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Merge branch 'master' into numpy_scalars
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.github/workflows/ci-tests-fabric.yml

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uv pip install ".[${EXTRA_PREFIX}test,${EXTRA_PREFIX}strategies]" \
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--upgrade \
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--find-links="${TORCH_URL}"
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# ensure pkg_resources is available for older python versions & packages like onnxruntime that require it
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uv pip install "setuptools<80.10.3"
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uv pip list
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- name: Adjust tests

.github/workflows/ci-tests-pytorch.yml

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--upgrade \
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--find-links="${TORCH_URL}" \
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--find-links="https://download.pytorch.org/whl/torch-tensorrt"
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# ensure pkg_resources is available for older python versions & packages like onnxruntime that require it
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uv pip install "setuptools<80.10.3"
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uv pip list
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- name: Drop LAI from extensions

.lightning/workflows/fabric.yml

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extra=$(python -c "print({'lightning': 'fabric-'}.get('${PACKAGE_NAME}', ''))")
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uv pip install ".[${extra}dev]" --upgrade
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# ensure pkg_resources is available for older python versions & packages like onnxruntime that require it
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uv pip install "setuptools<80.10.3"
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python requirements/collect_env_details.py
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python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu >= 2, f'GPU: {mgpu}'"
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python -c "import bitsandbytes"

.lightning/workflows/pytorch.yml

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uv pip uninstall pytorch-lightning
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fi
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# ensure pkg_resources is available for older python versions & packages like onnxruntime that require it
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uv pip install "setuptools<80.10.3"
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python requirements/collect_env_details.py
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python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu >= 2, f'GPU: {mgpu}'"
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python requirements/pytorch/check-avail-extras.py

pyproject.toml

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"ignore::FutureWarning:onnxscript", # Temporary ignore until onnxscript is updated
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"ignore:You are using `torch.load` with `weights_only=False`.*:FutureWarning",
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"ignore::FutureWarning:torch.distributed.algorithms.ddp_comm_hooks",
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# PyTorch pytree LeafSpec deprecation triggered during doctest
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"ignore:`isinstance\\(treespec, LeafSpec\\)` is deprecated.*:FutureWarning",
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]
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xfail_strict = true
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junit_duration_report = "call"

requirements/ci.txt

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setuptools <80.9.1
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setuptools <80.10.3
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wheel <0.46.0
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awscli >=1.30.0, <1.45.0
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twine ==6.2.0

requirements/collect_env_details.py

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import os
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import platform
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import sys
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from importlib.metadata import distributions
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import pkg_resources
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import torch
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sys.path += [os.path.abspath(".."), os.path.abspath("")]
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def info_packages() -> dict:
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"""Get name and version of all installed packages."""
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packages = {}
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for dist in pkg_resources.working_set:
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package = dist.as_requirement()
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packages[package.key] = package.specs[0][1]
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return packages
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return {dist.metadata["Name"]: dist.version for dist in distributions()}
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def nice_print(details: dict, level: int = 0) -> list:

requirements/fabric/examples.txt

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# NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
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# in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
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torchvision >=0.16.0, <0.25.0
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torchvision >=0.16.0, <0.26.0
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torchmetrics >=0.10.0, <1.9.0

requirements/pytorch/examples.txt

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# in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
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requests <2.33.0
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torchvision >=0.16.0, <0.25.0
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torchvision >=0.16.0, <0.26.0
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ipython[all] >=8.0.0, <10.0.0
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torchmetrics >=0.10.0, <1.9.0

requirements/pytorch/loggers.info

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# all supported loggers. this list is here as a reference, but they are not installed in CI
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litlogger >= 0.1.2
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litlogger >= 0.1.7
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neptune >=1.0.0
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comet-ml >=3.31.0
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mlflow >=1.0.0

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