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MatteoH2O1999 / alphaPoke

A pokémon showdown battle-bot project based on reinforcement learning techniques.
GNU General Public License v3.0
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fix(deps): bump the tensorflow group with 2 updates #98

Closed dependabot[bot] closed 9 months ago

dependabot[bot] commented 10 months ago

Bumps the tensorflow group with 2 updates: tensorflow-cpu and tf-agents.

Updates tensorflow-cpu from 2.14.0 to 2.15.0.post1

Release notes

Sourced from tensorflow-cpu's releases.

TensorFlow 2.15.0

Release 2.15.0

TensorFlow

Breaking Changes

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

Major Features and Improvements

  • oneDNN CPU performance optimizations Windows x64 & x86.

    • Windows x64 & x86 packages:
      • oneDNN optimizations are enabled by default on X86 CPUs
    • To explicitly enable or disable oneDNN optimizations, set the environment variable TF_ENABLE_ONEDNN_OPTS to 1 (enable) or 0 (disable) before running TensorFlow. To fall back to default settings, unset the environment variable.
    • oneDNN optimizations can yield slightly different numerical results compared to when oneDNN optimizations are disabled due to floating-point round-off errors from different computation approaches and orders.
    • To verify if oneDNN optimizations are on, look for a message with "oneDNN custom operations are on" in the log. If the exact phrase is not there, it means they are off.

  • Making the tf.function type system fully available:

    • tf.types.experimental.TraceType now allows custom tf.function inputs to declare Tensor decomposition and type casting support.
    • Introducing tf.types.experimental.FunctionType as the comprehensive representation of the signature of tf.function callables. It can be accessed through the function_type property of tf.functions and ConcreteFunctions. See the tf.types.experimental.FunctionType documentation for more details.

  • Introducing tf.types.experimental.AtomicFunction as the fastest way to perform TF computations in Python.

    • Can be accessed through inference_fn property of ConcreteFunctions
    • Does not support gradients.
    • See tf.types.experimental.AtomicFunction documentation for how to call and use it.

  • tf.data:

    • Moved option warm_start from tf.data.experimental.OptimizationOptions to tf.data.Options.

  • tf.lite:

    • sub_op and mul_op support broadcasting up to 6 dimensions.

    • The tflite::SignatureRunner class, which provides support for named parameters and for multiple named computations within a single TF Lite model, is no longer considered experimental. Likewise for the following signature-related methods of tflite::Interpreter:

      • tflite::Interpreter::GetSignatureRunner
      • tflite::Interpreter::signature_keys
      • tflite::Interpreter::signature_inputs
      • tflite::Interpreter::signature_outputs
      • tflite::Interpreter::input_tensor_by_signature
      • tflite::Interpreter::output_tensor_by_signature

    • Similarly, the following signature runner functions in the TF Lite C API are no longer considered experimental:

... (truncated)

Changelog

Sourced from tensorflow-cpu'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

... (truncated)

Commits


Updates tf-agents from 0.18.0 to 0.19.0

Commits
  • 737d758 Version updated for release 0.19.0.
  • 80572d0 Using an older version of typing-extensions
  • 20476b4 Internal change.
  • 06705c6 Removing tf-keras dependency as it is installed as the dependency of tensor...
  • c67f483 Fix broken kokoro by avoiding to use deprecated keras.layers.experimental
  • 0c336d6 Left from previous fix.
  • 2a18743 Adding tf-keras to the requirements.
  • d9256db Fix mock of tf.summary.scalar so that the mock also covers tf.compat.v2.summa...
  • 7b67210 logging.warn -> logging.warning to heed the deprecation warning.
  • 5907dce Merge pull request #851 from sehejjain:wrapper-update
  • Additional commits viewable in compare view


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codecov[bot] commented 9 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (f0772a5) 96.34% compared to head (4686393) 97.29%. Report is 2 commits behind head on main.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #98 +/- ## ========================================== + Coverage 96.34% 97.29% +0.94% ========================================== Files 15 15 Lines 821 813 -8 ========================================== Hits 791 791 + Misses 30 22 -8 ```

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