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Releases: google-deepmind/distrax

Distrax 0.1.43

21 Nov 11:13
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Distrax 0.1.43 Pre-release
Pre-release
Install dependencies before running version checks in the release wor…

…kflow.

PiperOrigin-RevId: 584269456

Distrax 0.1.42

20 Nov 21:48
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Distrax 0.1.42 Pre-release
Pre-release
Install dependencies before running version checks in the release wor…

…kflow.

PiperOrigin-RevId: 584269456

Distrax 0.1.41

20 Nov 15:24
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Distrax 0.1.41 Pre-release
Pre-release

What's Changed

  • Remove references to deprecated jax aliases by @copybara-service in #243
  • Add log_survival_function for Laplace distribution. by @copybara-service in #251

Full Changelog: v0.1.4...v0.1.

Distrax 0.1.5

21 Nov 12:38
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What's Changed

  • Remove references to deprecated jax aliases by @copybara-service in #243
  • Add log_survival_function for Laplace distribution. by @copybara-service in #251

Full Changelog: v0.1.4...v0.1.5

Distrax 0.1.4

29 Jun 14:16
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What's Changed

  • Update categorical.py by @cyprienc in #236
  • Drop python 3.7 and 3.8

New Contributors

Full Changelog: v0.1.3...v0.1.4

Version v0.1.3

14 Feb 11:02
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What's Changed

  • Adjust tolerance in gumbel_test.py. by @copybara-service in #135
  • Add an abstract class for linear bijectors. by @copybara-service in #136
  • Expose linear bijectors, shift bijector, and general multivariate normal. by @copybara-service in #138
  • Add missing symbols in all and put list in alphabetical order. by @copybara-service in #139
  • Added log_cdf method for the Gamma distribution and modified some tests in gamma_test.py. by @copybara-service in #141
  • Fix test_convert_seed. by @copybara-service in #142
  • Implement the Beta distribution. by @copybara-service in #140
  • Migrate RLax squashed gaussian to use Distrax. Explicitly broadcast shapes in Distrax scalar affine to avoid rank promotion errors. by @copybara-service in #143
  • Remove randomness in laplace_test.py. by @copybara-service in #144
  • Implement the Dirichlet distribution. by @copybara-service in #146
  • Add survival and log-survival function to distrax.Distribution base class. by @copybara-service in #148
  • Implement survival and log-survival function for the Logistic distribution. by @copybara-service in #150
  • Implement survival and log-survival function for the Normal distribution. by @copybara-service in #151
  • Raise ValueError when input parameters are not valid for Bernoulli, Multinomial, and Categorical. by @copybara-service in #153
  • Remove RTOL from all distribution tests. by @copybara-service in #152
  • Documentation changes to LogStddevNormal. by @copybara-service in #154
  • Improve numerical stability of prob/log_prob computation of distributions.Quantized. by @copybara-service in #149
  • Improve the tests in beta_test.py. by @copybara-service in #156
  • Remove the median of the Bernoulli distribution. by @copybara-service in #157
  • Change tolerance of sample stddev test in bertnoulli_test.py. by @copybara-service in #160
  • Delete references to removed jax.core attributes. by @copybara-service in #166
  • Update .pylintrc by @copybara-service in #170
  • Add the von Mises distribution to distrax. by @copybara-service in #169
  • Allow Distribution to work with ArrayTree events. by @copybara-service in #175
  • Explicitly separate JAX and non-JAX data during Jittable serialization. by @copybara-service in #177
  • Add PyPI badge showing the latest released version. by @copybara-service in #179
  • Add vmap support for Categorical, Normal, and Independent. by @copybara-service in #180
  • Use jax.tree_util.$tree_fn instead of deprecated jax.$tree_fn alias. by @copybara-service in #181
  • Compare with slightly less numerical precision. by @copybara-service in #183
  • Avoid NaN gradients from Categorical KL and entropy. by @copybara-service in #190
  • Add categorical-uniform distribution. by @copybara-service in #199
  • Add categorical-uniform distribution. by @copybara-service in #205
  • Add clipped distributions to distrax. by @copybara-service in #210
  • Lower the requirements to test the VonMises distribution. by @copybara-service in #217
  • Increase tolerance of test in gumbel_test.py. by @copybara-service in #221
  • Prepare inverse transformation for JAX jit==pjit migration. by @copybara-service in #223
  • Fix TypeErrors for python < 3.10. Fixes #224. by @copybara-service in #225

Full Changelog: v0.1.2...v0.1.3

Distrax 0.1.2

25 Mar 15:03
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What's Changed

  • Implement TFP's base measure interface for distrax distributions and bijectors. by @copybara-service in #104
  • Add a matrix property to affine bijectors that returns a matrix representing their linear part. by @copybara-service in #114
  • Fix categorical KL computation when the second distribution has zero probability on entries where the first distribution also has zero probability. by @copybara-service in #113
  • Implement the DiagAffine bijector. by @copybara-service in #115
  • Implement the MultivariateNormalFromBijector distribution. by @copybara-service in #116
  • Implement the MultivariateNormalDiag distribution as an instance of a MultivariateNormalFromBijector. by @copybara-service in #117
  • Implement the MultivariateNormalTri distribution. by @copybara-service in #118
  • Implement the MultivariateNormalDiagPlusLowRank distribution. by @copybara-service in #119
  • Add tests for KL computations between different Multivariate Gaussian distributions. by @copybara-service in #123
  • Demote TriangularAffine to TriangularLinear. by @copybara-service in #125
  • Add tests for same_as method to increase test coverage. by @copybara-service in #126
  • Demote DiagAffine to DiagLinear. by @copybara-service in #127
  • Demote DiagPlusLowRankAffine to DiagPlusLowRankLinear. by @copybara-service in #128
  • Updated 2-distributions tests for the MultivariateNormalDiagPlusLowRank. by @copybara-service in #131
  • Adjust test tolerances. by @copybara-service in #133
  • Expose the full-covariance multivariate normal distributions, and upgrade version. by @copybara-service in #134

Full Changelog: v0.1.1...v0.1.2

Distrax 0.1.1

25 Feb 14:19
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What's Changed

  • Add an absolute tolerance in multinomial_test to unblock an XLA optimization. by @copybara-service in #74
  • Change the default dtype of discrete distributions to unqualified int. by @copybara-service in #77
  • Add a straight-through gradient wrapper method. by @copybara-service in #70
  • Expose straight_through_wrapper. by @copybara-service in #82
  • Update Distrax citation. by @copybara-service in #83
  • Ensure forward compatibility with Chex. by @copybara-service in #84
  • Relax test tolerances in multinomial_test. by @copybara-service in #85
  • Update requirements and allow new versions of JAX. by @copybara-service in #87
  • Implement a triangular affine bijector, with tests. by @copybara-service in #88
  • Implement LowerUpperTriangularAffine as a composition of two TriangularAffines. by @copybara-service in #89
  • Reduce testing time by disabling JAX optimizations. by @copybara-service in #94
  • Remove the old venv directory before testing the package. by @copybara-service in #95
  • Initial Gumbel distribution and bijector. by @kashif in #36
  • Add the Gumbel distribution. by @copybara-service in #96
  • Delete unnecessary cdf definition. by @copybara-service in #98
  • Update the tests for the Tanh and Sigmoid bijectors. by @copybara-service in #97
  • Delete stale "pylint: disable". by @copybara-service in #99
  • Added the GumbelCDF bijector originally developed in #36. by @copybara-service in #100
  • Add an affine bijector whose weight matrix is a low-rank perturbation of a diagonal matrix. by @copybara-service in #90
  • Perform validity checking of probability distribution when sampling from Categorical / OneHotCategorical, and return -1 instead of an invalid sample if normalized probability distribution is invalid. by @copybara-service in #105
  • Use a safer log_prob in KL divergence between categoricals. by @copybara-service in #102
  • Clarify behaviour of the Transformed distribution in the docstring. by @copybara-service in #109

Full Changelog: v0.1.0...v0.1.1

Distrax 0.1.0

18 Nov 18:11
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Support for Python 3.6 has been dropped as per JAX deprecation policy. Please upgrade to a supported Python version.

Distrax 0.0.3

18 Nov 16:18
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It is the latest version compatible with Python 3.6. See deepmind/optax#222 for more details.

Full Changelog

Closed issues:

  • ImportError: cannot import name 'partial' from 'jax.util' #60
  • Problem with shapes in simple transformed distributions #42
  • Issue with jax version in requirements.txt #38
  • Duplication/Forking vs Collaboration #35
  • Tanh numerical instability #7

Merged pull requests:

* This Changelog was automatically generated by github_changelog_generator