mirror of
https://github.com/huggingface/optimum.git
synced 2026-10-12 02:15:46 +00:00
Alvaro MoranandClaude Opus 5
261e9102fa
fix(exporters): use hub's httpx re-export instead of requests tasks.py imported requests at module level while setup.py only declared it under the tests extra, forcing downstream projects to pin it themselves. The except clauses were also dead code with huggingface_hub v1, which raises httpx.ConnectError rather than requests' ConnectionError, so the snapshot_download cache fallback never fired when the Hub was unreachable. They now catch httpx.ConnectError and httpx.TimeoutException, mirroring what the hub does internally in file_download.py. httpx is imported through huggingface_hub.utils so that optimum follows the hub to httpx2 in its v2.x. That re-export landed in v1.31.0, hence the floor bump. The `raise ConnectionError(...)` in determine_framework now resolves to the builtin, which huggingface_hub's OfflineModeIsEnabled subclasses too. Co-authored-by: Claude Opus 5 (1M context) <[email protected]>
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
import re
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from setuptools import find_namespace_packages, setup
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# Ensure we match the version set in src/optimum/version.py
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try:
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filepath = "optimum/version.py"
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with open(filepath) as version_file:
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(__version__,) = re.findall('__version__ = "(.*)"', version_file.read())
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except Exception as error:
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assert False, "Error: Could not open '%s' due %s\n" % (filepath, error)
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REQUIRED_PKGS = [
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"transformers>=4.29",
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"torch>=1.11",
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"packaging",
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"numpy",
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"huggingface_hub>=1.31.0",
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]
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TESTS_REQUIRE = [
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"pytest",
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"accelerate",
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"parameterized",
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"pytest-xdist",
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"Pillow",
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"sacremoses",
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"torchvision",
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"torchaudio",
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"einops",
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"timm",
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"scikit-learn",
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"sentencepiece",
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"rjieba",
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"hf_xet",
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]
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QUALITY_REQUIRE = ["black~=23.1", "ruff==0.1.5"]
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BENCHMARK_REQUIRE = ["optuna", "tqdm", "scikit-learn", "seqeval", "torchvision", "evaluate>=0.2.0"]
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EXTRAS_REQUIRE = {
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"amd": "optimum-amd",
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"furiosa": "optimum-furiosa",
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"graphcore": "optimum-graphcore",
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"habana": "optimum-habana>=1.17.0",
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"intel": "optimum-intel>=1.23.0",
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"nncf": "optimum-intel[nncf]>=1.23.0",
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"neural-compressor": "optimum-intel[neural-compressor]>=1.23.0",
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"onnx": "optimum-onnx",
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"onnxruntime": "optimum-onnx[onnxruntime]",
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"onnxruntime-gpu": "optimum-onnx[onnxruntime-gpu]",
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"openvino": "optimum-intel[openvino]>=1.23.0",
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"quanto": "optimum-quanto>=0.2.4",
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###########################################################################
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"dev": TESTS_REQUIRE + QUALITY_REQUIRE,
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"tests": TESTS_REQUIRE,
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"quality": QUALITY_REQUIRE,
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"benchmark": BENCHMARK_REQUIRE,
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"doc-build": ["accelerate"],
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}
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setup(
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name="optimum",
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version=__version__,
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description="Optimum Library is an extension of the Hugging Face Transformers library, providing a framework to "
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"integrate third-party libraries from Hardware Partners and interface with their specific "
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"functionality.",
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long_description=open("README.md", "r", encoding="utf-8").read(),
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long_description_content_type="text/markdown",
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classifiers=[
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"Development Status :: 5 - Production/Stable",
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"License :: OSI Approved :: Apache Software License",
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"Intended Audience :: Developers",
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"Intended Audience :: Education",
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"Intended Audience :: Science/Research",
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"Operating System :: OS Independent",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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],
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keywords="transformers, quantization, pruning, optimization, training, inference, onnx, onnx runtime, intel, "
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"habana, graphcore, neural compressor, ipu, hpu",
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url="https://github.com/huggingface/optimum",
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author="HuggingFace Inc. Special Ops Team",
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author_email="[email protected]",
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license="Apache",
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packages=find_namespace_packages(include=["optimum*"]),
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install_requires=REQUIRED_PKGS,
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extras_require=EXTRAS_REQUIRE,
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python_requires=">=3.9.0",
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include_package_data=True,
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zip_safe=False,
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entry_points={"console_scripts": ["optimum-cli=optimum.commands.optimum_cli:main"]},
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)
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