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@dependabot dependabot bot commented on behalf of github May 6, 2024

Bumps the pip group with 5 updates in the / directory:

Package From To
flask 1.1.2 2.2.5
tensorflow 2.7.2 2.11.1
idna 3.4 3.7
pillow 9.5.0 10.3.0
tensorflow-gpu 2.7.2 2.12.0

Updates flask from 1.1.2 to 2.2.5

Release notes

Sourced from flask's releases.

2.2.5

This is a security fix release for the 2.2.x release branch. Note that 2.3.x is the currently supported release branch; please upgrade to the latest version if possible.

2.2.4

This is a fix release for the 2.2.x release branch.

2.2.3

This is a fix release for the 2.2.x release branch.

2.2.2

This is a fix release for the 2.2.0 feature release.

2.2.1

This is a fix release for the 2.2.0 feature release.

2.2.0

This is a feature release, which includes new features and removes previously deprecated code. The 2.2.x branch is now the supported bug fix branch, the 2.1.x branch will become a tag marking the end of support for that branch. We encourage everyone to upgrade, and to use a tool such as pip-tools to pin all dependencies and control upgrades.

2.1.3

2.1.2

This is a fix release for the 2.1.0 feature release.

2.1.1

This is a fix release for the 2.1.0 feature release.

... (truncated)

Changelog

Sourced from flask's changelog.

Version 2.2.5

Released 2023-05-02

  • Update for compatibility with Werkzeug 2.3.3.
  • Set Vary: Cookie header when the session is accessed, modified, or refreshed.

Version 2.2.4

Released 2023-04-25

  • Update for compatibility with Werkzeug 2.3.

Version 2.2.3

Released 2023-02-15

  • Autoescape is enabled by default for .svg template files. :issue:4831
  • Fix the type of template_folder to accept pathlib.Path. :issue:4892
  • Add --debug option to the flask run command. :issue:4777

Version 2.2.2

Released 2022-08-08

  • Update Werkzeug dependency to >= 2.2.2. This includes fixes related to the new faster router, header parsing, and the development server. :pr:4754
  • Fix the default value for app.env to be "production". This attribute remains deprecated. :issue:4740

Version 2.2.1

Released 2022-08-03

  • Setting or accessing json_encoder or json_decoder raises a deprecation warning. :issue:4732

Version 2.2.0

... (truncated)

Commits

Updates tensorflow from 2.7.2 to 2.11.1

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.11.1

Release 2.11.1

Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.

  • Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a GitHub issue to let us know.

This release also introduces several vulnerability fixes:

TensorFlow 2.11.0

Release 2.11.0

Breaking Changes

  • The tf.keras.optimizers.Optimizer base class now points to the new Keras optimizer, while the old optimizers have been moved to the tf.keras.optimizers.legacy namespace.

    If you find your workflow failing due to this change, you may be facing one of the following issues:

    • Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplifies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to tf.keras.optimizer.legacy.XXX (e.g. tf.keras.optimizer.legacy.Adam).
    • TF1 compatibility. The new optimizer, tf.keras.optimizers.Optimizer, does not support TF1 any more, so please use the legacy optimizer tf.keras.optimizer.legacy.XXX. We highly recommend migrating your workflow to TF2 for stable support and new features.
    • Old optimizer API not found. The new optimizer, tf.keras.optimizers.Optimizer, has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API documentation to find alternatives to the missing API. If you must call the deprecated API, please change your optimizer to the legacy optimizer.
    • Learning rate schedule access. When using a tf.keras.optimizers.schedules.LearningRateSchedule, the new optimizer's learning_rate property returns the current learning rate value instead of a LearningRateSchedule object as before. If you need to access the LearningRateSchedule object, please use optimizer._learning_rate.
    • If you implemented a custom optimizer based on the old optimizer. Please set your optimizer to subclass tf.keras.optimizer.legacy.XXX. If you want to migrate to the new optimizer and find it does not support your optimizer, please file an issue in the Keras GitHub repo.
    • Errors, such as Cannot recognize variable.... The new optimizer requires all optimizer variables to be created at the first apply_gradients() or minimize() call. If your workflow calls the optimizer to update different parts of the model in multiple stages, please call optimizer.build(model.trainable_variables) before the training loop.
    • Timeout or performance loss. We don't anticipate this to happen, but if you see such issues, please use the legacy optimizer, and file an issue in the Keras GitHub repo.

    The old Keras optimizer will never be deleted, but will not see any new feature additions. New optimizers (for example, tf.keras.optimizers.Adafactor) will only be implemented based on the new tf.keras.optimizers.Optimizer base class.

  • tensorflow/python/keras code is a legacy copy of Keras since the TensorFlow v2.7 release, and will be deleted in the v2.12 release. Please remove any import of tensorflow.python.keras and use the public API with from tensorflow import keras or import tensorflow as tf; tf.keras.

Major Features and Improvements

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.11.1

Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.

  • Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a GitHub issue to let us know.

This release also introduces several vulnerability fixes:

Release 2.11.0

Breaking Changes

  • tf.keras.optimizers.Optimizer now points to the new Keras optimizer, and old optimizers have moved to the tf.keras.optimizers.legacy namespace. If you find your workflow failing due to this change, you may be facing one of the following issues:

    • Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to tf.keras.optimizers.legacy.XXX (e.g. tf.keras.optimizers.legacy.Adam).
    • TF1 compatibility. The new optimizer does not support TF1 any more, so please use the legacy optimizer tf.keras.optimizer.legacy.XXX. We highly recommend to migrate your workflow to TF2 for stable support and new features.
    • API not found. The new optimizer has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API

... (truncated)

Commits
  • a3e2c69 Merge pull request #60016 from tensorflow/fix-relnotes
  • 13b85dc Fix release notes
  • 48b18db Merge pull request #60014 from tensorflow/disable-test-that-ooms
  • eea48f5 Disable a test that results in OOM+segfault
  • a632584 Merge pull request #60000 from tensorflow/venkat-patch-3
  • 93dea7a Update RELEASE.md
  • a2ba9f1 Updating Release.md with Legal Language for Release Notes
  • fae41c7 Merge pull request #59998 from tensorflow/fix-bad-cherrypick-again
  • 2757416 Fix bad cherrypick
  • c78616f Merge pull request #59992 from tensorflow/fix-2.11-build
  • Additional commits viewable in compare view

Updates idna from 3.4 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: kjd/idna@v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view

Updates jinja2 from 2.11.3 to 3.1.4

Release notes

Sourced from jinja2's releases.

3.1.4

This is the Jinja 3.1.4 security release, which fixes security issues and bugs but does not otherwise change behavior and should not result in breaking changes.

PyPI: https://pypi.org/project/Jinja2/3.1.4/ Changes: https://jinja.palletsprojects.com/en/3.1.x/changes/#version-3-1-4

  • The xmlattr filter does not allow keys with / solidus, > greater-than sign, or = equals sign, in addition to disallowing spaces. Regardless of any validation done by Jinja, user input should never be used as keys to this filter, or must be separately validated first. GHSA-h75v-3vvj-5mfj

3.1.3

This is a fix release for the 3.1.x feature branch.

3.1.2

This is a fix release for the 3.1.0 feature release.

3.1.1

3.1.0

This is a feature release, which includes new features and removes previously deprecated features. The 3.1.x branch is now the supported bugfix branch, the 3.0.x branch has become a tag marking the end of support for that branch. We encourage everyone to upgrade, and to use a tool such as pip-tools to pin all dependencies and control upgrades. We also encourage upgrading to MarkupSafe 2.1.1, the latest version at this time.

3.0.3

3.0.2

3.0.1

3.0.0

New major versions of all the core Pallets libraries, including Jinja 3.0, have been released! 🎉

This represents a significant amount of work, and there are quite a few changes. Be sure to carefully read the changelog, and use tools such as pip-compile and Dependabot to pin your dependencies and control your updates.

... (truncated)

Changelog

Sourced from jinja2's changelog.

Version 3.1.4

Released 2024-05-05

  • The xmlattr filter does not allow keys with / solidus, > greater-than sign, or = equals sign, in addition to disallowing spaces. Regardless of any validation done by Jinja, user input should never be used as keys to this filter, or must be separately validated first. :ghsa:h75v-3vvj-5mfj

Version 3.1.3

Released 2024-01-10

  • Fix compiler error when checking if required blocks in parent templates are empty. :pr:1858
  • xmlattr filter does not allow keys with spaces. :ghsa:h5c8-rqwp-cp95
  • Make error messages stemming from invalid nesting of {% trans %} blocks more helpful. :pr:1918

Version 3.1.2

Released 2022-04-28

  • Add parameters to Environment.overlay to match __init__. :issue:1645
  • Handle race condition in FileSystemBytecodeCache. :issue:1654

Version 3.1.1

Released 2022-03-25

  • The template filename on Windows uses the primary path separator. :issue:1637

Version 3.1.0

Released 2022-03-24

  • Drop support for Python 3.6. :pr:1534
  • Remove previously deprecated code. :pr:1544

... (truncated)

Commits

Updates pillow from 9.5.0 to 10.3.0

Release notes

Sourced from pillow's releases.

10.3.0

https://pillow.readthedocs.io/en/stable/releasenotes/10.3.0.html

Changes

... (truncated)

Changelog

Sourced from pillow's changelog.

10.3.0 (2024-04-01)

  • CVE-2024-28219: Use strncpy to avoid buffer overflow #7928 [radarhere, hugovk]

  • Deprecate eval(), replacing it with lambda_eval() and unsafe_eval() #7927 [radarhere, hugovk]

  • Raise ValueError if seeking to greater than offset-sized integer in TIFF #7883 [radarhere]

  • Add --report argument to __main__.py to omit supported formats #7818 [nulano, radarhere, hugovk]

  • Added RGB to I;16, I;16L, I;16B and I;16N conversion #7918, #7920 [radarhere]

  • Fix editable installation with custom build backend and configuration options #7658 [nulano, radarhere]

  • Fix putdata() for I;16N on big-endian #7209 [Yay295, hugovk, radarhere]

  • Determine MPO size from markers, not EXIF data #7884 [radarhere]

  • Improved conversion from RGB to RGBa, LA and La #7888 [radarhere]

  • Support FITS images with GZIP_1 compression #7894 [radarhere]

  • Use I;16 mode for 9-bit JPEG 2000 images #7900 [scaramallion, radarhere]

  • Raise ValueError if kmeans is negative #7891 [radarhere]

  • Remove TIFF tag OSUBFILETYPE when saving using libtiff #7893 [radarhere]

  • Raise ValueError for negative values when loading P1-P3 PPM images #7882 [radarhere]

  • Added reading of JPEG2000 palettes #7870 [radarhere]

  • Added alpha_quality argument when saving WebP images #7872 [radarhere]

... (truncated)

Commits
  • 5c89d88 10.3.0 version bump
  • 63cbfcf Update CHANGES.rst [ci skip]
  • 2776126 Merge pull request #7928 from python-pillow/lcms
  • aeb51cb Merge branch 'main' into lcms
  • 5beb0b6 Update CHANGES.rst [ci skip]
  • cac6ffa Merge pull request #7927 from python-pillow/imagemath
  • f5eeeac Name as 'options' in lambda_eval and unsafe_eval, but '_dict' in deprecated eval
  • facf3af Added release notes
  • 2a93aba Use strncpy to avoid buffer overflow
  • a670597 Update CHANGES.rst [ci skip]
  • Additional commits viewable in compare view

Updates werkzeug from 1.0.1 to 3.0.3

Release notes

Sourced from werkzeug's releases.

3.0.3

This is the Werkzeug 3.0.3 security release, which fixes security issues and bugs but does not otherwise change behavior and should not result in breaking changes.

PyPI: https://pypi.org/project/Werkzeug/3.0.3/ Changes: https://werkzeug.palletsprojects.com/en/3.0.x/changes/#version-3-0-3 Milestone: https://github.com/pallets/werkzeug/milestone/35?closed=1

  • Only allow localhost, .localhost, 127.0.0.1, or the specified hostname when running the dev server, to make debugger requests. Additional hosts can be added by using the debugger middleware directly. The debugger UI makes requests using the full URL rather than only the path. GHSA-2g68-c3qc-8985
  • Make reloader more robust when "" is in sys.path. #2823
  • Better TLS cert format with adhoc dev certs. #2891
  • Inform Python < 3.12 how to handle itms-services URIs correctly, rather than using an overly-broad workaround in Werkzeug that caused some redirect URIs to be passed on without encoding. #2828
  • Type annotation for Rule.endpoint and other uses of endpoint is Any. #2836

3.0.2

This is a fix release for the 3.0.x feature branch.

3.0.1

This is a security release for the 3.0.x feature branch.

3.0.0

This is a feature release, which includes new features, removes previously deprecated code, and adds new deprecations. The 3.0.x branch is now the supported fix branch, the 2.3.x branch will become a tag marking the end of support for that branch. We encourage everyone to upgrade, and to use a tool such as pip-tools to pin all dependencies and control upgrades. Test with warnings treated as errors to be able to adapt to deprecation warnings early.

2.3.8

This is a security release for the 2.3.x feature branch.

2.3.7

This is a fix release for the 2.3.x feature branch.

2.3.6

This is a fix release for the 2.3.x feature branch.

2.3.5

This is a fix release for the 2.3.x feature branch.

... (truncated)

Changelog

Sourced from werkzeug's changelog.

Version 3.0.3

Released 2024-05-05

  • Only allow localhost, .localhost, 127.0.0.1, or the specified hostname when running the dev server, to make debugger requests. Additional hosts can be added by using the debugger middleware directly. The debugger UI makes requests using the full URL rather than only the path. :ghsa:2g68-c3qc-8985

  • Make reloader more robust when "" is in sys.path. :pr:2823

  • Better TLS cert format with adhoc dev certs. :pr:2891

  • Inform Python < 3.12 how to handle itms-services URIs correctly, rather than using an overly-broad workaround in Werkzeug that caused some redirect URIs to be passed on without encoding. :issue:2828

  • Type annotation for Rule.endpoint and other uses of endpoint is Any. :issue:2836

  • Make reloader more robust when "" is in sys.path. :pr:2823

Version 3.0.2

Released 2024-04-01

  • Ensure setting merge_slashes to False results in NotFound for repeated-slash requests against single slash routes. :issue:2834
  • Fix handling of TypeError in TypeConversionDict.get() to match ValueError. :issue:2843
  • Fix response_wrapper type check in test client. :issue:2831
  • Make the return type of MultiPartParser.parse more precise. :issue:2840
  • Raise an error if converter arguments cannot be parsed. :issue:2822

Version 3.0.1

Released 2023-10-24

  • Fix slow multipart parsing for large parts potentially enabling DoS attacks.

Version 3.0.0

Released 2023-09-30

  • Remove previously deprecated code. :pr:2768

... (truncated)

Commits

Updates tensorflow-gpu from 2.7.2 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...

      Description has been truncated

Bumps the pip group with 5 updates in the / directory:

| Package | From | To |
| --- | --- | --- |
| [flask](https://github.com/pallets/flask) | `1.1.2` | `2.2.5` |
| [tensorflow](https://github.com/tensorflow/tensorflow) | `2.7.2` | `2.11.1` |
| [idna](https://github.com/kjd/idna) | `3.4` | `3.7` |
| [pillow](https://github.com/python-pillow/Pillow) | `9.5.0` | `10.3.0` |
| [tensorflow-gpu](https://github.com/tensorflow/tensorflow) | `2.7.2` | `2.12.0` |



Updates `flask` from 1.1.2 to 2.2.5
- [Release notes](https://github.com/pallets/flask/releases)
- [Changelog](https://github.com/pallets/flask/blob/main/CHANGES.rst)
- [Commits](pallets/flask@1.1.2...2.2.5)

Updates `tensorflow` from 2.7.2 to 2.11.1
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.7.2...v2.11.1)

Updates `idna` from 3.4 to 3.7
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.rst)
- [Commits](kjd/idna@v3.4...v3.7)

Updates `jinja2` from 2.11.3 to 3.1.4
- [Release notes](https://github.com/pallets/jinja/releases)
- [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst)
- [Commits](pallets/jinja@2.11.3...3.1.4)

Updates `pillow` from 9.5.0 to 10.3.0
- [Release notes](https://github.com/python-pillow/Pillow/releases)
- [Changelog](https://github.com/python-pillow/Pillow/blob/main/CHANGES.rst)
- [Commits](python-pillow/Pillow@9.5.0...10.3.0)

Updates `werkzeug` from 1.0.1 to 3.0.3
- [Release notes](https://github.com/pallets/werkzeug/releases)
- [Changelog](https://github.com/pallets/werkzeug/blob/main/CHANGES.rst)
- [Commits](pallets/werkzeug@1.0.1...3.0.3)

Updates `tensorflow-gpu` from 2.7.2 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@v2.7.2...v2.12.0)

---
updated-dependencies:
- dependency-name: flask
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: idna
  dependency-type: indirect
  dependency-group: pip
- dependency-name: jinja2
  dependency-type: indirect
  dependency-group: pip
- dependency-name: pillow
  dependency-type: indirect
  dependency-group: pip
- dependency-name: werkzeug
  dependency-type: indirect
  dependency-group: pip
- dependency-name: tensorflow-gpu
  dependency-type: direct:production
  dependency-group: pip
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label May 6, 2024
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dependabot bot commented on behalf of github May 21, 2024

Superseded by #36.

@dependabot dependabot bot closed this May 21, 2024
@dependabot dependabot bot deleted the dependabot/pip/pip-3204dd2d44 branch May 21, 2024 07:42
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