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Update dependency tensorflow to ~2.16.0 #729

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This PR contains the following updates:

Package Change Age Adoption Passing Confidence
tensorflow ~2.8 -> ~2.16.0 age adoption passing confidence

Configuration

πŸ“… Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).

🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.

β™» Rebasing: Never, or you tick the rebase/retry checkbox.

πŸ”• Ignore: Close this PR and you won't be reminded about this update again.


  • If you want to rebase/retry this PR, check this box

This PR has been generated by Mend Renovate. View repository job log here.

@forking-renovate forking-renovate bot added the dependencies Dependency changes and updates label Mar 10, 2024
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⚠ Artifact update problem

Renovate failed to update an artifact related to this branch. You probably do not want to merge this PR as-is.

β™» Renovate will retry this branch, including artifacts, only when one of the following happens:

  • any of the package files in this branch needs updating, or
  • the branch becomes conflicted, or
  • you click the rebase/retry checkbox if found above, or
  • you rename this PR's title to start with "rebase!" to trigger it manually

The artifact failure details are included below:

File name: poetry.lock
Creating virtualenv cloud-datasets-02SzFaNK-py3.8 in /home/ubuntu/.cache/pypoetry/virtualenvs
Updating dependencies
Resolving dependencies...


The current project's Python requirement (3.8.12) is not compatible with some of the required packages Python requirement:
  - tensorflow requires Python >=3.9, so it will not be satisfied for Python 3.8.12

Because no versions of tensorflow match >=2.16.0,<2.16.1 || >2.16.1,<2.17.0
 and tensorflow (2.16.1) requires Python >=3.9, tensorflow is forbidden.
So, because cloud-datasets depends on tensorflow (~2.16.0), version solving failed.

  β€’ Check your dependencies Python requirement: The Python requirement can be specified via the `python` or `markers` properties
    
    For tensorflow, a possible solution would be to set the `python` property to "<empty>"

    https://python-poetry.org/docs/dependency-specification/#python-restricted-dependencies,
    https://python-poetry.org/docs/dependency-specification/#using-environment-markers

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