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Update jax requirement from <0.2.20,>0.2.16 to >0.2.16,<0.2.21

Created by: dependabot[bot]

Updates the requirements on jax to permit the latest version.

Changelog

Sourced from jax's changelog.

jax 0.2.20 (Sept 2, 2021)

  • GitHub commits.
  • Breaking Changes
    • jnp.poly* functions now require array-like inputs ({jax-issue}[#7732](https://github.com/google/jax/issues/7732))
    • jnp.unique and other set-like operations now require array-like inputs ({jax-issue}[#7662](https://github.com/google/jax/issues/7662))

jaxlib 0.1.71 (Sep 1, 2021)

  • Breaking changes:
    • Support for CUDA 11.0 and CUDA 10.1 has been dropped. Jaxlib now supports CUDA 10.2 and CUDA 11.1+.

jax 0.2.19 (Aug 12, 2021)

  • GitHub commits.
  • Breaking changes:
    • Support for NumPy 1.17 has been dropped, per the deprecation policy. Please upgrade to a supported NumPy version.

    • The jit decorator has been added around the implementation of a number of operators on JAX arrays. This speeds up dispatch times for common operators such as +.

      This change should largely be transparent to most users. However, there is one known behavioral change, which is that large integer constants may now produce an error when passed directly to a JAX operator (e.g., x + 2**40). The workaround is to cast the constant to an explicit type (e.g., np.float64(2**40)).

  • New features:
    • Improved the support for shape polymorphism in jax2tf for operations that need to use a dimension size in array computation, e.g., jnp.mean. ({jax-issue}[#7317](https://github.com/google/jax/issues/7317))
  • Bug fixes:
    • Some leaked trace errors from the previous release ({jax-issue}[#7613](https://github.com/google/jax/issues/7613))

jaxlib 0.1.70 (Aug 9, 2021)

  • Breaking changes:
    • Support for Python 3.6 has been dropped, per the deprecation policy. Please upgrade to a supported Python version.

    • Support for NumPy 1.17 has been dropped, per the deprecation policy. Please upgrade to a supported NumPy version.

    • The host_callback mechanism now uses one thread per local device for making the calls to the Python callbacks. Previously there was a single thread for all devices. This means that the callbacks may now be called interleaved. The callbacks corresponding to one device will still be called in sequence.

... (truncated)

Commits
  • a7b61c0 Merge pull request #7793 from yashk2810:update_pypi
  • 19d7710 Remove the last long running CI build from github actions which is being repl...
  • d4d5bc4 Merge pull request #7798 from jakevdp:fix-sparse-doc
  • 20a0bb4 DOC: fix formatting
  • aed5137 Merge pull request #7792 from jakevdp:sparse-doc
  • 5dba8cf Merge pull request #7781 from sharadmv:while-batching
  • e78511f Merge pull request #7794 from google:dce-fix
  • d693324 change while loop batching fixed point condition
  • 82a7b7e DOC: add documentation of jax.experimental.sparse
  • 7fbbb95 Merge pull request #7779 from jakevdp:bcoo-reordering
  • Additional commits viewable in compare view

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