Update tensorflow requirement from <=2.13.1 to <=2.15.0.post1

[dependabot]

Updates the requirements on tensorflow to permit the latest version.

Changelog

Sourced from tensorflow's changelog.

Release 2.15.0.post1

TensorFlow

Bug Fixes and Other Changes

• Hot-fix was needed for an issue affecting the TensorFlow installation process.
  • TensorFlow 2.15.0 Python package was requesting tensorrt-related packages that cannot be found unless the user installs them beforehand or provides additional installation flags.
  • This dependency affected anyone installing TensorFlow 2.15 alongside NVIDIA CUDA dependencies via pip install tensorflow[and-cuda].
  • Depending on the installation method, TensorFlow 2.14 would be installed instead of 2.15, or users could receive an installation error due to those missing dependencies.
• TensorFlow 2.15.0.post1 is being released for Linux x86_64 to resolve this issue as quickly as possible.
  • This version removes the tensorrt Python package dependencies from the tensorflow[and-cuda] installation method to ensure pip install tensorflow[and-cuda] works as originally intended for TensorFlow 2.15.
  • Support for TensorRT is otherwise unaffected as long as TensorRT is already installed on the system.
• Using .post1 instead of a full minor release allowed us to push this release out quickly. However, please note the following caveat:
  • For users wishing to pin their Python dependency in a requirements file or other situation, under Python's version specification rules, tensorflow[and-cuda]==2.15.0 will not install this fixed version. Please use ==2.15.0.post1 to specify this exact version on Linux platforms, or a fuzzy version specification, such as ==2.15.*, to specify the most recent compatible version of TensorFlow 2.15 on all platforms.

Release 2.15.0

TensorFlow

Breaking Changes

• tf.types.experimental.GenericFunction has been renamed to tf.types.experimental.PolymorphicFunction.

Known Caveats

Major Features and Improvements

• oneDNN CPU performance optimizations Windows x64 & x86.

  • Windows x64 & x86 packages:
    • oneDNN optimizations are enabled by default on X86 CPUs

... (truncated)

Commits

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🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

📊 Key Changes

• Updated the maximum version requirement for TensorFlow from 2.13.1 to 2.15.0.post1 in the pyproject.toml file.

🎯 Purpose & Impact

• The purpose of this update is to allow Ultralytics' YOLOv5 to be compatible with newer versions of TensorFlow, potentially providing users with improvements and bug fixes from the latest TensorFlow releases.
• This change opens the door for enhancements that may come with TensorFlow versions between 2.13.1 and 2.15.0.post1, which could include performance optimizations, new features, or security patches.
• Users might experience improved functionality or encounter fewer bugs when using YOLOv5 with TensorFlow.

🌟 Summary

The update expands TensorFlow compatibility for YOLOv5, fostering better performance and stability. 🆙✨

[dependabot]

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.