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build(deps): bump the python-packages group with 4 updates #42

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merged 1 commit into from
Nov 5, 2024
Merged

build(deps): bump the python-packages group with 4 updates #42

merged 1 commit into from
Nov 5, 2024

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@dependabot dependabot bot commented on behalf of github Nov 1, 2024

Bumps the python-packages group with 4 updates: openai, pytest-cov, torch and transformers.

Updates openai from 1.50.2 to 1.53.0

Release notes

Sourced from openai's releases.

v1.53.0

1.53.0 (2024-10-30)

Full Changelog: v1.52.2...v1.53.0

Features

  • api: add new, expressive voices for Realtime and Audio in Chat Completions (7cf0a49)

Chores

v1.52.2

1.52.2 (2024-10-23)

Full Changelog: v1.52.1...v1.52.2

Chores

v1.52.1

1.52.1 (2024-10-22)

Full Changelog: v1.52.0...v1.52.1

Bug Fixes

  • client/async: correctly retry in all cases (#1803) (9fe3f3f)

Chores

v1.52.0

1.52.0 (2024-10-17)

Full Changelog: v1.51.2...v1.52.0

Features

  • api: add gpt-4o-audio-preview model for chat completions (#1796) (fbf1e0c)

... (truncated)

Changelog

Sourced from openai's changelog.

1.53.0 (2024-10-30)

Full Changelog: v1.52.2...v1.53.0

Features

  • api: add new, expressive voices for Realtime and Audio in Chat Completions (7cf0a49)

Chores

1.52.2 (2024-10-23)

Full Changelog: v1.52.1...v1.52.2

Chores

1.52.1 (2024-10-22)

Full Changelog: v1.52.0...v1.52.1

Bug Fixes

  • client/async: correctly retry in all cases (#1803) (9fe3f3f)

Chores

1.52.0 (2024-10-17)

Full Changelog: v1.51.2...v1.52.0

Features

  • api: add gpt-4o-audio-preview model for chat completions (#1796) (fbf1e0c)

1.51.2 (2024-10-08)

Full Changelog: v1.51.1...v1.51.2

... (truncated)

Commits

Updates pytest-cov from 5.0.0 to 6.0.0

Changelog

Sourced from pytest-cov's changelog.

6.0.0 (2024-10-29)

  • Updated various documentation inaccuracies, especially on subprocess handling.
  • Changed fail under checks to use the precision set in the coverage configuration. Now it will perform the check just like coverage report would.
  • Added a --cov-precision cli option that can override the value set in your coverage configuration.
  • Dropped support for now EOL Python 3.8.
Commits
  • 9540437 Bump version: 5.0.0 → 6.0.0
  • 9f81754 Further trim down envs and drop Python 3.8.
  • b12b5ec Update conf.
  • 23f4b27 Update changelog.
  • 291a04f Bump test deps and trim config.
  • 08f1101 Add --cov-precision option. Close #655.
  • 76fe2a7 Move the warnings/errors in a place that doesn't import anything.
  • a9ea7b7 Implement error/warning for the bad dynamic_context being set in config.
  • c299e01 Add explicit suffixing to make it easier to see the identify the sources/usag...
  • c87e546 Add reproducer for weird xdist dynamic_context interaction. Ref #604.
  • Additional commits viewable in compare view

Updates torch from 2.4.1 to 2.5.1

Release notes

Sourced from torch's releases.

PyTorch 2.5.1: bug fix release

This release is meant to fix the following regressions:

Besides the regression fixes, the release includes several documentation updates.

See release tracker pytorch/pytorch#132400 for additional information.

PyTorch 2.5.0 Release, SDPA CuDNN backend, Flex Attention

PyTorch 2.5 Release Notes

  • Highlights
  • Backwards Incompatible Change
  • Deprecations
  • New Features
  • Improvements
  • Bug fixes
  • Performance
  • Documentation
  • Developers
  • Security

Highlights

We are excited to announce the release of PyTorch® 2.5! This release features a new CuDNN backend for SDPA, enabling speedups by default for users of SDPA on H100s or newer GPUs. As well, regional compilation of torch.compile offers a way to reduce the cold start up time for torch.compile by allowing users to compile a repeated nn.Module (e.g. a transformer layer in LLM) without recompilations. Finally, TorchInductor CPP backend offers solid performance speedup with numerous enhancements like FP16 support, CPP wrapper, AOT-Inductor mode, and max-autotune mode. This release is composed of 4095 commits from 504 contributors since PyTorch 2.4. We want to sincerely thank our dedicated community for your contributions. As always, we encourage you to try these out and report any issues as we improve 2.5. More information about how to get started with the PyTorch 2-series can be found at our Getting Started page. As well, please check out our new ecosystem projects releases with TorchRec and TorchFix.

Beta Prototype
CuDNN backend for SDPA FlexAttention
torch.compile regional compilation without recompilations Compiled Autograd
TorchDynamo added support for exception handling & MutableMapping types Flight Recorder
TorchInductor CPU backend optimization Max-autotune Support on CPU with GEMM Template
TorchInductor on Windows
FP16 support on CPU path for both eager mode and TorchInductor CPP backend
Autoload Device Extension
Enhanced Intel GPU support

*To see a full list of public feature submissions click here.

BETA FEATURES

[Beta] CuDNN backend for SDPA

The cuDNN "Fused Flash Attention" backend was landed for torch.nn.functional.scaled_dot_product_attention. On NVIDIA H100 GPUs this can provide up to 75% speed-up over FlashAttentionV2. This speedup is enabled by default for all users of SDPA on H100 or newer GPUs.

[Beta] torch.compile regional compilation without recompilations

Regional compilation without recompilations, via torch._dynamo.config.inline_inbuilt_nn_modules which default to True in 2.5+. This option allows users to compile a repeated nn.Module (e.g. a transformer layer in LLM) without recompilations. Compared to compiling the full model, this option can result in smaller compilation latencies with 1%-5% performance degradation compared to full model compilation.

... (truncated)

Commits

Updates transformers from 4.45.1 to 4.46.1

Release notes

Sourced from transformers's releases.

Patch release v4.46.1

Patch release v4.4.61

This is mostly for fx and onnx issues!

** Fix regression loading dtype #34409 by @​SunMarc ** LLaVa: latency issues #34460 by @​zucchini-nlp ** Fix pix2struct #34374 by @​IlyasMoutawwakil ** Fix onnx non-exposable inplace aten op #34376 by @​IlyasMoutawwakil ** Fix torch.fx issue related to the new loss_kwargs keyword argument #34380 by @​michaelbenayoun

Release v4.46.0

New model additions

Moshi

The Moshi model was proposed in Moshi: a speech-text foundation model for real-time dialogue by Alexandre Défossez, Laurent Mazaré, Manu Orsini, Amélie Royer, Patrick Pérez, Hervé Jégou, Edouard Grave and Neil Zeghidour.

Moshi is a speech-text foundation model that casts spoken dialogue as speech-to-speech generation. Starting from a text language model backbone, Moshi generates speech as tokens from the residual quantizer of a neural audio codec, while modeling separately its own speech and that of the user into parallel streams. This allows for the removal of explicit speaker turns, and the modeling of arbitrary conversational dynamics. Moshi also predicts time-aligned text tokens as a prefix to audio tokens. This “Inner Monologue” method significantly improves the linguistic quality of generated speech and provides streaming speech recognition and text-to-speech. As a result, Moshi is the first real-time full-duplex spoken large language model, with a theoretical latency of 160ms, 200ms in practice.

image

Zamba

Zamba-7B-v1 is a hybrid between state-space models (Specifically Mamba) and transformer, and was trained using next-token prediction. Zamba uses a shared transformer layer after every 6 mamba blocks. It uses the Mistral v0.1 tokenizer. We came to this architecture after a series of ablations at small scales. Zamba-7B-v1 was pre-trained on 1T tokens of text and code data.

GLM

The GLM Model was proposed in ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools by GLM Team, THUDM & ZhipuAI.

The abstract from the paper starts with the following:

... (truncated)

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build(deps): bump the python-packages group with 4 updates
97924cb 
Bumps the python-packages group with 4 updates: [openai](https://github.com/openai/openai-python), [pytest-cov](https://github.com/pytest-dev/pytest-cov), [torch](https://github.com/pytorch/pytorch) and [transformers](https://github.com/huggingface/transformers).


Updates `openai` from 1.50.2 to 1.53.0
- [Release notes](https://github.com/openai/openai-python/releases)
- [Changelog](https://github.com/openai/openai-python/blob/main/CHANGELOG.md)
- [Commits](openai/openai-python@v1.50.2...v1.53.0)

Updates `pytest-cov` from 5.0.0 to 6.0.0
- [Changelog](https://github.com/pytest-dev/pytest-cov/blob/master/CHANGELOG.rst)
- [Commits](pytest-dev/pytest-cov@v5.0.0...v6.0.0)

Updates `torch` from 2.4.1 to 2.5.1
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v2.4.1...v2.5.1)

Updates `transformers` from 4.45.1 to 4.46.1
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.45.1...v4.46.1)

---
updated-dependencies:
- dependency-name: openai
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: python-packages
- dependency-name: pytest-cov
  dependency-type: direct:development
  update-type: version-update:semver-major
  dependency-group: python-packages
- dependency-name: torch
  dependency-type: direct:development
  update-type: version-update:semver-minor
  dependency-group: python-packages
- dependency-name: transformers
  dependency-type: direct:development
  update-type: version-update:semver-minor
  dependency-group: python-packages
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Nov 1, 2024
@hangyav hangyav merged commit 9efa57c into main Nov 5, 2024
1 check passed
@dependabot dependabot bot deleted the dependabot/pip/python-packages-f6f8c2f27c branch November 5, 2024 17:07
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