chore(deps): update python

[renovate-bot]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence	Update	Pending
Werkzeug (changelog)	==3.0.6 -> ==3.1.3					minor
accelerate	==v1.0.1 -> ==1.2.1					minor
bitsandbytes	==0.44.1 -> ==0.45.0					minor
click (changelog)	==8.1.7 -> ==8.1.8					patch
cryptography (changelog)	==43.0.1 -> ==43.0.3					patch
datasets	==3.1.0 -> ==3.2.0					minor
elasticsearch	==8.15.0 -> ==8.17.0					minor
fastapi (changelog)	==0.114.0 -> ==0.115.6					minor
gcsfs	==2024.9.0 -> ==2024.12.0					minor
google-auth	~=2.34.0 -> ~=2.37.0					minor
google-cloud-aiplatform	==1.65.0 -> ==1.75.0					minor	1.76.0
google-cloud-pubsub	~=2.23.0 -> ~=2.27.1					minor	2.27.2
google-cloud-storage	==2.18.2 -> ==2.19.0					minor
gradio	==5.8.0 -> ==5.9.1					minor	5.12.0 (+2)
langchain (changelog)	==0.2.16 -> ==0.3.14					minor
langchain-weaviate	==0.0.2 -> ==0.0.3					patch
mlflow	==2.17.2 -> ==2.19.0					minor
numpy (changelog)	==2.1.1 -> ==2.2.1					minor
pandas (source)	==2.2.2 -> ==2.2.3					patch
peft	==v0.13.2 -> ==0.14.0					minor
pgvector	==0.3.2 -> ==0.3.6					patch
psutil	==6.1.0 -> ==6.1.1					patch
psycopg2-binary (source, changelog)	==2.9.9 -> ==2.9.10					patch
pymupdf (changelog)	==1.24.10 -> ==1.25.1					minor
qdrant-client	==1.11.1 -> ==1.12.2					minor
redis (changelog)	==5.0.8 -> ==5.2.1					minor
ruff (source, changelog)	>=0.6,<=0.6.4 -> >=0.8,<=0.8.6					minor	0.9.1 (+1)
scikit-learn (changelog)	==1.5.1 -> ==1.6.0					minor	1.6.1
scipy	==1.14.1 -> ==1.15.0					minor	1.15.1
six	==1.16.0 -> ==1.17.0					minor
streamlit (source, changelog)	==1.38.0 -> ==1.41.1					minor
tensorflow	==2.17.0 -> ==2.18.0					minor
thejsonlogger	==0.0.3 -> ==0.0.5					patch
transformers	==4.44.2 -> ==4.47.1					minor	4.48.0
transformers	==v4.46.1 -> ==4.47.1					minor	4.48.0
trl	==v0.11.4 -> ==0.13.0					minor
tzdata	==2024.1 -> ==2024.2					minor
uvicorn (changelog)	==0.30.6 -> ==0.34.0					minor
weaviate-client	==4.7.1 -> ==4.10.2					minor
	All locks refreshed					lockFileMaintenance

---

Warning

Some dependencies could not be looked up. Check the Dependency Dashboard for more information.

---

Release Notes

huggingface/accelerate (accelerate)

v1.2.1: : Patchfix

Compare Source

• fix: add max_memory to _init_infer_auto_device_map's return statement inhttps://github.com/huggingface/accelerate/pull/32799 by @​Nech-C
• fix load_state_dict for npu in https://github.com/huggingface/accelerate/pull/3211 by @​statelesshz

Full Changelog: huggingface/accelerate@v1.2.0...v1.2.1

v1.2.0: : Bug Squashing & Fixes across the board

Compare Source

Core

• enable find_executable_batch_size on XPU by @​faaany in https://github.com/huggingface/accelerate/pull/3236
• Use numpy._core instead of numpy.core by @​qgallouedec in https://github.com/huggingface/accelerate/pull/3247
• Add warnings and fallback for unassigned devices in infer_auto_device_map by @​Nech-C in https://github.com/huggingface/accelerate/pull/3066
• Allow for full dynamo config passed to Accelerator by @​muellerzr in https://github.com/huggingface/accelerate/pull/3251
• [WIP] FEAT Decorator to purge accelerate env vars by @​BenjaminBossan in https://github.com/huggingface/accelerate/pull/3252
• [data_loader] Optionally also propagate set_epoch to batch sampler by @​tomaarsen in https://github.com/huggingface/accelerate/pull/3246
• use XPU instead of GPU in the accelerate config prompt text by @​faaany in https://github.com/huggingface/accelerate/pull/3268

Big Modeling

• Fix align_module_device, ensure only cpu tensors for get_state_dict_offloaded_model by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3217
• Remove hook for bnb 4-bit by @​SunMarc in https://github.com/huggingface/accelerate/pull/3223
• [docs] add instruction to install bnb on non-cuda devices by @​faaany in https://github.com/huggingface/accelerate/pull/3227
• Take care of case when "_tied_weights_keys" is not an attribute by @​fabianlim in https://github.com/huggingface/accelerate/pull/3226
• Update deferring_execution.md by @​max-yue in https://github.com/huggingface/accelerate/pull/3262
• Revert default behavior of get_state_dict_from_offload by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3253
• Fix: Resolve #​3060, preload_module_classes is lost for nested modules by @​wejoncy in https://github.com/huggingface/accelerate/pull/3248

DeepSpeed

• Select the DeepSpeedCPUOptimizer based on the original optimizer class. by @​eljandoubi in https://github.com/huggingface/accelerate/pull/3255
• support for wrapped schedulefree optimizer when using deepspeed by @​winglian in https://github.com/huggingface/accelerate/pull/3266

Documentation

• Update code in tracking documentation by @​faaany in https://github.com/huggingface/accelerate/pull/3235

• Replaced set/check breakpoint with set/check trigger in the troubleshooting documentation by @​relh in https://github.com/huggingface/accelerate/pull/3259

• Update set-seed by @​faaany in https://github.com/huggingface/accelerate/pull/3228

• Fix typo by @​faaany in https://github.com/huggingface/accelerate/pull/3221

• Use real path for checkpoint by @​faaany in https://github.com/huggingface/accelerate/pull/3220

• Fixed multiple typos for Tutorials and Guides docs by @​henryhmko in https://github.com/huggingface/accelerate/pull/3274

New Contributors

• @​winglian made their first contribution in https://github.com/huggingface/accelerate/pull/3266
• @​max-yue made their first contribution in https://github.com/huggingface/accelerate/pull/3262
• @​as12138 made their first contribution in https://github.com/huggingface/accelerate/pull/3261
• @​relh made their first contribution in https://github.com/huggingface/accelerate/pull/3259
• @​wejoncy made their first contribution in https://github.com/huggingface/accelerate/pull/3248
• @​henryhmko made their first contribution in https://github.com/huggingface/accelerate/pull/3274

Full Changelog

• Fix align_module_device, ensure only cpu tensors for get_state_dict_offloaded_model by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3217
• remove hook for bnb 4-bit by @​SunMarc in https://github.com/huggingface/accelerate/pull/3223
• enable find_executable_batch_size on XPU by @​faaany in https://github.com/huggingface/accelerate/pull/3236
• take care of case when "_tied_weights_keys" is not an attribute by @​fabianlim in https://github.com/huggingface/accelerate/pull/3226
• [docs] update code in tracking documentation by @​faaany in https://github.com/huggingface/accelerate/pull/3235
• Add warnings and fallback for unassigned devices in infer_auto_device_map by @​Nech-C in https://github.com/huggingface/accelerate/pull/3066
• [data_loader] Optionally also propagate set_epoch to batch sampler by @​tomaarsen in https://github.com/huggingface/accelerate/pull/3246
• [docs] add instruction to install bnb on non-cuda devices by @​faaany in https://github.com/huggingface/accelerate/pull/3227
• Use numpy._core instead of numpy.core by @​qgallouedec in https://github.com/huggingface/accelerate/pull/3247
• Allow for full dynamo config passed to Accelerator by @​muellerzr in https://github.com/huggingface/accelerate/pull/3251
• [WIP] FEAT Decorator to purge accelerate env vars by @​BenjaminBossan in https://github.com/huggingface/accelerate/pull/3252
• use XPU instead of GPU in the accelerate config prompt text by @​faaany in https://github.com/huggingface/accelerate/pull/3268
• support for wrapped schedulefree optimizer when using deepspeed by @​winglian in https://github.com/huggingface/accelerate/pull/3266
• Update deferring_execution.md by @​max-yue in https://github.com/huggingface/accelerate/pull/3262
• Fix: Resolve #​3257 by @​as12138 in https://github.com/huggingface/accelerate/pull/3261
• Replaced set/check breakpoint with set/check trigger in the troubleshooting documentation by @​relh in https://github.com/huggingface/accelerate/pull/3259
• Select the DeepSpeedCPUOptimizer based on the original optimizer class. by @​eljandoubi in https://github.com/huggingface/accelerate/pull/3255
• Revert default behavior of get_state_dict_from_offload by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3253
• Fix: Resolve #​3060, preload_module_classes is lost for nested modules by @​wejoncy in https://github.com/huggingface/accelerate/pull/3248
• [docs] update set-seed by @​faaany in https://github.com/huggingface/accelerate/pull/3228
• [docs] fix typo by @​faaany in https://github.com/huggingface/accelerate/pull/3221
• [docs] use real path for checkpoint by @​faaany in https://github.com/huggingface/accelerate/pull/3220
• Fixed multiple typos for Tutorials and Guides docs by @​henryhmko in https://github.com/huggingface/accelerate/pull/3274

Code Diff

Release diff: huggingface/accelerate@v1.1.1...v1.2.0

v1.1.1

Compare Source

v1.1.0: : Python 3.9 minimum, torch dynamo deepspeed support, and bug fixes

Compare Source

Internals:

• Allow for a data_seed argument in https://github.com/huggingface/accelerate/pull/3150
• Trigger weights_only=True by default for all compatible objects when checkpointing and saving with torch.save in https://github.com/huggingface/accelerate/pull/3036
• Handle negative values for dim input in pad_across_processes in https://github.com/huggingface/accelerate/pull/3114
• Enable cpu bnb distributed lora finetune in https://github.com/huggingface/accelerate/pull/3159

DeepSpeed

• Support torch dynamo for deepspeed>=0.14.4 in https://github.com/huggingface/accelerate/pull/3069

Megatron

• update Megatron-LM plugin code to version 0.8.0 or higher in https://github.com/huggingface/accelerate/pull/3174

Big Model Inference

• New has_offloaded_params utility added in https://github.com/huggingface/accelerate/pull/3188

Examples

• Florence2 distributed inference example in https://github.com/huggingface/accelerate/pull/3123

Full Changelog

• Handle negative values for dim input in pad_across_processes by @​mariusarvinte in https://github.com/huggingface/accelerate/pull/3114
• Fixup DS issue with weakref by @​muellerzr in https://github.com/huggingface/accelerate/pull/3143
• Refactor scaler to util by @​muellerzr in https://github.com/huggingface/accelerate/pull/3142
• DS fix, continued by @​muellerzr in https://github.com/huggingface/accelerate/pull/3145
• Florence2 distributed inference example by @​hlky in https://github.com/huggingface/accelerate/pull/3123
• POC: Allow for a data_seed by @​muellerzr in https://github.com/huggingface/accelerate/pull/3150
• Adding multi gpu speech generation by @​dame-cell in https://github.com/huggingface/accelerate/pull/3149
• support torch dynamo for deepspeed>=0.14.4 by @​oraluben in https://github.com/huggingface/accelerate/pull/3069
• Fixup Zero3 + save_model by @​muellerzr in https://github.com/huggingface/accelerate/pull/3146
• Trigger weights_only=True by default for all compatible objects by @​muellerzr in https://github.com/huggingface/accelerate/pull/3036
• Remove broken dynamo test by @​oraluben in https://github.com/huggingface/accelerate/pull/3155
• fix version check bug in get_xpu_available_memory by @​faaany in https://github.com/huggingface/accelerate/pull/3165
• enable cpu bnb distributed lora finetune by @​jiqing-feng in https://github.com/huggingface/accelerate/pull/3159
• [Utils] has_offloaded_params by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3188
• fix bnb by @​eljandoubi in https://github.com/huggingface/accelerate/pull/3186
• [docs] update neptune API by @​faaany in https://github.com/huggingface/accelerate/pull/3181
• docs: fix a wrong word in comment in src/accelerate/accelerate.py:1255 by @​Rebornix-zero in https://github.com/huggingface/accelerate/pull/3183
• [docs] use nn.module instead of tensor as model by @​faaany in https://github.com/huggingface/accelerate/pull/3157
• Fix typo by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3191
• MLU devices : Checks if mlu is available via an cndev-based check which won't trigger the drivers and leave mlu by @​huismiling in https://github.com/huggingface/accelerate/pull/3187
• update Megatron-LM plugin code to version 0.8.0 or higher. by @​eljandoubi in https://github.com/huggingface/accelerate/pull/3174
• 🚨 🚨 🚨 Goodbye Python 3.8! 🚨 🚨 🚨 by @​muellerzr in https://github.com/huggingface/accelerate/pull/3194
• Update transformers.deepspeed references from transformers 4.46.0 release by @​loadams in https://github.com/huggingface/accelerate/pull/3196
• eliminate dead code by @​statelesshz in https://github.com/huggingface/accelerate/pull/3198
• take torch.nn.Module model into account when moving to device by @​faaany in https://github.com/huggingface/accelerate/pull/3167
• [docs] add xpu part and fix bug in torchrun by @​faaany in https://github.com/huggingface/accelerate/pull/3166
• Models With Tied Weights Need Re-Tieing After FSDP Param Init by @​fabianlim in https://github.com/huggingface/accelerate/pull/3154
• add the missing xpu for local sgd by @​faaany in https://github.com/huggingface/accelerate/pull/3163
• typo fix in big_modeling.py by @​a-r-r-o-w in https://github.com/huggingface/accelerate/pull/3207
• [Utils] align_module_device by @​kylesayrs in https://github.com/huggingface/accelerate/pull/3204

New Contributors

• @​mariusarvinte made their first contribution in https://github.com/huggingface/accelerate/pull/3114
• @​hlky made their first contribution in https://github.com/huggingface/accelerate/pull/3123
• @​dame-cell made their first contribution in https://github.com/huggingface/accelerate/pull/3149
• @​kylesayrs made their first contribution in https://github.com/huggingface/accelerate/pull/3188
• @​eljandoubi made their first contribution in https://github.com/huggingface/accelerate/pull/3186
• @​Rebornix-zero made their first contribution in https://github.com/huggingface/accelerate/pull/3183
• @​loadams made their first contribution in https://github.com/huggingface/accelerate/pull/3196

Full Changelog: huggingface/accelerate@v1.0.1...v1.1.0

bitsandbytes-foundation/bitsandbytes (bitsandbytes)

v0.45.0: : LLM.int8() support for H100; faster 4-bit/8-bit inference

Compare Source

Highlights

H100 Support for LLM.int8()

PR #​1401 brings full LLM.int8() support for NVIDIA Hopper GPUs such as the H100, H200, and H800!

As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.

Performance Improvements

This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.

The improvements were measured using the 🤗optimum-benchmark tool.

For more benchmark results, see benchmarking/README.md.

LLM.int8()

• Turing/Ampere/Ada: The observed per-token throughput is improved by 60-85%, while latency is decreased by 40-45%.
• H100: With our benchmarking of Llama 3.1 70B, we observed the new LLM.int8() to consistently outperform NF4 at batch size >= 8.

Example throughput improvement for Qwen 2.5 14B Instruct on RTX 4090:

• Batch size = 1: 9.05 tokens/s => 15.44 tokens/s
• Batch size = 8: 66.62 tokens/s => 110.95 tokens/s

Example throughput improvement for Qwen 2.5 3B Instruct on T4:

• Batch size = 1: 3.34 tokens/s => 5.98 tokens/s
• Batch size = 8: 24.28 tokens/s => 44.15 tokens/s

NF4/FP4

• Turing/Ampere/Ada: With batch size of 1, per-token throughput is improved by 10-25% and per-token latency is decreased by 10-20%.
• H100: Across all batch sizes, per-token throughput is improved by up to 28% and per-token latency is decreased by up to 22%.

Example throughput improvement for Qwen 2.5 14B Instruct on RTX 4090:

• Batch size = 1: 31.46 tokens/s => 39.03 tokens/s
• Batch size = 8: 110.70 tokens/s => 111.29 tokens/s

Example throughput improvement for Qwen 2.5 3B Instruct on T4:

• Batch size = 1: 11.05 tokens/s => 13.58 tokens/s
• Batch size = 8: 69.8 tokens/s => 76.80 tokens/s

Changes

Packaging Changes

The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.

CUDA Toolkit Versions

• Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
• The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.

Breaking

🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.

New

• A new public API for int8 dequantization has been added: bitsandbytes.functional.int8_vectorwise_dequant(). This functionality is being integrated into 🤗PEFT and 🤗transformers.
• We've continued to make documentation updates. The bitsandbytes.functional module now has an API documentation page.

Deprecations

A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.

k-bit quantization

The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.

LLM.int8() deprecations:

As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.

The following relevant functions from bitsandbytes.functional are now deprecated :

• dequant_min_max
• dequantize_no_absmax
• extract_outliers
• get_special_format_str
• get_transform_buffer
• get_transform_func
• mm_dequant (replacement: int8_mm_dequant)
• igemmlt (replacement: int8_linear_matmul)
• nvidia_transform
• transform
• quantize_no_absmax
• vectorwise_dequant
• vectorwise_quant (~replacement: int8_vectorwise_quant)
• vectorwise_mm_dequant (~replacement: int8_mm_dequant)

General Deprecations

Additionally the following functions from bitsandbytes.functional are deprecated:

• _mul
• arange
• post_call
• pre_call

What's Changed

• refine docs for multi-backend alpha release by @​Titus-von-Koeller in https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1380
• README: Replace special Unicode text symbols with regular characters by @​akx in https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1385
• Update CI tools & fix typos by @​akx in https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1386
• Fix invalid escape sequence warning in Python 3.12 by @​oshiteku in https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1420
• [Build] Add CUDA 12.6.2 build; update 12.5.0 to 12.5.1 by @​matthewdouglas in https://github.com/bitsandbytes-foundation/bitsandbytes/pull/1431
• LLM.int8() Refactoring: Part 1 by @​matthewdouglas in [https://github.com/bitsandbytes-foundation/bitsandbyte

---

Configuration

📅 Schedule: Branch creation - "* 0-3 * * 1" (UTC), Automerge - At any time (no schedule defined).

🚦 Automerge: Enabled.

♻ Rebasing: Whenever PR is behind base branch, or you tick the rebase/retry checkbox.

👻 Immortal: This PR will be recreated if closed unmerged. Get config help if that's undesired.

---

• If you want to rebase/retry this PR, check this box

---

This PR was generated by Mend Renovate. View the repository job log.

[bourgeoisor]

Looks like most of the issues look like this:

6.059 The conflict is caused by:
6.059     langchain 0.3.0 depends on langchain-core<0.4.0 and >=0.3.0
6.059     langchain-community 0.3.0 depends on langchain-core<0.4.0 and >=0.3.0
6.059     langchain-google-vertexai 1.0.10 depends on langchain-core<0.3 and >=0.2.33

Might need to manually bump langchain-google-vertexai, latest is 2.0.1