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RelationRx / pyrelational

pyrelational is a python active learning library for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.
https://pyrelational.readthedocs.io
Apache License 2.0
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Update torch requirement from <2.3.0,>=1.9.0 to >=1.9.0,<2.5.0 in /requirements #182

Open dependabot[bot] opened 4 months ago

dependabot[bot] commented 4 months ago

Updates the requirements on torch to permit the latest version.

Release notes

Sourced from torch's releases.

PyTorch 2.4: Python 3.12, AOTInductor freezing, libuv backend for TCPStore

PyTorch 2.4 Release Notes

Highlights

We are excited to announce the release of PyTorch® 2.4! PyTorch 2.4 adds support for the latest version of Python (3.12) for torch.compile. AOTInductor freezing gives developers running AOTInductor more performance based optimizations by allowing the serialization of MKLDNN weights. As well, a new default TCPStore server backend utilizing libuv has been introduced which should significantly reduce initialization times for users running large-scale jobs. Finally, a new Python Custom Operator API makes it easier than before to integrate custom kernels into PyTorch, especially for torch.compile.

This release is composed of 3661 commits and 475 contributors since PyTorch 2.3. 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 2.4.

Tracked Regressions

Subproc exception with torch.compile and onnxruntime-training

There is a reported issue when using torch.compile if onnxruntime-training lib is installed. The issue will be fixed in v2.4.1. It can be solved locally by setting the environment variable TORCHINDUCTOR_WORKER_START=fork before executing the script.

cu118 wheels will not work with pre-cuda12 drivers

It was also reported that the new version of triton uses cuda features that are not compatible with pre-cuda12 drivers. In this case, the workaround is to set TRITON_PTXAS_PATH manually as follows (adapt the code according to the local installation path):

TRITON_PTXAS_PATH=/usr/local/lib/python3.10/site-packages/torch/bin/ptxas  python script.py

Backwards Incompatible Change

Python frontend

Default TreadPool size to number of physical cores (#125963)

Changed the default number of threads used for intra-op parallelism from the number of logical cores to the number of

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Changelog

Sourced from torch's changelog.

Releasing PyTorch

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

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Commits


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dependabot[bot] commented 4 months ago

The following labels could not be found: ci.

dependabot[bot] commented 2 months ago

A newer version of torch exists, but since this PR has been edited by someone other than Dependabot I haven't updated it. You'll get a PR for the updated version as normal once this PR is merged.