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Bump the pip group across 9 directories with 4 updates #11

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@dependabot dependabot bot commented on behalf of github Aug 30, 2024

Bumps the pip group with 1 update in the /CoDi directory: aiohttp.
Bumps the pip group with 1 update in the /activation_clustering directory: tensorflow-gpu.
Bumps the pip group with 1 update in the /arithmetic_sampling directory: keras.
Bumps the pip group with 2 updates in the /aux_tasks directory: keras and opencv-python.
Bumps the pip group with 1 update in the /axial directory: tensorflow-gpu.
Bumps the pip group with 1 update in the /cache_replacement directory: opencv-python.
Bumps the pip group with 2 updates in the /concept_explanations directory: tensorflow-gpu and keras.
Bumps the pip group with 1 update in the /contrastive_rl directory: keras.
Bumps the pip group with 1 update in the /cvl_public directory: keras.

Updates aiohttp from 3.9.1 to 3.10.2

Release notes

Sourced from aiohttp's releases.

3.10.2

Bug fixes

  • Fixed server checks for circular symbolic links to be compatible with Python 3.13 -- by :user:steverep.

    Related issues and pull requests on GitHub: #8565.

  • Fixed request body not being read when ignoring an Upgrade request -- by :user:Dreamsorcerer.

    Related issues and pull requests on GitHub: #8597.

  • Fixed an edge case where shutdown would wait for timeout when the handler was already completed -- by :user:Dreamsorcerer.

    Related issues and pull requests on GitHub: #8611.

  • Fixed connecting to npipe://, tcp://, and unix:// urls -- by :user:bdraco.

    Related issues and pull requests on GitHub: #8632.

  • Fixed WebSocket ping tasks being prematurely garbage collected -- by :user:bdraco.

    There was a small risk that WebSocket ping tasks would be prematurely garbage collected because the event loop only holds a weak reference to the task. The garbage collection risk has been fixed by holding a strong reference to the task. Additionally, the task is now scheduled eagerly with Python 3.12+ to increase the chance it can be completed immediately and avoid having to hold any references to the task.

    Related issues and pull requests on GitHub: #8641.

  • Fixed incorrectly following symlinks for compressed file variants -- by :user:steverep.

    Related issues and pull requests on GitHub:

... (truncated)

Changelog

Sourced from aiohttp's changelog.

3.10.2 (2024-08-08)

Bug fixes

  • Fixed server checks for circular symbolic links to be compatible with Python 3.13 -- by :user:steverep.

    Related issues and pull requests on GitHub: :issue:8565.

  • Fixed request body not being read when ignoring an Upgrade request -- by :user:Dreamsorcerer.

    Related issues and pull requests on GitHub: :issue:8597.

  • Fixed an edge case where shutdown would wait for timeout when the handler was already completed -- by :user:Dreamsorcerer.

    Related issues and pull requests on GitHub: :issue:8611.

  • Fixed connecting to npipe://, tcp://, and unix:// urls -- by :user:bdraco.

    Related issues and pull requests on GitHub: :issue:8632.

  • Fixed WebSocket ping tasks being prematurely garbage collected -- by :user:bdraco.

    There was a small risk that WebSocket ping tasks would be prematurely garbage collected because the event loop only holds a weak reference to the task. The garbage collection risk has been fixed by holding a strong reference to the task. Additionally, the task is now scheduled eagerly with Python 3.12+ to increase the chance it can be completed immediately and avoid having to hold any references to the task.

    Related issues and pull requests on GitHub: :issue:8641.

  • Fixed incorrectly following symlinks for compressed file variants -- by :user:steverep.

... (truncated)

Commits
  • 491106e Release 3.10.2 (#8655)
  • ce2e975 [PR #8652/b0536ae6 backport][3.10] Do not follow symlinks for compressed file...
  • 6a77806 [PR #8636/51d872e backport][3.10] Remove Request.wait_for_disconnection() met...
  • 1f92213 [PR #8642/e4942771 backport][3.10] Fix response to circular symlinks with Pyt...
  • 2ef14a6 [PR #8641/0a88bab backport][3.10] Fix WebSocket ping tasks being prematurely ...
  • 68e8496 [PR #8608/c4acabc backport][3.10] Fix timer handle churn in websocket heartbe...
  • 72f41aa [PR #8632/b2691f2 backport][3.10] Fix connecting to npipe://, tcp://, and uni...
  • bf83dbe [PR #8634/c7293e19 backport][3.10] Backport #8620 as improvements to various ...
  • 4815765 [PR #8597/c99a1e27 backport][3.10] Fix reading of body when ignoring an upgra...
  • 266608d [PR #8611/1fcef940 backport][3.10] Fix handler waiting on shutdown (#8627)
  • Additional commits viewable in compare view

Updates tensorflow-gpu from 2.1.0 to 2.12.0

Release notes

Sourced from tensorflow-gpu's releases.

TensorFlow 2.12.0

Release 2.12.0

TensorFlow

Breaking Changes

  • Build, Compilation and Packaging

    • Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These packages were removed and replaced with packages that direct users to switch to tensorflow or tf-nightly respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See https://pypi.org/project/tensorflow-gpu for more details.

  • tf.function:

    • tf.function now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as:
      • Using functools.wraps on a function with different signature
      • Using functools.partial with an invalid tf.function input
    • tf.function now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.
    • Parameterless tf.functions are assumed to have an empty input_signature instead of an undefined one even if the input_signature is unspecified.
    • tf.types.experimental.TraceType now requires an additional placeholder_value method to be defined.
    • tf.function now traces with placeholder values generated by TraceType instead of the value itself.

  • Experimental APIs tf.config.experimental.enable_mlir_graph_optimization and tf.config.experimental.disable_mlir_graph_optimization were removed.

Major Features and Improvements

  • Support for Python 3.11 has been added.

  • Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.

  • tf.lite:

    • Add 16-bit float type support for built-in op fill.
    • Transpose now supports 6D tensors.
    • Float LSTM now supports diagonal recurrent tensors: https://arxiv.org/abs/1903.08023

  • tf.experimental.dtensor:

    • Coordination service now works with dtensor.initialize_accelerator_system, and enabled by default.
    • Add tf.experimental.dtensor.is_dtensor to check if a tensor is a DTensor instance.

  • tf.data:

    • Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the experimental_symbolic_checkpoint option of tf.data.Options().
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.random() operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If seed is set and rerandomize_each_iteration=True, the random() operation will produce a different (deterministic) sequence of numbers every epoch.
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.sample_from_datasets() operation, which controls whether the sequence of generated random numbers used for sampling should be re-randomized every epoch or not. If seed is set and rerandomize_each_iteration=True, the sample_from_datasets() operation will use a different (deterministic) sequence of numbers every epoch.

  • tf.test:

    • Added tf.test.experimental.sync_devices, which is useful for accurately measuring performance in benchmarks.

  • tf.experimental.dtensor:

... (truncated)

Changelog

Sourced from tensorflow-gpu's changelog.

Release 2.12.0

Breaking Changes

  • Build, Compilation and Packaging

    • Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These packages were removed and replaced with packages that direct users to switch to tensorflow or tf-nightly respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See https://pypi.org/project/tensorflow-gpu for more details.

  • tf.function:

    • tf.function now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as:
      • Using functools.wraps on a function with different signature
      • Using functools.partial with an invalid tf.function input
    • tf.function now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.
    • Parameterless tf.functions are assumed to have an empty input_signature instead of an undefined one even if the input_signature is unspecified.
    • tf.types.experimental.TraceType now requires an additional placeholder_value method to be defined.
    • tf.function now traces with placeholder values generated by TraceType instead of the value itself.

  • Experimental APIs tf.config.experimental.enable_mlir_graph_optimization and tf.config.experimental.disable_mlir_graph_optimization were removed.

Major Features and Improvements

  • Support for Python 3.11 has been added.

  • Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.

  • tf.lite:

    • Add 16-bit float type support for built-in op fill.
    • Transpose now supports 6D tensors.
    • Float LSTM now supports diagonal recurrent tensors: https://arxiv.org/abs/1903.08023

  • tf.experimental.dtensor:

    • Coordination service now works with dtensor.initialize_accelerator_system, and enabled by default.
    • Add tf.experimental.dtensor.is_dtensor to check if a tensor is a DTensor instance.

  • tf.data:

    • Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the experimental_symbolic_checkpoint option of tf.data.Options().
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.random() operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If seed is set and rerandomize_each_iteration=True, the random() operation will produce a different (deterministic) sequence of numbers every epoch.
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.sample_from_datasets() operation, which controls whether the sequence of generated random numbers used for sampling should be re-randomized every epoch or not. If seed is set and rerandomize_each_iteration=True, the sample_from_datasets() operation will use a different (deterministic) sequence of numbers every epoch.

  • tf.test:

    • Added tf.test.experimental.sync_devices, which is useful for accurately measuring performance in benchmarks.

  • tf.experimental.dtensor:

    • Added experimental support to ReduceScatter fuse on GPU (NCCL).

... (truncated)

Commits
  • 0db597d Merge pull request #60051 from tensorflow/venkat2469-patch-1
  • 1a12f59 Update RELEASE.md
  • aa4d558 Merge pull request #60050 from tensorflow/venkat-patch-6
  • bd1ab8a Update the security section in RELEASE.md
  • 4905be0 Merge pull request #60049 from tensorflow/venkat-patch-5
  • 9f96caa Update setup.py on TF release branch with released version of Estimator and k...
  • e719b6b Update Relese.md (#60033)
  • 64a9d54 Merge pull request #60017 from tensorflow/joefernandez-patch-2.12-release-notes
  • 7a4ebfd Update RELEASE.md
  • e0e10a9 Merge pull request #59988 from tensorflow-jenkins/version-numbers-2.12.0-8756
  • Additional commits viewable in compare view

Updates keras from 2.12.0 to 2.13.1

Release notes

Sourced from keras's releases.

Keras Release 2.13.1

What's Changed

... (truncated)

Commits
  • b3ffea6 Cherrypick Sequential serialization bug fix for r2.13 (#18258)
  • 87db506 Cherrypick the release script fix for RC. (#18082)
  • a51c89a Increase the version number for keras 2.13 (#18081)
  • 861ad74 Adds error for serializing metric using layer serialization.
  • 1b7c53d Adds Keras v3 saving testing coverage to Keras layers tests.
  • e7c4d09 Expands Keras internal testing coverage for the new v3 saving format for comm...
  • d72829a Change references from distribution_strategy_context.py to `distribute_lib....
  • 605b2d7 Merge pull request #17961 from SamuelMarks:keras.layers.activation-defaults-to
  • a64d0b7 Merge pull request #17955 from SamuelMarks:keras.datasets-defaults-to
  • cb1e1a0 Merge pull request #17967 from SamuelMarks:keras.layers.preprocessing-default...
  • Additional commits viewable in compare view

Updates keras from 2.8.0 to 2.13.1

Release notes

Sourced from keras's releases.

Keras Release 2.13.1

What's Changed

... (truncated)

Commits
  • b3ffea6 Cherrypick Sequential serialization bug fix for r2.13 (#18258)
  • 87db506 Cherrypick the release script fix for RC. (#18082)
  • a51c89a Increase the version number for keras 2.13 (#18081)
  • 861ad74 Adds error for serializing metric using layer serialization.
  • 1b7c53d Adds Keras v3 saving testing coverage to Keras layers tests.
  • e7c4d09 Expands Keras internal testing coverage for the new v3 saving format for comm...
  • d72829a Change references from distribution_strategy_context.py to `distribute_lib....
  • 605b2d7 Merge pull request #17961 from SamuelMarks:keras.layers.activation-defaults-to
  • a64d0b7 Merge pull request #17955 from SamuelMarks:keras.datasets-defaults-to
  • cb1e1a0 Merge pull request #17967 from SamuelMarks:keras.layers.preprocessing-default...
  • Additional commits viewable in compare view

Updates opencv-python from 4.5.5.64 to 4.8.1.78

Release notes

Sourced from opencv-python's releases.

4.8.1.78

OpenCV 4.8.1 release.

Important changes:

4.8.0.76

Adds cv2.typing to package. Close #869

4.8.0.74

Important changes:

  • #20370 Python typing stubs.
  • #23350 Fix reference counting errors in registerNewType.
  • #23399, #23436, #23138 Fixed ChAruco and diamond boards detector bindings.
  • #23371 Added bindings to allow GpuMat and Stream objects to be initialized from memory initialized in other libraries
  • #23691 np.float16 support.
  • Python bindings for RotatedRect, CV_MAKETYPE, CV_8UC(n).
  • Several build fixes for OpenCV-Python package

4.7.0.72

OpenCV 4.7.0 with various distribution bug fixes.

  • Mac OS 11 support.
  • Old Linux support with zlib version older than 1.9.
  • Package build fixes for Python 11 on Musl C based system (Alpine).

4.7.0.70

OpenCV 4.7.0 with various distribution bug fixes.

  • Mac OS 11 support.
  • Old Linux support with zlib version older than 1.9.
  • Package build fixes for Python 11 on Musl C based system (Alpine).

4.7.0.68

opencv-python: https://pypi.org/project/opencv-python/ opencv-contrib-python: https://pypi.org/project/opencv-contrib-python/ opencv-python-headless: https://pypi.org/project/opencv-python-headless/ opencv-contrib-python-headless: https://pypi.org/project/opencv-contrib-python-headless/

OpenCV 4.7.0

Changes:

  • Updated third-party libraries to fix potential vulnerabilities.
  • Dropped Python 3.6 support.
  • Added Python 3.11 support.

4.6.0.66

opencv-python: https://pypi.org/project/opencv-python/ opencv-contrib-python: https://pypi.org/project/opencv-contrib-python/ opencv-python-headless: https://pypi.org/project/opencv-python-headless/

... (truncated)

Commits

Updates tensorflow-gpu from 1.15.0 to 2.12.0

Release notes

Sourced from tensorflow-gpu's releases.

TensorFlow 2.12.0

Release 2.12.0

TensorFlow

Breaking Changes

  • Build, Compilation and Packaging

    • Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These packages were removed and replaced with packages that direct users to switch to tensorflow or tf-nightly respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See https://pypi.org/project/tensorflow-gpu for more details.

  • tf.function:

    • tf.function now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as:
      • Using functools.wraps on a function with different signature
      • Using functools.partial with an invalid tf.function input
    • tf.function now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.
    • Parameterless tf.functions are assumed to have an empty input_signature instead of an undefined one even if the input_signature is unspecified.
    • tf.types.experimental.TraceType now requires an additional placeholder_value method to be defined.
    • tf.function now traces with placeholder values generated by TraceType instead of the value itself.

  • Experimental APIs tf.config.experimental.enable_mlir_graph_optimization and tf.config.experimental.disable_mlir_graph_optimization were removed.

Major Features and Improvements

  • Support for Python 3.11 has been added.

  • Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.

  • tf.lite:

    • Add 16-bit float type support for built-in op fill.
    • Transpose now supports 6D tensors.
    • Float LSTM now supports diagonal recurrent tensors: https://arxiv.org/abs/1903.08023

  • tf.experimental.dtensor:

    • Coordination service now works with dtensor.initialize_accelerator_system, and enabled by default.
    • Add tf.experimental.dtensor.is_dtensor to check if a tensor is a DTensor instance.

  • tf.data:

    • Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the experimental_symbolic_checkpoint option of tf.data.Options().
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.random() operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If seed is set and rerandomize_each_iteration=True, the random() operation will produce a different (deterministic) sequence of numbers every epoch.
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.sample_from_datasets() operation, which controls whether the sequence of generated random numbers used for sampling should be re-randomized every epoch or not. If seed is set and rerandomize_each_iteration=True, the sample_from_datasets() operation will use a different (deterministic) sequence of numbers every epoch.

  • tf.test:

    • Added tf.test.experimental.sync_devices, which is useful for accurately measuring performance in benchmarks.

  • tf.experimental.dtensor:

... (truncated)

Changelog

Sourced from tensorflow-gpu's changelog.

Release 2.12.0

Breaking Changes

  • Build, Compilation and Packaging

    • Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These packages were removed and replaced with packages that direct users to switch to tensorflow or tf-nightly respectively. Since TensorFlow 2.1, the only difference between these two sets of packages was their names, so there is no loss of functionality or GPU support. See https://pypi.org/project/tensorflow-gpu for more details.

  • tf.function:

    • tf.function now uses the Python inspect library directly for parsing the signature of the Python function it is decorated on. This change may break code where the function signature is malformed, but was ignored previously, such as:
      • Using functools.wraps on a function with different signature
      • Using functools.partial with an invalid tf.function input
    • tf.function now enforces input parameter names to be valid Python identifiers. Incompatible names are automatically sanitized similarly to existing SavedModel signature behavior.
    • Parameterless tf.functions are assumed to have an empty input_signature instead of an undefined one even if the input_signature is unspecified.
    • tf.types.experimental.TraceType now requires an additional placeholder_value method to be defined.
    • tf.function now traces with placeholder values generated by TraceType instead of the value itself.

  • Experimental APIs tf.config.experimental.enable_mlir_graph_optimization and tf.config.experimental.disable_mlir_graph_optimization were removed.

Major Features and Improvements

  • Support for Python 3.11 has been added.

  • Support for Python 3.7 has been removed. We are not releasing any more patches for Python 3.7.

  • tf.lite:

    • Add 16-bit float type support for built-in op fill.
    • Transpose now supports 6D tensors.
    • Float LSTM now supports diagonal recurrent tensors: https://arxiv.org/abs/1903.08023

  • tf.experimental.dtensor:

    • Coordination service now works with dtensor.initialize_accelerator_system, and enabled by default.
    • Add tf.experimental.dtensor.is_dtensor to check if a tensor is a DTensor instance.

  • tf.data:

    • Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the experimental_symbolic_checkpoint option of tf.data.Options().
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.random() operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If seed is set and rerandomize_each_iteration=True, the random() operation will produce a different (deterministic) sequence of numbers every epoch.
    • Added a new rerandomize_each_iteration argument for the tf.data.Dataset.sample_from_datasets() operation, which controls whether the sequence of generated random numbers used for sampling should be re-randomized every epoch or not. If seed is set and rerandomize_each_iteration=True, the sample_from_datasets() operation will use a different (deterministic) sequence of numbers every epoch.

  • tf.test:

    • Added tf.test.experimental.sync_devices, which is useful for accurately measuring performance in benchmarks.

  • tf.experimental.dtensor:

    • Added experimental support to ReduceScatter fuse on GPU (NCCL).

... (truncated)

Commits
  • 0db597d Merge pull request #60051 from tensorflow/venkat2469-patch-1
  • 1a12f59 Update RELEASE.md
  • aa4d558 Merge pull request #60050 from tensorflow/venkat-patch-6
  • bd1ab8a Update the security section in RELEASE.md
  • 4905be0 Merge pull request #60049 from tensorflow/venkat-patch-5
  • 9f96caa Update setup.py on TF release branch with released version of Estimator and k...
  • e719b6b Update Relese.md (#60033)
  • 64a9d54 Merge pull request #60017 from tensorflow/joefernandez-patch-2.12-release-notes
  • 7a4ebfd Update RELEASE.md
  • e0e10a9 Merge pull request #59988 from tensorflow-jenkins/version-numbers-2.12.0-8756
  • Additional commits viewable in compare view

Updates opencv-python from 4.2.0.32 to 4.8.1.78

Release notes

Sourced from opencv-python's releases.

4.8.1.78

OpenCV 4.8.1 release.

Important changes:

4.8.0.76

Adds cv2.typing to package. Close #869

4.8.0.74

Important changes:

@dependabot
Bump the pip group across 9 directories with 4 updates
68b120d 
Bumps the pip group with 1 update in the /CoDi directory: [aiohttp](https://github.com/aio-libs/aiohttp).
Bumps the pip group with 1 update in the /activation_clustering directory: [tensorflow-gpu](https://github.com/tensorflow/tensorflow).
Bumps the pip group with 1 update in the /arithmetic_sampling directory: [keras](https://github.com/keras-team/keras).
Bumps the pip group with 2 updates in the /aux_tasks directory: [keras](https://github.com/keras-team/keras) and [opencv-python](https://github.com/opencv/opencv-python).
Bumps the pip group with 1 update in the /axial directory: [tensorflow-gpu](https://github.com/tensorflow/tensorflow).
Bumps the pip group with 1 update in the /cache_replacement directory: [opencv-python](https://github.com/opencv/opencv-python).
Bumps the pip group with 2 updates in the /concept_explanations directory: [tensorflow-gpu](https://github.com/tensorflow/tensorflow) and [keras](https://github.com/keras-team/keras).
Bumps the pip group with 1 update in the /contrastive_rl directory: [keras](https://github.com/keras-team/keras).
Bumps the pip group with 1 update in the /cvl_public directory: [keras](https://github.com/keras-team/keras).


Updates `aiohttp` from 3.9.1 to 3.10.2
- [Release notes](https://github.com/aio-libs/aiohttp/releases)
- [Changelog](https://github.com/aio-libs/aiohttp/blob/master/CHANGES.rst)
- [Commits](aio-libs/aiohttp@v3.9.1...v3.10.2)

Updates `tensorflow-gpu` from 2.1.0 to 2.12.0
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.1.0...v2.12.0)

Updates `keras` from 2.12.0 to 2.13.1
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.12.0...v2.13.1)

Updates `keras` from 2.8.0 to 2.13.1
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.12.0...v2.13.1)

Updates `opencv-python` from 4.5.5.64 to 4.8.1.78
- [Release notes](https://github.com/opencv/opencv-python/releases)
- [Commits](https://github.com/opencv/opencv-python/commits)

Updates `tensorflow-gpu` from 1.15.0 to 2.12.0
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.1.0...v2.12.0)

Updates `opencv-python` from 4.2.0.32 to 4.8.1.78
- [Release notes](https://github.com/opencv/opencv-python/releases)
- [Commits](https://github.com/opencv/opencv-python/commits)

Updates `tensorflow-gpu` from 1.13.1 to 2.12.0
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.1.0...v2.12.0)

Updates `keras` from 2.2.4 to 2.13.1
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.12.0...v2.13.1)

Updates `keras` from 2.8.0 to 2.13.1
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.12.0...v2.13.1)

Updates `keras` from 2.8.0 to 2.13.1
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.12.0...v2.13.1)

---
updated-dependencies:
- dependency-name: aiohttp
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow-gpu
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: opencv-python
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow-gpu
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: opencv-python
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow-gpu
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Aug 30, 2024
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