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.
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Bumps jaxlib from 0.1.61 to 0.1.74.
Changelog
Sourced from jaxlib's changelog.
... (truncated)
Commits
b53a174
Merge pull request #8564 from hawkinsp:testfix9e09b51
Merge pull request #8381 from LenaMartens:changelist/4053995816883571
Merge pull request #8561 from mattjj:add-donated-invars-to-xlacomputatione14fea3
Overload jnp ops which are polymorphic to an array's value and support PRNGKeys.1bcedd5
Fix test failures and update changelog.5d35b8a
add donated_invars to xla.XlaComputationb7e3129
Merge pull request #8562 from hawkinsp:jaxliba864c95
Update XLA.9491414
Merge pull request #8499 from jakevdp:load-wrapper1137aa1
Properly handle bfloat16 in jnp.load()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
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