Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Bump tensorflow-probability from 0.11.1 to 0.17.0 #30

Closed

Conversation

dependabot[bot]
Copy link

@dependabot dependabot bot commented on behalf of github Jul 1, 2022

Bumps tensorflow-probability from 0.11.1 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

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

Bumps [tensorflow-probability](https://github.com/tensorflow/probability) from 0.11.1 to 0.17.0.
- [Release notes](https://github.com/tensorflow/probability/releases)
- [Commits](tensorflow/probability@v0.11.1...v0.17.0)

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

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot @github
Copy link
Author

dependabot bot commented on behalf of github Jul 1, 2022

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

POST https://api.github.com/repos/kearnsw/rasa/pulls/30/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 kearnsw/rasa repository. // See: https://docs.github.com/rest/reference/pulls#request-reviewers-for-a-pull-request

@dependabot @github
Copy link
Author

dependabot bot commented on behalf of github Jul 1, 2022

The following labels could not be found: type:dependencies.

@dependabot @github
Copy link
Author

dependabot bot commented on behalf of github Oct 1, 2022

Superseded by #34.

@dependabot dependabot bot closed this Oct 1, 2022
@dependabot dependabot bot deleted the dependabot-pip-tensorflow-probability-0.17.0 branch October 1, 2022 13:27
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants