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[tune](deps): Bump tensorflow-probability from 0.14.0 to 0.17.0 in /python/requirements/ml #132

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@dependabot dependabot bot commented on behalf of github Jun 11, 2022

Bumps tensorflow-probability from 0.14.0 to 0.17.0.

Release notes

Sourced from tensorflow-probability's releases.

TensorFlow Probability 0.17.0

Release notes

This is the 0.17.0 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.9.1 and JAX 0.3.13 .

Change notes

  • Distributions

    • Discrete distributions transform correctly when a bijector is applied.
    • Fix bug in Taylor approximation of log-normalizing constant for the ContinuousBernoulli.
    • Add TwoPieceNormal distribution and reparameterize it's samples.
    • Make IncrementLogProb a proper tfd.Distribution.
    • Add quantiles to Empirical distribution.
    • Add tfp.experimental.distributions.MultiTaskGaussianProcessRegressionModel
    • Improve efficiency of MultiTaskGaussian Processes in the presence of observation noise: Reduce complexity from O((NT)^3) to O(N^3 + T^3) where N is the number of data points and T is the number of tasks.
    • Improve efficiency of VariationalGaussianProcess.
    • Add tfd.LognNormal.experimental_from_mean_variance.
  • Bijectors

    • Fix Softfloor bijector to act as the identity at high temperature, and floor at low temperature.
    • Remove tfb.Ordered bijector and finite_nondiscrete flags in Distributions.
  • Math

    • Add tfp.math.betainc and gradients with respect to all parameters.
  • STS

    • Several bug fixes and performance improvements to tfp.experimental.sts_gibbs for Gibbs sampling Bayesian structural time series models with sparse linear regression.
    • Enable tfp.experimental.sts_gibbs under JAX
  • Experimental

    • Ensemble Kalman filter is now efficient in the case of ensemble size << observation size and an "easy to invert" modeled observation covariance.
    • Add a perturbed_observations option to ensemble_kalman_filter_log_marginal_likelihood.
    • Add Experimental support for custom JAX PRNGs.
  • Other

    • Add assertAllMeansClose to tfp.TestCase for testing sampling code.

Huge thanks to all the contributors to this release!

  • Adam Sorrenti
  • Alexey Radul

... (truncated)

Commits
  • e3d67c0 Update version for the TFP 0.17.0 release.
  • bfe7d2b Revert "Fix TensorFlow checkpoint and trackable imports."
  • 6d04325 Increase tolerance in LinearOperatorUnitaryTest.test_solve.
  • 5172cc7 Merge pull request #1569 from ryanrussell:main
  • 6685d04 Merge pull request #1573 from RenuPatelGoogle:patch-1
  • b689df6 Add holidays as a test dependency for TFP.
  • 8e72c11 Fix failure in windowed_sampling_test.jax in OSS.
  • 9cdc4ee Fixed few code lines in this API example
  • f8107c1 DOCFIX: Correct Markov state distribution notation in EnKF. The distributions...
  • 0a10dd4 Fix TensorFlow checkpoint and trackable imports.
  • Additional commits viewable in compare view

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Jun 11, 2022
Bumps [tensorflow-probability](https://github.com/tensorflow/probability) from 0.14.0 to 0.17.0.
- [Release notes](https://github.com/tensorflow/probability/releases)
- [Commits](tensorflow/probability@v0.14.0...v0.17.0)

---
updated-dependencies:
- dependency-name: tensorflow-probability
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot force-pushed the dependabot/pip/python/requirements/ml/tensorflow-probability-0.17.0 branch from 85655dd to 9fc82b1 Compare June 17, 2022 21:51
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