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Bump the pip group across 2 directories with 8 updates#1
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dependabot/pip/binder/pip-22536f2502

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Bumps the pip group with 6 updates in the /binder directory:

Package From To
keras 2.8.0 3.9.0
nltk 3.6.6 3.9.1
pillow 9.1.1 10.3.0
tensorflow 2.8.1 2.12.1
tqdm 4.62.3 4.66.3
transformers 4.30.0 4.48.0

Bumps the pip group with 5 updates in the /lessons/5-NLP directory:

Package From To
nltk 3.5 3.9.1
pillow 7.1.2 10.3.0
transformers 4.30.0 4.48.0
opencv-python 4.5.1.48 4.8.1.78
torch 1.8.1 2.4.0

Updates keras from 2.8.0 to 3.9.0

Release notes

Sourced from keras's releases.

Keras 3.9.0

New features

  • Add new Keras rematerialization API: keras.RematScope and keras.remat. It can be used to turn on rematerizaliation for certain layers in fine-grained manner, e.g. only for layers larger than a certain size, or for a specific set of layers, or only for activations.
  • Increase op coverage for OpenVINO backend.
  • New operations:
    • keras.ops.rot90
    • keras.ops.rearrange (Einops-style)
    • keras.ops.signbit
    • keras.ops.polar
    • keras.ops.image.perspective_transform
    • keras.ops.image.gaussian_blur
  • New layers:
    • keras.layers.RMSNormalization
    • keras.layers.AugMix
    • keras.layers.CutMix
    • keras.layers.RandomInvert
    • keras.layers.RandomErasing
    • keras.layers.RandomGaussianBlur
    • keras.layers.RandomPerspective
  • Minor additions:
    • Add support for dtype argument to JaxLayer and FlaxLayer layers
    • Add boolean input support to BinaryAccuracy metric
    • Add antialias argument to keras.layers.Resizing layer.
  • Security fix: disallow object pickling in saved npz model files (numpy format). Thanks to Peng Zhou for reporting the vulnerability.

New Contributors

Full Changelog: keras-team/keras@v3.8.0...v3.9.0

Keras 3.8.0

New: OpenVINO backend

OpenVINO is now available as an infererence-only Keras backend. You can start using it by setting the backend field to "openvino" in your keras.json config file.

... (truncated)

Commits
  • eb1f844 Fix Discretization serialization when num_bins is used. (#20971)
  • 19b1418 Enable cuDNN RNNs when dropout is set and training=True (#20983)
  • 465a3d2 Update version number
  • 2688bfc Fix docstring
  • ff427e5 [Keras Ops and Layer] Add keras.ops.rms_norm() and keras.layers.RMSNormalizat...
  • f7115c2 Fix PyTorch stateful RNN/LSTM gradient computation error resolves #20875 (#20...
  • 7a7bca6 [OpenVINO backend] Support numpy.append (#20951)
  • c356cae Bump the github-actions group with 3 updates (#20975)
  • 0902ff4 [OpenVino BackEnd]support np.count_nonzero for ov BackEnd (#20945)
  • 21c8997 Make gaussian_blur to use scipy convolve2d (#20974)
  • Additional commits viewable in compare view

Updates nltk from 3.6.6 to 3.9.1

Changelog

Sourced from nltk's changelog.

Version 3.9.2 2025-03-10

  • Minor fixes including:
  • properly initialize Portuguese corpus reader
  • support for mixed rules conversion into Chomsky Normal Form
  • only import tkinter if a GUI is needed
  • issue #2112 with Corenlp
  • new environment variable NLTK_DOWNLOADER_FORCE_INTERACTIVE_SHELL
  • Lesk defaults to most frequent sense in case of ties

Thanks to the following contributions to 3.9.2: Jose Cols, Peter de Blanc, GeneralPoxter, Eric Kafe, William LaCroix, Jason Liu, Samer Masterson, Mike014, purificant, Andrew Ernest Ritz, samertm, Ikram Ul Haq

Version 3.9.1 2024-08-19

  • Fixed bug that prevented wordnet from loading

Version 3.9 2024-08-18

  • Fix security vulnerability CVE-2024-39705 (breaking change)
  • Replace pickled models (punkt, chunker, taggers) by new pickle-free "_tab" packages
  • No longer sort Wordnet synsets and relations (sort in calling function when required)
  • Only strip the last suffix in Wordnet Morphy, thus restricting synsets() results
  • Add Python 3.12 support
  • Many other minor fixes

Thanks to the following contributors to 3.8.2: Tom Aarsen, Cat Lee Ball, Veralara Bernhard, Carlos Brandt, Konstantin Chernyshev, Michael Higgins, Eric Kafe, Vivek Kalyan, David Lukes, Rob Malouf, purificant, Alex Rudnick, Liling Tan, Akihiro Yamazaki.

Version 3.8.1 2023-01-02

  • Resolve RCE vulnerability in localhost WordNet Browser (#3100)
  • Remove unused tool scripts (#3099)
  • Resolve XSS vulnerability in localhost WordNet Browser (#3096)
  • Add Python 3.11 support (#3090)

Thanks to the following contributors to 3.8.1: Francis Bond, John Vandenberg, Tom Aarsen

Version 3.8 2022-12-12

  • Refactor dispersion plot (#3082)
  • Provide type hints for LazyCorpusLoader variables (#3081)
  • Throw warning when LanguageModel is initialized with incorrect vocabulary (#3080)
  • Fix WordNet's all_synsets() function (#3078)
  • Resolve TreebankWordDetokenizer inconsistency with end-of-string contractions (#3070)
  • Support both iso639-3 codes and BCP-47 language tags (#3060)
  • Avoid DeprecationWarning in Regexp tokenizer (#3055)
  • Fix many doctests, add doctests to CI (#3054, #3050, #3048)
  • Fix bool field not being read in VerbNet (#3044)

... (truncated)

Commits

Updates pillow from 9.1.1 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

Deprecations

  • Deprecate eval(), replacing it with lambda_eval() and unsafe_eval() #7927 [@​hugovk]
  • Deprecate ImageCms constants and versions() function #7702 [@​nulano]

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 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 tqdm from 4.62.3 to 4.66.3

Release notes

Sourced from tqdm's releases.

tqdm v4.66.3 stable

tqdm v4.66.2 stable

  • pandas: add DataFrame.progress_map (#1549)
  • notebook: fix HTML padding (#1506)
  • keras: fix resuming training when verbose>=2 (#1508)
  • fix format_num negative fractions missing leading zero (#1548)
  • fix Python 3.12 DeprecationWarning on import (#1519)
  • linting: use f-strings (#1549)
  • update tests (#1549)
  • CI: bump actions (#1549)

tqdm v4.66.1 stable

  • fix utils.envwrap types (#1493 <- #1491, #1320 <- #966, #1319)
    • e.g. cloudwatch & kubernetes workaround: export TQDM_POSITION=-1
  • drop mentions of unsupported Python versions

tqdm v4.66.0 stable

  • environment variables to override defaults (TQDM_*) (#1491 <- #1061, #950 <- #614, #1318, #619, #612, #370)
    • e.g. in CI jobs, export TQDM_MININTERVAL=5 to avoid log spam
    • add tests & docs for tqdm.utils.envwrap
  • fix & update CLI completion
  • fix & update API docs
  • minor code tidy: replace os.path => pathlib.Path
  • fix docs image hosting
  • release with CI bot account again (cli/cli#6680)

tqdm v4.65.2 stable

  • exclude examples from distributed wheel (#1492)

tqdm v4.65.1 stable

  • migrate setup.{cfg,py} => pyproject.toml (#1490)
    • fix asv benchmarks
    • update docs
  • fix snap build (#1490)
  • fix & update tests (#1490)
    • fix flaky notebook tests
    • bump pre-commit
    • bump workflow actions

tqdm v4.65.0 stable

  • add Python 3.11 and drop Python 3.6 support (#1439, #1419, #502 <- #720, #620)
  • misc code & docs tidy
  • fix & update CI workflows & tests

tqdm v4.64.1 stable

... (truncated)

Commits

Updates transformers from 4.30.0 to 4.48.0

Release notes

Sourced from transformers's releases.

v4.48.0: ModernBERT, Aria, TimmWrapper, ColPali, Falcon3, Bamba, VitPose, DinoV2 w/ Registers, Emu3, Cohere v2, TextNet, DiffLlama, PixtralLarge, Moonshine

New models

ModernBERT

The ModernBert model was proposed in Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference by Benjamin Warner, Antoine Chaffin, Benjamin Clavié, Orion Weller, Oskar Hallström, Said Taghadouini, Alexis Galalgher, Raja Bisas, Faisal Ladhak, Tom Aarsen, Nathan Cooper, Grifin Adams, Jeremy Howard and Iacopo Poli.

It is a refresh of the traditional encoder architecture, as used in previous models such as BERT and RoBERTa.

It builds on BERT and implements many modern architectural improvements which have been developed since its original release, such as:

  • Rotary Positional Embeddings to support sequences of up to 8192 tokens.
  • Unpadding to ensure no compute is wasted on padding tokens, speeding up processing time for batches with mixed-length sequences.
  • GeGLU Replacing the original MLP layers with GeGLU layers, shown to improve performance.
  • Alternating Attention where most attention layers employ a sliding window of 128 tokens, with Global Attention only used every 3 layers.
  • Flash Attention to speed up processing.
  • A model designed following recent The Case for Co-Designing Model Architectures with Hardware, ensuring maximum efficiency across inference GPUs.
  • Modern training data scales (2 trillion tokens) and mixtures (including code ande math data)

image

Aria

The Aria model was proposed in Aria: An Open Multimodal Native Mixture-of-Experts Model by Li et al. from the Rhymes.AI team.

Aria is an open multimodal-native model with best-in-class performance across a wide range of multimodal, language, and coding tasks. It has a Mixture-of-Experts architecture, with respectively 3.9B and 3.5B activated parameters per visual token and text token.

TimmWrapper

We add a TimmWrapper set of classes such that timm models can be loaded in as transformer models into the library.

Here's a general usage example:

import torch
from urllib.request import urlopen
from PIL import Image
from transformers import AutoConfig, AutoModelForImageClassification, AutoImageProcessor
checkpoint = "timm/resnet50.a1_in1k"
img = Image.open(urlopen(
'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
))
image_processor = AutoImageProcessor.from_pretrained(checkpoint)
</tr></table>

... (truncated)

Commits

Updates nltk from 3.5 to 3.9.1

Changelog

Sourced from nltk's changelog.

Version 3.9.2 2025-03-10

  • Minor fixes including:
  • properly initialize Portuguese corpus reader
  • support for mixed rules conversion into Chomsky Normal Form
  • only import tkinter if a GUI is needed
  • issue #2112 with Corenlp
  • new environment variable NLTK_DOWNLOADER_FORCE_INTERACTIVE_SHELL
  • Lesk defaults to most frequent sense in case of ties

Thanks to the following contributions to 3.9.2: Jose Cols, Peter de Blanc, GeneralPoxter, Eric Kafe, William LaCroix, Jason Liu, Samer Masterson, Mike014, purificant, Andrew Ernest Ritz, samertm, Ikram Ul Haq

Version 3.9.1 2024-08-19

  • Fixed bug that prevented wordnet from loading

Version 3.9 2024-08-18

  • Fix security vulnerability CVE-2024-39705 (breaking change)
  • Replace pickled models (punkt, chunker, taggers) by new pickle-free "_tab" packages
  • No longer sort Wordnet synsets and relations (sort in calling function when required)
  • Only strip the last suffix in Wordnet Morphy, thus restricting synsets() results
  • Add Python 3.12 support
  • Many other minor fixes

Thanks to the following contributors to 3.8.2: Tom Aarsen, Cat Lee Ball, Veralara Bernhard, Carlos Brandt, Konstantin Chernyshev, Michael Higgins, Eric Kafe, Vivek Kalyan, David Lukes, Rob Malouf, purificant, Alex Rudnick, Liling Tan, Akihiro Yamazaki.

Version 3.8.1 2023-01-02

  • Resolve RCE vulnerability in localhost WordNet Browser (#3100)
  • Remove unused tool scripts (#3099)
  • Resolve XSS vulnerability in localhost WordNet Browser (#3096)
  • Add Python 3.11 support (#3090)

Thanks to the following contributors to 3.8.1: Francis Bond, John Vandenberg, Tom Aarsen

Version 3.8 2022-12-12

  • Refactor dispersion plot (#3082)
  • Provide type hints for LazyCorpusLoader variables (#3081)
  • Throw warning when LanguageModel is initialized with incorrect vocabulary (#3080)
  • Fix WordNet's all_synsets() function (#3078)
  • Resolve TreebankWordDetokenizer inconsistency with end-of-string contractions (#3070)
  • Support both iso639-3 codes and BCP-47 language tags (#3060)
  • Avoid DeprecationWarning in Regexp tokenizer (#3055)
  • Fix many doctests, add doctests to CI (#3054, #3050, #3048)
  • Fix bool field not being read in VerbNet (#3044)

... (truncated)

Commits

Updates pillow from 7.1.2 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

Deprecations

  • Deprecate eval(), replacing it with lambda_eval() and unsafe_eval() #7927 [@​hugovk]
  • Deprecate ImageCms constants and versions() function #7702 [@​nulano]

Changes

Bumps the pip group with 6 updates in the /binder directory:

| Package | From | To |
| --- | --- | --- |
| [keras](https://github.com/keras-team/keras) | `2.8.0` | `3.9.0` |
| [nltk](https://github.com/nltk/nltk) | `3.6.6` | `3.9.1` |
| [pillow](https://github.com/python-pillow/Pillow) | `9.1.1` | `10.3.0` |
| [tensorflow](https://github.com/tensorflow/tensorflow) | `2.8.1` | `2.12.1` |
| [tqdm](https://github.com/tqdm/tqdm) | `4.62.3` | `4.66.3` |
| [transformers](https://github.com/huggingface/transformers) | `4.30.0` | `4.48.0` |

Bumps the pip group with 5 updates in the /lessons/5-NLP directory:

| Package | From | To |
| --- | --- | --- |
| [nltk](https://github.com/nltk/nltk) | `3.5` | `3.9.1` |
| [pillow](https://github.com/python-pillow/Pillow) | `7.1.2` | `10.3.0` |
| [transformers](https://github.com/huggingface/transformers) | `4.30.0` | `4.48.0` |
| [opencv-python](https://github.com/opencv/opencv-python) | `4.5.1.48` | `4.8.1.78` |
| [torch](https://github.com/pytorch/pytorch) | `1.8.1` | `2.4.0` |



Updates `keras` from 2.8.0 to 3.9.0
- [Release notes](https://github.com/keras-team/keras/releases)
- [Commits](keras-team/keras@v2.8.0...v3.9.0)

Updates `nltk` from 3.6.6 to 3.9.1
- [Changelog](https://github.com/nltk/nltk/blob/develop/ChangeLog)
- [Commits](nltk/nltk@3.6.6...3.9.1)

Updates `pillow` from 9.1.1 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@9.1.1...10.3.0)

Updates `tensorflow` from 2.8.1 to 2.12.1
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.8.1...v2.12.1)

Updates `tqdm` from 4.62.3 to 4.66.3
- [Release notes](https://github.com/tqdm/tqdm/releases)
- [Commits](tqdm/tqdm@v4.62.3...v4.66.3)

Updates `transformers` from 4.30.0 to 4.48.0
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.30.0...v4.48.0)

Updates `nltk` from 3.5 to 3.9.1
- [Changelog](https://github.com/nltk/nltk/blob/develop/ChangeLog)
- [Commits](nltk/nltk@3.6.6...3.9.1)

Updates `pillow` from 7.1.2 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@9.1.1...10.3.0)

Updates `transformers` from 4.30.0 to 4.48.0
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.30.0...v4.48.0)

Updates `opencv-python` from 4.5.1.48 to 4.8.1.78
- [Release notes](https://github.com/opencv/opencv-python/releases)
- [Commits](https://github.com/opencv/opencv-python/commits)

Updates `torch` from 1.8.1 to 2.4.0
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v1.8.1...v2.4.0)

---
updated-dependencies:
- dependency-name: keras
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: nltk
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: pillow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tqdm
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: transformers
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: nltk
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: pillow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: transformers
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: opencv-python
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: torch
  dependency-type: direct:production
  dependency-group: pip
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Mar 30, 2025
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