Add Ascending bijector and deprecate Ordered.
• Add optional low parameter to the Softplus bijector.
• Enable ScaleMatvecLinearOperator bijector to wrap blockwise LinearOperators to form a multipart bijectors.
• Allow passing kwargs to Blockwise.
• Bijectors now share a global cache, keyed by the bijector parameters and the value being transformed.

Distributions:

• BREAKING: Remove deprecated HiddenMarkovModel.num_states property.
• BREAKING: Change the naming scheme of un-named variables in JointDistributions.
• BREAKING: Remove deprecated batch_shape and event_shape arguments of TransformedDistribution.
• Add Skellam distribution.
• JointDistributionCoroutine{AutoBatched} now uses namedtuples as the sample dtype.
• von-Mises Fisher distribution now works for dimensions > 5 and implements VonMisesFisher.entropy.
• Add ExpGamma and ExpInverseGamma distributions.
• JointDistribution*AutoBatched now support (reproducible) tensor seeds.
• Add KL(VonMisesFisher || SphericalUniform).
• Added Distribution.parameter_properties method.
• experimental_default_event_space_bijector now accepts additional arguments to pin some distribution parts.
• Add JointDistribution.experimental_pin and JointDistributionPinned.
• Add NegativeBinomial.experimental_from_mean_dispersion method.
• Add tfp.experimental.distribute, with DistributionStrategy-aware distributions that support cross-device likelihood computations.
• HiddenMarkovModel can now accept time varying observation distributions if time_varying_observation_distribution is set.
• Beta, Binomial, and NegativeBinomial CDF no longer returns nan outside the support.
• Remove the "dynamic graph" code path from the Mixture sampler. (Mixture now ignores the use_static_graph parameter.)
• Mixture now computes standard deviations more accurately and robustly.
• Fix incorrect nan samples generated by several distributions.
• Fix KL divergence between Categorical distributions when logits contain -inf.
• Implement Bernoulli.cdf.
• Add a log_rate parameter to tfd.Gamma.
• Add option for parallel filtering and sampling to LinearGaussianStateSpaceModel.

MCMC:

• Add tfp.experimental.mcmc.ProgressBarReducer.

... (truncated)

Commits

• 43a9d6c Merge pull request #1205 from jburnim/r0.12
• c1818a8 Set the version for the TFP 0.12.1 release.
• 0c282ef Avoid cache errors when user-written Bijectors don't pass parameters.
• dcd59ed Merge pull request #1199 from jburnim/r0.12
• 90fa3f0 Set the version for the TFP 0.12.0 release.
• ead8501 internal change
• 1cc5c39 Allow 0 concentration in gamma samplers.
• 5f0dbec Add float64 support to PHMC.
• d3bf5a0 Rewrite experimental sample_chain in terms of run_kernel.
• e7d64b7 Add a default bijector to the Deterministic distributions.
• Additional commits viewable in compare view

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[dependabot]

Dependabot tried to add @alwx as a reviewer to this PR, but received the following error from GitHub:

POST https://api.github.com/repos/neo-alex/rasa/pulls/2/requested_reviewers: 422 - Reviews may only be requested from collaborators. One or more of the users or teams you specified is not a collaborator of the neo-alex/rasa repository. // See: https://docs.github.com/rest/reference/pulls#request-reviewers-for-a-pull-request

[dependabot]

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[dependabot]

Superseded by #19.