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Bump the pip group across 1 directory with 11 updates #1186

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Bump the pip group across 1 directory with 11 updates #1186

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@dependabot dependabot bot commented on behalf of github Apr 3, 2024

Bumps the pip group with 11 updates in the /cm-mlops/script/get-dataset-cifar10 directory:

Package From To
certifi 2020.12.5 2023.7.22
grpcio 1.34.0 1.53.2
joblib 1.1.1 1.2.0
pillow 8.1.0 10.3.0
protobuf 3.14.0 3.18.3
requests 2.25.1 2.31.0
scikit-learn 0.24.1 1.0.1
scipy 1.6.0 1.11.1
tensorflow 2.5.0 2.11.1
urllib3 1.26.3 1.26.18
werkzeug 1.0.1 2.3.8

Updates certifi from 2020.12.5 to 2023.7.22

Commits

Updates grpcio from 1.34.0 to 1.53.2

Release notes

Sourced from grpcio's releases.

Release v1.53.2

This is release gRPC Core 1.53.2 (glockenspiel).

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes.

Core

Release v1.53.1

This is release gRPC Core 1.53.1 (glockenspiel).

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes.

Release v1.53.0

This is release 1.53.0 (glockenspiel) of gRPC Core.

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes, with highlights listed below.

Core

  • xDS: fix crash when removing the last endpoint from the last locality in weighted_target. (#32592)
  • filter stack: pass peer name up via recv_initial_metadata batch. (#31933)
  • [EventEngine] Add advice against blocking work in callbacks. (#32397)
  • [http2] Dont drop connections on metadata limit exceeded. (#32309)
  • xDS: reject aggregate cluster with empty cluster list. (#32238)
  • Fix Python epoll1 Fork Support. (#32196)
  • server: introduce ServerMetricRecorder API and move per-call reporting from a C++ interceptor to a C-core filter. (#32106)
  • [EventEngine] Add invalid handle types to the public API. (#32202)
  • [EventEngine] Refactoring the EventEngine Test Suite: Part 1. (#32127)
  • xDS: fix WeightedClusters total weight handling. (#32134)

C++

  • Update minimum MSVC version to 2019. (#32615)
  • Use CMake variables for paths in pkg-config files. (#31671)

... (truncated)

Changelog

Sourced from grpcio's changelog.

gRPC Release Schedule

Below is the release schedule for gRPC Java, Go and Core and its dependent languages C++, C#, Objective-C, PHP, Python and Ruby.

Releases are scheduled every six weeks on Tuesdays on a best effort basis. In some unavoidable situations a release may be delayed or released early or a language may skip a release altogether and do the next release to catch up with other languages. See the past releases in the links above. A six-week cycle gives us a good balance between delivering new features/fixes quickly and keeping the release overhead low.

The gRPC release support policy can be found here.

Releases are cut from release branches. For Core and Java repos, the release branch is cut two weeks before the scheduled release date. For Go, the branch is cut just before the release. An RC (release candidate) is published for Core and its dependent languages just after the branch cut. This RC is later promoted to release version if no further changes are made to the release branch. We do our best to keep head of master branch stable at all times regardless of release schedule. Daily build packages from master branch for C#, PHP, Python, Ruby and Protoc plugins are published on packages.grpc.io. If you depend on gRPC in production we recommend to set up your CI system to test the RCs and, if possible, the daily builds.

Names of gRPC releases are here.

Release Scheduled Branch Cut Scheduled Release Date
v1.17.0 Nov 19, 2018 Dec 4, 2018
v1.18.0 Jan 2, 2019 Jan 15, 2019
v1.19.0 Feb 12, 2019 Feb 26, 2019
v1.20.0 Mar 26, 2019 Apr 9, 2019
v1.21.0 May 7, 2019 May 21, 2019
v1.22.0 Jun 18, 2019 Jul 2, 2019
v1.23.0 Jul 30, 2019 Aug 13, 2019
v1.24.0 Sept 10, 2019 Sept 24, 2019
v1.25.0 Oct 22, 2019 Nov 5, 2019
v1.26.0 Dec 3, 2019 Dec 17, 2019
v1.27.0 Jan 14, 2020 Jan 28, 2020
v1.28.0 Feb 25, 2020 Mar 10, 2020
v1.29.0 Apr 7, 2020 Apr 21, 2020
v1.30.0 May 19, 2020 Jun 2, 2020
v1.31.0 Jul 14, 2020 Jul 28, 2020
v1.32.0 Aug 25, 2020 Sep 8, 2020
v1.33.0 Oct 6, 2020 Oct 20, 2020
Commits
  • afb307f [v1.53.x][Interop] Backport Python image update (#33864)
  • 7a9373b [Backport] [dependency] Restrict cython to less than 3.X (#33770)
  • fdb64a6 [v1.53][Build] Update Phusion baseimage (#33767) (#33836)
  • cdf4186 [PSM Interop] Legacy tests: fix xDS test client build (v1.53.x backport) (#33...
  • ce5b93a [PSM Interop] Legacy test builds always pull the driver from master (v1.53.x ...
  • b24b6ea [release] Bump release version to 1.53.2 (#33709)
  • 1e86ca5 [backport][iomgr][EventEngine] Improve server handling of file descriptor exh...
  • aff3066 [PSM interop] Don't fail url_map target if sub-target already failed (v1.53.x...
  • 539d75c [PSM interop] Don't fail target if sub-target already failed (#33222) (v1.53....
  • 3e79c88 [Release] Bump version to 1.53.1 (on v1.53.x branch) (#33047)
  • Additional commits viewable in compare view

Updates joblib from 1.1.1 to 1.2.0

Changelog

Sourced from joblib's changelog.

Release 1.2.0

  • Fix a security issue where eval(pre_dispatch) could potentially run arbitrary code. Now only basic numerics are supported. joblib/joblib#1327

  • Make sure that joblib works even when multiprocessing is not available, for instance with Pyodide joblib/joblib#1256

  • Avoid unnecessary warnings when workers and main process delete the temporary memmap folder contents concurrently. joblib/joblib#1263

  • Fix memory alignment bug for pickles containing numpy arrays. This is especially important when loading the pickle with mmap_mode != None as the resulting numpy.memmap object would not be able to correct the misalignment without performing a memory copy. This bug would cause invalid computation and segmentation faults with native code that would directly access the underlying data buffer of a numpy array, for instance C/C++/Cython code compiled with older GCC versions or some old OpenBLAS written in platform specific assembly. joblib/joblib#1254

  • Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+.

  • Vendor loky 3.3.0 which fixes several bugs including:

    • robustly forcibly terminating worker processes in case of a crash (joblib/joblib#1269);

    • avoiding leaking worker processes in case of nested loky parallel calls;

    • reliability spawn the correct number of reusable workers.

Commits
  • 5991350 Release 1.2.0
  • 3fa2188 MAINT cleanup numpy warnings related to np.matrix in tests (#1340)
  • cea26ff CI test the future loky-3.3.0 branch (#1338)
  • 8aca6f4 MAINT: remove pytest.warns(None) warnings in pytest 7 (#1264)
  • 067ed4f XFAIL test_child_raises_parent_exits_cleanly with multiprocessing (#1339)
  • ac4ebd5 MAINT add back pytest warnings plugin (#1337)
  • a23427d Test child raises parent exits cleanly more reliable on macos (#1335)
  • ac09691 [MAINT] various test updates (#1334)
  • 4a314b1 Vendor loky 3.2.0 (#1333)
  • bdf47e9 Make test_parallel_with_interactively_defined_functions_default_backend timeo...
  • Additional commits viewable in compare view

Updates pillow from 8.1.0 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 protobuf from 3.14.0 to 3.18.3

Release notes

Sourced from protobuf's releases.

Protocol Buffers v3.18.3

C++

Protocol Buffers v3.18.2

Java

  • Improve performance characteristics of UnknownFieldSet parsing (#9371)

Protocol Buffers v3.18.1

Python

  • Update setup.py to reflect that we now require at least Python 3.5 (#8989)
  • Performance fix for DynamicMessage: force GetRaw() to be inlined (#9023)

Ruby

  • Update ruby_generator.cc to allow proto2 imports in proto3 (#9003)

Protocol Buffers v3.18.0

C++

  • Fix warnings raised by clang 11 (#8664)
  • Make StringPiece constructible from std::string_view (#8707)
  • Add missing capability attributes for LLVM 12 (#8714)
  • Stop using std::iterator (deprecated in C++17). (#8741)
  • Move field_access_listener from libprotobuf-lite to libprotobuf (#8775)
  • Fix #7047 Safely handle setlocale (#8735)
  • Remove deprecated version of SetTotalBytesLimit() (#8794)
  • Support arena allocation of google::protobuf::AnyMetadata (#8758)
  • Fix undefined symbol error around SharedCtor() (#8827)
  • Fix default value of enum(int) in json_util with proto2 (#8835)
  • Better Smaller ByteSizeLong
  • Introduce event filters for inject_field_listener_events
  • Reduce memory usage of DescriptorPool
  • For lazy fields copy serialized form when allowed.
  • Re-introduce the InlinedStringField class
  • v2 access listener
  • Reduce padding in the proto's ExtensionRegistry map.
  • GetExtension performance optimizations
  • Make tracker a static variable rather than call static functions
  • Support extensions in field access listener
  • Annotate MergeFrom for field access listener
  • Fix incomplete types for field access listener
  • Add map_entry/new_map_entry to SpecificField in MessageDifferencer. They record the map items which are different in MessageDifferencer's reporter.
  • Reduce binary size due to fieldless proto messages
  • TextFormat: ParseInfoTree supports getting field end location in addition to start.
  • Fix repeated enum extension size in field listener
  • Enable Any Text Expansion for Descriptors::DebugString()
  • Switch from int{8,16,32,64} to int{8,16,32,64}_t

... (truncated)

Commits

Updates requests from 2.25.1 to 2.31.0

Release notes

Sourced from requests's releases.

v2.31.0

2.31.0 (2023-05-22)

Security

  • Versions of Requests between v2.3.0 and v2.30.0 are vulnerable to potential forwarding of Proxy-Authorization headers to destination servers when following HTTPS redirects.

    When proxies are defined with user info (https://user:pass@proxy:8080), Requests will construct a Proxy-Authorization header that is attached to the request to authenticate with the proxy.

    In cases where Requests receives a redirect response, it previously reattached the Proxy-Authorization header incorrectly, resulting in the value being sent through the tunneled connection to the destination server. Users who rely on defining their proxy credentials in the URL are strongly encouraged to upgrade to Requests 2.31.0+ to prevent unintentional leakage and rotate their proxy credentials once the change has been fully deployed.

    Users who do not use a proxy or do not supply their proxy credentials through the user information portion of their proxy URL are not subject to this vulnerability.

    Full details can be read in our Github Security Advisory and CVE-2023-32681.

v2.30.0

2.30.0 (2023-05-03)

Dependencies

v2.29.0

2.29.0 (2023-04-26)

Improvements

  • Requests now defers chunked requests to the urllib3 implementation to improve standardization. (#6226)
  • Requests relaxes header component requirements to support bytes/str subclasses. (#6356)

... (truncated)

Changelog

Sourced from requests's changelog.

2.31.0 (2023-05-22)

Security

  • Versions of Requests between v2.3.0 and v2.30.0 are vulnerable to potential forwarding of Proxy-Authorization headers to destination servers when following HTTPS redirects.

    When proxies are defined with user info (https://user:pass@proxy:8080), Requests will construct a Proxy-Authorization header that is attached to the request to authenticate with the proxy.

    In cases where Requests receives a redirect response, it previously reattached the Proxy-Authorization header incorrectly, resulting in the value being sent through the tunneled connection to the destination server. Users who rely on defining their proxy credentials in the URL are strongly encouraged to upgrade to Requests 2.31.0+ to prevent unintentional leakage and rotate their proxy credentials once the change has been fully deployed.

    Users who do not use a proxy or do not supply their proxy credentials through the user information portion of their proxy URL are not subject to this vulnerability.

    Full details can be read in our Github Security Advisory and CVE-2023-32681.

2.30.0 (2023-05-03)

Dependencies

2.29.0 (2023-04-26)

Improvements

  • Requests now defers chunked requests to the urllib3 implementation to improve standardization. (#6226)
  • Requests relaxes header component requirements to support bytes/str subclasses. (#6356)

2.28.2 (2023-01-12)

... (truncated)

Commits

Updates scikit-learn from 0.24.1 to 1.0.1

Release notes

Sourced from scikit-learn's releases.

scikit-learn 1.0.1

We're happy to announce the 1.0.1 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.0.html#version-1-0-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

scikit-learn 1.0

We're happy to announce the 1.0 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.0.html#changes-1-0

This version supports Python versions 3.7 to 3.9.

scikit-learn 0.24.2

We're happy to announce the 0.24.2 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn
Commits
  • 0d37891 Trigger wheel builder workflow: [cd build]
  • 7737cb9 DOC update the News section in website (#21417)
  • 8971a19 DOC Ensures that MultiTaskElasticNetCV passes numpydoc validation (#21405)
  • d6e24ee DOC Ensures that LabelSpreading passes numpydoc validation (#21414)
  • 14fda2f DOC Ensures that PassiveAggressiveRegressor passes numpydoc validation (#21413)
  • 112ae4e DOC Ensures that OrthogonalMatchingPursuitCV passes numpydoc validation (#21412)
  • cd927c0 FIX delete feature_names_in_ when refitting on a ndarray (#21389)
  • ae223ee bumpversion to 1.0.1
  • 9227162 MNT remove 1.1 changelog due to rebase conflict
  • 5d75547 MNT fix changelog 1.0.1 (#21416)
  • Additional commits viewable in compare view

Updates scipy from 1.6.0 to 1.11.1

Release notes

Sourced from scipy's releases.

SciPy 1.11.1 Release Notes

SciPy 1.11.1 is a bug-fix release with no new features compared to 1.11.0. In particular, a licensing issue discovered after the release of 1.11.0 has been addressed.

Authors

  • Name (commits)
  • h-vetinari (1)
  • Robert Kern (1)
  • Ilhan Polat (4)
  • Tyler Reddy (8)

A total of 4 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

SciPy 1.11.0 Release Notes

SciPy 1.11.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.11.x branch, and on adding new features on the main branch.

This release requires Python 3.9+ and NumPy 1.21.6 or greater.

For running on PyPy, PyPy3 6.0+ is required.

Highlights of this release

  • Several scipy.sparse array API improvements, including sparse.sparray, a new public base class distinct from the older sparse.spmatrix class, proper 64-bit index support, and numerous deprecations paving the way to a modern sparse array experience.
  • scipy.stats added tools for survival analysis, multiple hypothesis testing, sensitivity analysis, and working with censored data.

... (truncated)

Commits
  • cfe8011 REL: 1.11.1 rel commit [wheel build]
  • 450d8aa Merge pull request #18779 from tylerjereddy/treddy_1_11_1_prep
  • 6f942e8 DOC: update 1.11.1 relnotes
  • 145cec5 MAINT: fix unuran licensing
  • 0760bab MAINT:linalg.det:Return scalars for singleton inputs (#18763)
  • a1c6f99 MAINT:linalg:Use only NumPy types in lu
  • 5cdc2fe MAINT:linalg:Remove memcpy from lu
  • d9ac3f3 FIX:linalg:Guard against possible permute_l out of bound behavior
  • 7ec5010 BUG: fix handling for factorial(..., exact=False) for 0-dim array inputs (#...
  • 90415c6 BUG: Fix work array construction for various weight shapes. (#18741)
  • Additional commits viewable in compare view

Updates tensorflow from 2.5.0 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:

@dependabot
Bump the pip group across 1 directory with 11 updates
f47e4c2 
Bumps the pip group with 11 updates in the /cm-mlops/script/get-dataset-cifar10 directory:

| Package | From | To |
| --- | --- | --- |
| [certifi](https://github.com/certifi/python-certifi) | `2020.12.5` | `2023.7.22` |
| [grpcio](https://github.com/grpc/grpc) | `1.34.0` | `1.53.2` |
| [joblib](https://github.com/joblib/joblib) | `1.1.1` | `1.2.0` |
| [pillow](https://github.com/python-pillow/Pillow) | `8.1.0` | `10.3.0` |
| [protobuf](https://github.com/protocolbuffers/protobuf) | `3.14.0` | `3.18.3` |
| [requests](https://github.com/psf/requests) | `2.25.1` | `2.31.0` |
| [scikit-learn](https://github.com/scikit-learn/scikit-learn) | `0.24.1` | `1.0.1` |
| [scipy](https://github.com/scipy/scipy) | `1.6.0` | `1.11.1` |
| [tensorflow](https://github.com/tensorflow/tensorflow) | `2.5.0` | `2.11.1` |
| [urllib3](https://github.com/urllib3/urllib3) | `1.26.3` | `1.26.18` |
| [werkzeug](https://github.com/pallets/werkzeug) | `1.0.1` | `2.3.8` |



Updates `certifi` from 2020.12.5 to 2023.7.22
- [Commits](certifi/python-certifi@2020.12.05...2023.07.22)

Updates `grpcio` from 1.34.0 to 1.53.2
- [Release notes](https://github.com/grpc/grpc/releases)
- [Changelog](https://github.com/grpc/grpc/blob/master/doc/grpc_release_schedule.md)
- [Commits](grpc/grpc@v1.34.0...v1.53.2)

Updates `joblib` from 1.1.1 to 1.2.0
- [Release notes](https://github.com/joblib/joblib/releases)
- [Changelog](https://github.com/joblib/joblib/blob/main/CHANGES.rst)
- [Commits](joblib/joblib@1.1.1...1.2.0)

Updates `pillow` from 8.1.0 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@8.1.0...10.3.0)

Updates `protobuf` from 3.14.0 to 3.18.3
- [Release notes](https://github.com/protocolbuffers/protobuf/releases)
- [Changelog](https://github.com/protocolbuffers/protobuf/blob/main/protobuf_release.bzl)
- [Commits](protocolbuffers/protobuf@v3.14.0...v3.18.3)

Updates `requests` from 2.25.1 to 2.31.0
- [Release notes](https://github.com/psf/requests/releases)
- [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md)
- [Commits](psf/requests@v2.25.1...v2.31.0)

Updates `scikit-learn` from 0.24.1 to 1.0.1
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@0.24.1...1.0.1)

Updates `scipy` from 1.6.0 to 1.11.1
- [Release notes](https://github.com/scipy/scipy/releases)
- [Commits](scipy/scipy@v1.6.0...v1.11.1)

Updates `tensorflow` from 2.5.0 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@v2.5.0...v2.11.1)

Updates `urllib3` from 1.26.3 to 1.26.18
- [Release notes](https://github.com/urllib3/urllib3/releases)
- [Changelog](https://github.com/urllib3/urllib3/blob/main/CHANGES.rst)
- [Commits](urllib3/urllib3@1.26.3...1.26.18)

Updates `werkzeug` from 1.0.1 to 2.3.8
- [Release notes](https://github.com/pallets/werkzeug/releases)
- [Changelog](https://github.com/pallets/werkzeug/blob/main/CHANGES.rst)
- [Commits](pallets/werkzeug@1.0.1...2.3.8)

---
updated-dependencies:
- dependency-name: certifi
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: grpcio
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: joblib
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: pillow
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: protobuf
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: requests
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: scikit-learn
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: scipy
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: tensorflow
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: urllib3
  dependency-type: direct:production
  dependency-group: pip-security-group
- dependency-name: werkzeug
  dependency-type: direct:production
  dependency-group: pip-security-group
...

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@dependabot dependabot bot requested a review from a team as a code owner April 3, 2024 18:25
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Apr 3, 2024
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github-actions bot commented Apr 3, 2024

MLCommons CLA bot All contributors have signed the MLCommons CLA ✍️ ✅

@gfursin gfursin closed this Apr 3, 2024
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dependabot bot commented on behalf of github Apr 3, 2024

This pull request was built based on a group rule. Closing it will not ignore any of these versions in future pull requests.

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@dependabot dependabot bot deleted the dependabot/pip/cm-mlops/script/get-dataset-cifar10/pip-security-group-66cde625c3 branch April 3, 2024 18:33
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