Update tensorflow requirement from <=2.13.1 to <=2.16.1

[dependabot]

Updates the requirements on tensorflow to permit the latest version.

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.16.1

Release 2.16.1

TensorFlow

• TensorFlow Windows Build:
  • Clang is now the default compiler to build TensorFlow CPU wheels on the Windows Platform starting with this release. The currently supported version is LLVM/clang 17. The official Wheels-published on PyPI will be based on Clang; however, users retain the option to build wheels using the MSVC compiler following the steps mentioned in https://www.tensorflow.org/install/source_windows as has been the case before
• TensorFlow 2.16 will be released as TF 2.16.1 (instead of 2.16.0). The patch release will be done as 2.16.2 during the next release cycle.

Breaking Changes

• tf.summary.trace_on now takes a profiler_outdir argument. This must be set if profiler arg is set to True.

  • tf.summary.trace_export's profiler_outdir arg is now a no-op. Enabling the profiler now requires setting profiler_outdir in trace_on.

• tf.estimator

  • The tf.estimator API is removed.
  • To continue using tf.estimator, you will need to use TF 2.15 or an earlier version.

• Keras 3.0 will be the default Keras version. You may need to update your script to use Keras 3.0.

• Please refer to the new Keras documentation for Keras 3.0 (https://keras.io/keras_3).

• To continue using Keras 2.0, do the following.

• 1. Install tf-keras via pip install tf-keras~=2.16

  2. To switch tf.keras to use Keras 2 (tf-keras), set the environment variable TF_USE_LEGACY_KERAS=1 directly or in your python program with import os;os.environ["TF_USE_LEGACY_KERAS"]="1". Please note that this will set it for all packages in your Python runtime program

  3. Change the keras import: replace import tensorflow.keras as keras or import keras with import tf_keras as keras. Update any tf.keras references to keras.

• Apple Silicon users: If you previously installed TensorFlow using pip install tensorflow-macos, please update your installation method. Use pip install tensorflow from now on.

• Mac x86 users: Mac x86 builds are being deprecated and will no longer be released as a Pip package from TF 2.17 onwards.

Known Caveats

• Full aarch64 Linux and Arm64 macOS wheels are now published to the tensorflow pypi repository and no longer redirect to a separate package.

Major Features and Improvements

• Support for Python 3.12 has been added.
• tensorflow-tpu package is now available for easier TPU based installs.
• TensorFlow pip packages are now built with CUDA 12.3 and cuDNN 8.9.7
• Added experimental support for float16 auto-mixed precision using the new AMX-FP16 instruction set on X86 CPUs.

Bug Fixes and Other Changes

• tf.lite

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.16.1

TensorFlow

• TensorFlow Windows Build:
  • Clang is now the default compiler to build TensorFlow CPU wheels on the Windows Platform starting with this release. The currently supported version is LLVM/clang 17. The official Wheels-published on PyPI will be based on Clang; however, users retain the option to build wheels using the MSVC compiler following the steps mentioned in https://www.tensorflow.org/install/source_windows as has been the case before
• TensorFlow 2.16 will be released as TF 2.16.1 (instead of 2.16.0). The patch release will be done as 2.16.2 during the next release cycle.

Breaking Changes

• tf.summary.trace_on now takes a profiler_outdir argument. This must be set if profiler arg is set to True.

  • tf.summary.trace_export's profiler_outdir arg is now a no-op. Enabling the profiler now requires setting profiler_outdir in trace_on.

• tf.estimator

  • The tf.estimator API is removed.
  • To continue using tf.estimator, you will need to use TF 2.15 or an earlier version.

• Keras 3.0 will be the default Keras version. You may need to update your script to use Keras 3.0.

• Please refer to the new Keras documentation for Keras 3.0 (https://keras.io/keras_3).

• To continue using Keras 2.0, do the following.

• 1. Install tf-keras via pip install tf-keras~=2.16

  2. To switch tf.keras to use Keras 2 (tf-keras), set the environment variable TF_USE_LEGACY_KERAS=1 directly or in your python program with import os;os.environ["TF_USE_LEGACY_KERAS"]="1". Please note that this will set it for all packages in your Python runtime program

  3. Change the keras import: replace import tensorflow.keras as keras or import keras with import tf_keras as keras. Update any tf.keras references to keras.

• Apple Silicon users: If you previously installed TensorFlow using pip install tensorflow-macos, please update your installation method. Use pip install tensorflow from now on.

• Mac x86 users: Mac x86 builds are being deprecated and will no longer be released as a Pip package from TF 2.17 onwards.

Known Caveats

• Full aarch64 Linux and Arm64 macOS wheels are now published to the tensorflow pypi repository and no longer redirect to a separate package.

Major Features and Improvements

• Support for Python 3.12 has been added.
• tensorflow-tpu package is now available for easier TPU based installs.
• TensorFlow pip packages are now built with CUDA 12.3 and cuDNN 8.9.7
• Added experimental support for float16 auto-mixed precision using the new AMX-FP16 instruction set on X86 CPUs.

Bug Fixes and Other Changes

• tf.lite
  • Added support for stablehlo.gather.

... (truncated)

Commits

• 5bc9d26 Merge pull request #63073 from Intel-tensorflow/kanvi/update-release-notes
• 086d2cc Merge pull request #63127 from rtg0795/r2.16
• 82cdec2 Update RELEASE.md
• 563129d Merge pull request #63120 from tensorflow/MarkDaoust-2.16-release-notes
• 152a11b Merge branch 'r2.16' into MarkDaoust-2.16-release-notes
• 1196a06 Merge pull request #63121 from tensorflow-jenkins/version-numbers-2.16.1-25649
• 46faa44 Update release notes for TensorFlow 2.16.1 (#63117)
• 5fdacf3 Merge pull request #63119 from tensorflow/patch-r2.16-release-notes
• 887bcc9 Update version numbers to 2.16.1
• f1b3d80 Fix formatting.
• Additional commits viewable in compare view

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🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Updated TensorFlow version constraint in YOLOv5 project dependencies.

📊 Key Changes

• TensorFlow version constraint changed from <=2.13.1 to <=2.16.1.

🎯 Purpose & Impact

• Purpose: This change aims to address a specific TensorFlow bug referenced in the Ultralytics GitHub issue. By updating the version constraint, the project ensures compatibility with newer TensorFlow versions that likely include bug fixes and performance improvements.
• Impact: Users can now use YOLOv5 with TensorFlow versions up to 2.16.1, potentially leading to enhanced model performance and stability in deployments. This update is essential for keeping the project up-to-date with TensorFlow's ecosystem, benefiting both expert developers and users integrating YOLOv5 into their applications.🚀