Update dependency keras_nlp to v0.15.1

[renovate-bot]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
keras_nlp	==0.12.1 -> ==0.15.1

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Release Notes

keras-team/keras-nlp (keras_nlp)

v0.15.1

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Summary

Bug fix patch release.

• Always run tf preprocessing on CPU.
• Fix running preprocessing outside the main python thread.
• Fix loading classifiers with the "old name" of XXClasssifier as XXTextClassifier.
• Restore support for bytestring to tokenizers and other preprocessing layers as strings.

What's Changed

• Version bump for pre-release by @​mattdangerw in https://github.com/keras-team/keras-hub/pull/1842
• V0.15.1.dev1 by @​mattdangerw in https://github.com/keras-team/keras-hub/pull/1844
• Version bump for 0.15.1 release by @​mattdangerw in https://github.com/keras-team/keras-hub/pull/1845

Full Changelog: keras-team/keras-hub@v0.15.0...v0.15.1

v0.15.0

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Summary

📢 KerasNLP is becoming KerasHub 📢, read more about it here.

This release contains a number of feature improvements:

• Added int8 quantization support.
  • Use the quantize() method to quantize any model.
  • Llama 2 and Llama 3 pre-quantized presets are available.
• PaliGemmaCausalLM will automatically resize input images during preprocessing.
• Added more converters for hugginface/transformers checkpoints.
  • Gemma 2, PaliGemma, GPT2, Bert, Albert, DistilBert, Bart.
• Class detection for huggingface/transformers checkpoints.
  • Call from_preset() on a base class, and we will find the correct subclass to create.
• Added Vicuna presets.
• Alias Classifier as TextClassifier, BertClassifier as BertTextClassifier.
• Added tokenizer.special_tokens and tokenizer.special_token_ids as convenient properties to view all special tokens on a pretrained tokenizer.

##### Quantize an unquantized model.
lm = keras_nlp.models.CausalLM.from_preset(
    "gemma2_instruct_2b_en",
    dtype="bfloat16",
)
lm.quantize("int8")

##### Load a pre-quantized model.
lm = keras_nlp.models.CausalLM.from_preset(
    "llama3_instruct_8b_en_int8",
    dtype="bfloat16",
)

##### Convert a bert model in the huggingface/transformers format.
classifier = keras_nlp.models.TextClassifier.from_preset(
    "hf://google-bert/bert-base-uncased",
    num_classes=2,
)

##### View all special tokens.
print(classifier.preprocessor.tokenizer.special_tokens)
print(classifier.preprocessor.tokenizer.special_token_ids)

Breaking changes

• On all backends, all strings and ragged output will be returned as python strings or python lists respectively.
  • This include preprocessing methods like tokenize() and detokenize().
  • This may break code that depended on tf.Tensor output on the tensorflow backend, but will lead to consistent output on all backends, which we believe will be an overall improvement.
  • Preprocessing layers can still always be included in a tf.data preprocessing pipeline, on any backend.

What's Changed

• Version bump to 0.14.0.dev0 by @​grasskin in https://github.com/keras-team/keras-nlp/pull/1675
• Revert "Version bump to 0.14.0.dev0" by @​grasskin in https://github.com/keras-team/keras-nlp/pull/1676
• Remove Keras pin, fix tests by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1681
• Add quantization support for Gemma, Gemma2 and PaliGemma by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1670
• add vicuna preset by @​sineeli in https://github.com/keras-team/keras-nlp/pull/1672
• Porting Gemma 2 transformers checkpoint by @​ariG23498 in https://github.com/keras-team/keras-nlp/pull/1678
• Improve CI speed and resolve issues of run_quantization_check by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1682
• Remove build_from_signature from MHA layers by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1687
• Refactoring: in CachedMultiHeadAttention call MHA methods instead of recoding the attention calculation by @​apehex in https://github.com/keras-team/keras-nlp/pull/1684
• Porting PaliGemma transformers checkpoint by @​ariG23498 in https://github.com/keras-team/keras-nlp/pull/1686
• Allow importing keras_nlp without tensorflow by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1660
• Add flag to gemma conversion script to specify local orbax by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1688
• Fix compatibility for earlier versions of Keras by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1690
• Add a test against keras-nightly by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1693
• Fix dtype bugs in ReversibleEmbedding and LayerNorm by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1692
• Partially revert #​1687 by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1695
• Fix quantization test for XLNet by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1699
• Add a HF BERT converter, improve safetensor loading by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1694
• Add a subtle fix for gemma 2 conversions by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1701
• One more small Gemma conversion fix by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1702
• Slightly more defensive handling of type for backbone by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1703
• Add support for converting Gemma 2 checkpoints by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1700
• Make it clearer what is running in the github action UI by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1707
• Try upgrading tensorflow pin by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1706
• Bump version to fix query norm in Gemma 2 9b by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1709
• Gemma: Add logit soft-capping to score function. by @​RyanMullins in https://github.com/keras-team/keras-nlp/pull/1712
• Version bump HEAD to 0.15 by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1713
• Port gpt2 transformers checkpoint by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1704
• Add soft capping to reversible embedding layer by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1718
• Add presets for gemma 2 2b by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1721
• Utilize to_numpy=True in quantize if available by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1725
• Dynamic int8 quantization for Llama2 and Llama3 by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1720
• Bump the python group with 2 updates by @​dependabot in https://github.com/keras-team/keras-nlp/pull/1726
• Shield gemma shortnames by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1731
• Sliding window fixes by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1738
• Add int8 models to Llama2 and Llama3 by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1734
• Port distilbert transformer checkpoint by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1736
• Add support of kwargs to Backbone.from_preset and fix the dtype forwarding in Task.from_preset by @​james77777778 in https://github.com/keras-team/keras-nlp/pull/1742
• Remove src init file contents by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1743
• Remove ROADMAP.md by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1773
• Fix nested list in args on keras.io by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1772
• Remove stale tf only examples by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1771
• Limit the default sequence length to 1024 for all models by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1770
• Consistent preprocessing output on all backends by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1777
• Port albert transformer checkpoint by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1767
• Lower the default learning rate for albert by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1786
• Port bart transformer checkpoint by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1783
• Add an option to disable default compilation by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1787
• Port mistral transformer checkpoint by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1768
• [Bart]Fix missing weight port by @​cosmo3769 in https://github.com/keras-team/keras-nlp/pull/1789
• Remove python 3.8 version in setup.py by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1792
• Class detection works for huggingface checkpoints by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1800
• Rename KerasNLP symbols for a multi-modal future by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1803
• Move preprocessing to base classes by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1807
• Add add_bos=False, add_eos=False to SentencePieceTokenizer.init() by @​briango28 in https://github.com/keras-team/keras-nlp/pull/1811
• Only load a full task config when load_task_extras is passed by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1812
• Add image and audio converter classes by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1813
• Simplify registering "built-in" presets by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1818
• Support image and audio information in task summaries by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1819
• Take two of #​1812, simpler classifier head loading by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1823
• Remove preprocessing layers we no longer use by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1824
• Version bump for dev release by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1825
• Version bump for dev release by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1830
• Version bump for 0.15.0 release by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1832

New Contributors

• @​apehex made their first contribution in https://github.com/keras-team/keras-nlp/pull/1684
• @​cosmo3769 made their first contribution in https://github.com/keras-team/keras-nlp/pull/1704

Full Changelog: keras-team/keras-hub@v0.14.4...v0.15.0

v0.14.4

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Summary

• Fix issues with Gemma 2 sliding window.
• Fix TensorFlow backend Gemma 2 generation.

What's Changed

• Sliding window fixes by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1738
• version bump by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1740
• version bump by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1741

Full Changelog: keras-team/keras-hub@v0.14.3...v0.14.4

v0.14.3

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Summary

• Short names for shield gemma checkpoints.

keras_nlp.models.GemmaCausalLM.from_preset("shieldgemma_2b_en")

What's Changed

• Version bump dev release by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1732
• Version bump for release by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1733

Full Changelog: keras-team/keras-hub@v0.14.2...v0.14.3

v0.14.2

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Summary

• Add Gemma 2 2b.
• Fixes for logit softcapping.

What's Changed

• Version bump 0.14.2.dev0 by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1719
• Bump pypi action version by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1722
• version bump by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1723
• Version bump 0.14.2 by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1724

Full Changelog: keras-team/keras-hub@v0.14.1...v0.14.2

v0.14.1

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Summary

• Update Gemma 2 9b to fix minor config error.

What's Changed

• Bump version to fix query norm in Gemma 2 9b by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1709
• Version bump 0.14.1.dev0 by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1714

Full Changelog: keras-team/keras-hub@v0.14.0...v0.14.1

v0.14.0: 0.14.0

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Summary

• Add Gemma 2 model!
• Support loading fine-tuned transformers checkpoints in KerasNLP. Loading Gemma and Llama3 models are supported for now and will convert on the fly.
• KerasNLP no longer supports Keras 2. Read Getting started with Keras for more information on installing Keras 3 and compatibility with different frameworks. We recommend using KerasNLP with TensorFlow 2.16 or later, as TF 2.16 packages Keras 3 by default.

What's Changed

• Fix newline characters for pali_gemma by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1655
• Remove dead code by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1659
• Fix some testing on the latest version of keras by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1663
• Vicuna Models checkpoints transfer script by @​sineeli in https://github.com/keras-team/keras-nlp/pull/1657
• Add documented but missing methods for some tokenizers by @​SamanehSaadat in https://github.com/keras-team/keras-nlp/pull/1664
• Changed from_preset file downloading to use GFile when able by @​VarunS1997 in https://github.com/keras-team/keras-nlp/pull/1665
• Fix gfile downloads by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1666
• More error handling for gfile by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1667
• Update error message by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1668
• Ditch Keras 2 support by @​mattdangerw in https://github.com/keras-team/keras-nlp/pull/1658
• fix GemmaBackbone.get_layout_map + test by @​martin-gorner in https://github.com/keras-team/keras-nlp/pull/1669
• Covert a safetensor checkpoint from Hugging Face hub by @​ariG23498 in https://github.com/keras-team/keras-nlp/pull/1662
• Add Gemma 2 model by @​grasskin in https://github.com/keras-team/keras-nlp/pull/1673
• Version bump to 0.14.0.dev0 by @​grasskin in https://github.com/keras-team/keras-nlp/pull/1677

Full Changelog: keras-team/keras-hub@v0.12.1...r0.14

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