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)

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🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Updated TensorFlow version constraint in pyproject.toml for Ultralytics YOLOv3 repository.

📊 Key Changes

• TensorFlow version upper limit changed from <=2.13.1 to <=2.15.0.post1.

🎯 Purpose & Impact

• 🚀 Purpose: To enable the use of a newer TensorFlow version with YOLOv3, presumably after confirming compatibility or resolving earlier issues.
• ✅ Impact: Users can now leverage improvements and bug fixes from newer TensorFlow releases, potentially enhancing model performance or providing access to newer features.