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Bump the pip group across 3 directories with 2 updates #5

Closed dependabot[bot] closed 3 hours ago

dependabot[bot] commented 3 hours ago

Bumps the pip group with 1 update in the /examples/ogbg_molpcba directory: tensorflow. Bumps the pip group with 2 updates in the /examples/ppo directory: tensorflow and opencv-python. Bumps the pip group with 1 update in the /examples/sst2 directory: tensorflow.

Updates tensorflow from 2.8.1 to 2.12.1

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.12.1

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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.

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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:

... (truncated)

Commits
  • 8e2b665 Merge pull request #61094 from tensorflow/venkat-patch-444
  • 02478f0 Fix unit test failure caused by numpy update
  • 2cd9b41 Merge pull request #61082 from tensorflow/venkat-patch-333
  • 7995c95 Updating Simplified retry logic to DNS cache
  • 29479ed Merge pull request #60872 from tensorflow/r2.12-c45a6c0b1cb
  • e76a933 Simplified retry logic to DNS cache
  • 76addf7 Merge pull request #60850 from elfringham/non_pip_fix
  • 05987a8 [Linaro:ARM_CI] Fix permissions for running nonpip tests
  • 23724d2 Merge pull request #60842 from elfringham/r2.12
  • 496730b Limit typing_extensions to less than 4.6.0 until it works
  • Additional commits viewable in compare view


Updates tensorflow from 2.8.1 to 2.12.1

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.12.1

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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.

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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:

... (truncated)

Commits
  • 8e2b665 Merge pull request #61094 from tensorflow/venkat-patch-444
  • 02478f0 Fix unit test failure caused by numpy update
  • 2cd9b41 Merge pull request #61082 from tensorflow/venkat-patch-333
  • 7995c95 Updating Simplified retry logic to DNS cache
  • 29479ed Merge pull request #60872 from tensorflow/r2.12-c45a6c0b1cb
  • e76a933 Simplified retry logic to DNS cache
  • 76addf7 Merge pull request #60850 from elfringham/non_pip_fix
  • 05987a8 [Linaro:ARM_CI] Fix permissions for running nonpip tests
  • 23724d2 Merge pull request #60842 from elfringham/r2.12
  • 496730b Limit typing_extensions to less than 4.6.0 until it works
  • Additional commits viewable in compare view


Updates opencv-python from 4.5.4.60 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 from 2.8.1 to 2.12.1

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.12.1

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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.

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.12.1

Bug Fixes and Other Changes

  • The use of the ambe config to build and test aarch64 is not needed. The ambe config will be removed in the future. Making cpu_arm64_pip.sh and cpu_arm64_nonpip.sh more similar for easier future maintenance.

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:

... (truncated)

Commits
  • 8e2b665 Merge pull request #61094 from tensorflow/venkat-patch-444
  • 02478f0 Fix unit test failure caused by numpy update
  • 2cd9b41 Merge pull request #61082 from tensorflow/venkat-patch-333
  • 7995c95 Updating Simplified retry logic to DNS cache
  • 29479ed Merge pull request #60872 from tensorflow/r2.12-c45a6c0b1cb
  • e76a933 Simplified retry logic to DNS cache
  • 76addf7 Merge pull request #60850 from elfringham/non_pip_fix
  • 05987a8 [Linaro:ARM_CI] Fix permissions for running nonpip tests
  • 23724d2 Merge pull request #60842 from elfringham/r2.12
  • 496730b Limit typing_extensions to less than 4.6.0 until it works
  • Additional commits viewable in compare view


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Summary by Sourcery

Update dependencies for TensorFlow and OpenCV-Python across various directories to their latest versions, enhancing security and functionality.

Enhancements:

performance-testing-bot[bot] commented 3 hours ago

Unable to locate .performanceTestingBot config file

sourcery-ai[bot] commented 3 hours ago

Reviewer's Guide by Sourcery

This PR updates the TensorFlow and OpenCV-Python dependencies across three different directories. The main changes include upgrading TensorFlow from 2.8.1 to 2.12.1 in all three directories and OpenCV-Python from 4.5.4.60 to 4.8.1.78 in the PPO directory.

Class diagram for updated dependencies

classDiagram
    class Requirements {
        +absl_py: String
        +atari_py: String
        +opencv_python: String
        +flax: String
        +gym: String
        +ml_collections: String
        +numpy: String
        +optax: String
        +tensorflow: String
        +tensorflow_datasets: String
        +tensorflow_text: String
    }
    note for Requirements "Updated opencv-python to 4.8.1.78 and tensorflow to 2.12.1"

File-Level Changes

Change Details Files
Update TensorFlow to version 2.12.1 across all directories
  • Added support for Python 3.11
  • Removed support for Python 3.7
  • Removed redundant tensorflow-gpu package
  • Updated tf.function behavior with stricter function signature parsing
  • Added new features in tf.lite, tf.experimental.dtensor, and tf.data modules
 examples/ppo/requirements.txt
examples/ogbg_molpcba/requirements.txt
examples/sst2/requirements.txt
Update OpenCV-Python to version 4.8.1.78 in PPO directory
  • Added WebP security update for CVE-2023-4863
  • Added cv2.typing package
  • Added Python typing stubs
  • Added support for np.float16
  • Fixed reference counting errors in registerNewType
 examples/ppo/requirements.txt
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For COLLABORATOR only :

git-greetings[bot] commented 3 hours ago
PR Details of @dependabot[bot] in midjourney-flax : OPEN CLOSED TOTAL
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coderabbitai[bot] commented 3 hours ago

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socket-security[bot] commented 3 hours ago

New and removed dependencies detected. Learn more about Socket for GitHub ↗︎

Package New capabilities Transitives Size Publisher
pypi/opencv-python@4.8.1.78 environment, eval, filesystem, network, shell, unsafe +26 1.11 GB andrey.senyaev, asmorkalov, sergregory, ...1 more

🚮 Removed packages: pypi/opencv-python@4.5.4.60

View full report↗︎