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Releases: danielward27/flowjax

v16.0.0

17 Oct 10:59
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What's Changed

Breaking changes:

  • Calls to get_ravelled_pytree_constructor will now need to explicitly pass the *args and **kwargs for partitioning parameters (usually setting is_leaf=lambda leaf: isinstance(leaf, wrappers.NonTrainable).
  • fit_to_data now returns list of floats, rather than than a list of scalar arrays.

Note, fit_to_variational_target will be deprecated in the next version. This version adds its replacement fit_to_key_based_loss. This was primarily because of some defaults which were "bad", e.g. steps: int = 100, and return_best=True (see #188 for details). It also generalizes the name, as it can be used to fit any pytree, and doesn't have to be used with a variational inference loss function.

Full Changelog: v15.1.0...v16.0.0

v15.1.0

07 Oct 12:17
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Full Changelog: v15.0.0...v15.1.0

v15.0.0

17 Sep 20:00
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Breaking changes:

  • Users must switch from old style PRNGKey arrays to new style ones (replacing jax.random.PRNGKey with jax.random.key . The old keys will be deprecated in JAX.
  • LogNormal is now a Exp transformed Normal, which is an implementation detail, unless you previously relied on log_normal.base_dist or log_normal.bijection.
  • recursive_unwrap was removed, as alone it didn't provide additional functionality.

What's Changed

Full Changelog: v14.0.0...v15.0.0

v14.0.0

02 Sep 17:40
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I was not happy with the original implementation of some wrappers in flowjax.wrappers, e.g. BijectionReparam introduced some (avoidable, but untidy) circular dependency issues. We now primarily use Parameterize a new name for what was Lambda. This introduces some breaking changes, primarily the aformentioned renaming, in addition to the removal of BijectionReparam and Where . See the pull request for more information.

Full Changelog: v13.1.1...v14.0.0

v13.1.1

29 Aug 13:24
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v13.1.0

29 Aug 10:08
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Full Changelog: v13.0.1...v13.1.0

Thanks for the help @weiyaw!

v13.0.1

24 Jul 14:52
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New release to trigger update to docs.

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v13.0.0

24 Jul 14:22
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Some small breaking changes:

  • The interval attribute of RationalQuadraticSpline is now a two-tuple with type tuple[float | int, float | int], representing the upper and lower bound of the spline. Previously, the interval was a float | int, forcing the interval to be symmetric about 0.
  • Any custom loss functions used with fit_to_data now should accept a key (whether or not it is used), having signature loss(params, static, x, condition, key), for consistency of API.

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Full Changelog: v12.4.0...v13.0.0

v12.4.0

21 Jun 17:29
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Full Changelog: v12.3.0...v12.4.0

v12.3.0

06 Jun 11:59
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The main thing of note is a bug fix to ContrastiveLoss (see #164). Apologies for any inconvenience!

  • Fix bug in ContrastiveLoss normalization and add improve numpyro transformed wrapper by @danielward27 in #164

Full Changelog: v12.2.0...v12.3.0