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Bump jax from 0.2.5 to 0.2.25#255

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Bump jax from 0.2.5 to 0.2.25#255
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@dependabot dependabot Bot commented on behalf of github Nov 11, 2021

Bumps jax from 0.2.5 to 0.2.25.

Release notes

Sourced from jax's releases.

JAX release v0.2.25

  • New features:

    • (Experimental) jax.distributed.initialize exposes multi-host GPU backend.
    • jax.random.permutation supports new independent keyword argument ({jax-issue}[#8430](https://github.com/google/jax/issues/8430))
  • Breaking changes

    • Moved jax.experimental.stax to jax.example_libraries.stax
    • Moved jax.experimental.optimizers to jax.example_libraries.optimizers
  • New features:

    • Added jax.lax.linalg.qdwh.

Jax release v0.2.24

  • New features:
    • jax.random.choice and jax.random.permutation now support multidimensional arrays and an optional axis argument (#8158)
  • Breaking changes:
    • jax.numpy.take and jax.numpy.take_along_axis now require array-like inputs (see #7737)

Jax release v0.2.21

  • New features:

    • Added jax.numpy.insert implementation (#7936 ).
  • Breaking Changes

    • jax.api has been removed. Functions that were available as jax.api.* were aliases for functions in jax.*; please use the functions in jax.* instead.
    • jax.partial, jax.lax.partial, and jax.util.partial were accidental exports that have now been removed. Use functools.partial from the Python standard library instead.
    • Boolean scalar indices now raise a TypeError; previously this silently returned wrong results (#7925 ).
    • Many more jax.numpy functions now require array-like inputs, and will error if passed a list (#7747 #7802 #7907 ). See #7737 for a discussion of the rationale behind this change.
    • When inside a transformation such as jax.jit, jax.numpy.array always stages the array it produces into the traced computation. Previously jax.numpy.array would sometimes produce a on-device array, even under a jax.jit decorator. This change may break code that used JAX arrays to perform shape or index computations that must be known statically; the workaround is to perform such computations using classic NumPy arrays instead.
    • jnp.ndarray is now a true base-class for JAX arrays. In particular, this means that for a standard numpy array x, isinstance(x, jnp.ndarray) will now return False (#7927).

Jax release v0.2.20

No release notes provided.

Changelog

Sourced from jax's changelog.

jax 0.2.25 (Nov 10, 2021)

  • GitHub commits.

  • New features:

    • (Experimental) jax.distributed.initialize exposes multi-host GPU backend.
    • jax.random.permutation supports new independent keyword argument ({jax-issue}[#8430](https://github.com/google/jax/issues/8430))
  • Breaking changes

    • Moved jax.experimental.stax to jax.example_libraries.stax
    • Moved jax.experimental.optimizers to jax.example_libraries.optimizers
  • New features:

    • Added jax.lax.linalg.qdwh.

jax 0.2.24 (Oct 19, 2021)

  • GitHub commits.

  • New features:

    • jax.random.choice and jax.random.permutation now support multidimensional arrays and an optional axis argument ({jax-issue}[#8158](https://github.com/google/jax/issues/8158))
  • Breaking changes:

    • jax.numpy.take and jax.numpy.take_along_axis now require array-like inputs (see {jax-issue}[#7737](https://github.com/google/jax/issues/7737))

jaxlib 0.1.73 (Oct 18, 2021)

  • Multiple cuDNN versions are now supported for jaxlib GPU cuda11 wheels.

    • cuDNN 8.2 or newer. We recommend using the cuDNN 8.2 wheel if your cuDNN installation is new enough, since it supports additional functionality.
    • cuDNN 8.0.5 or newer.
  • Breaking changes:

    • The install commands for GPU jaxlib are as follows:

      pip install --upgrade pip
      Installs the wheel compatible with CUDA 11 and cuDNN 8.2 or newer.
      pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_releases.html
      Installs the wheel compatible with Cuda 11 and cudnn 8.2 or newer.
      pip install jax[cuda11_cudnn82] -f https://storage.googleapis.com/jax-releases/jax_releases.html
      Installs the wheel compatible with Cuda 11 and cudnn 8.0.5 or newer.
      pip install jax[cuda11_cudnn805] -f https://storage.googleapis.com/jax-releases/jax_releases.html

jax 0.2.22 (Oct 12, 2021)

... (truncated)

Commits
  • 821fcaa Make the pjit docs clear about who does local and global communication
  • 0f47712 Implements a lowering function for tf.expm1 and adds tests.
  • 66009d6 Merge pull request #8331 from jakevdp:odeint-args
  • beb473d Merge pull request #8320 from jakevdp:hist-density
  • ca4e430 Merge pull request #8332 from jakevdp:bcoo-block
  • 3338947 odeint: args validation allows pytrees
  • 11127ad [JAX] Replace users of deprecated jax.lib.xla_bridge functions with more publ...
  • 20062e5 [sparse] add .block_until_ready() to sparse objects
  • 7a5e843 Internal change
  • bc1c6b1 [JAX] Fix sphinx formatting issue
  • Additional commits viewable in compare view

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Bumps [jax](https://github.com/google/jax) from 0.2.5 to 0.2.25.
- [Release notes](https://github.com/google/jax/releases)
- [Changelog](https://github.com/google/jax/blob/main/CHANGELOG.md)
- [Commits](jax-ml/jax@jax-v0.2.5...jax-v0.2.25)

---
updated-dependencies:
- dependency-name: jax
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added the dependencies Pull requests that update a dependency file label Nov 11, 2021
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dependabot Bot commented on behalf of github Dec 9, 2021

Superseded by #266.

@dependabot dependabot Bot closed this Dec 9, 2021
@dependabot dependabot Bot deleted the dependabot/pip/jax-0.2.25 branch December 9, 2021 05:04
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