tensorflow-onnx/pyproject.toml at main · onnx/tensorflow-onnx · GitHub

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# SPDX-License-Identifier: Apache-2.0

[build-system]
requires = ["setuptools>=77.0"]
build-backend = "setuptools.build_meta"

[project]
name = "tf2onnx"
dynamic = ["version"]
description = "Tensorflow to ONNX converter"
license = "Apache-2.0"
readme = "README.md"
requires-python = ">=3.10"
authors = [
    { name = "ONNX", email = "onnx-technical-discuss@lists.lfaidata.foundation" },
]
dependencies = [
    "numpy>=1.23.5",
    "onnx>=1.14.0",
    "requests",
    "flatbuffers>=1.12",
    # protobuf is intentionally not pinned here: it is a transitive dependency of
    # onnx, tensorflow and onnxruntime, which already agree on a compatible range.
    # Declaring our own floor only risks resolver conflicts (e.g. blocking newer
    # TensorFlow that requires a different protobuf) without adding safety.
]
classifiers = [
    "Development Status :: 5 - Production/Stable",
    "Intended Audience :: Developers",
    "Intended Audience :: Education",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering",
    "Topic :: Scientific/Engineering :: Mathematics",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Software Development",
    "Topic :: Software Development :: Libraries",
    "Topic :: Software Development :: Libraries :: Python Modules",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
]

[project.optional-dependencies]
test = [
    "graphviz",
    "parameterized",
    "pytest",
    "pytest-cov",
    "pyyaml"
]

[project.urls]
Homepage = "https://github.com/onnx/tensorflow-onnx"

[tool.setuptools.packages.find]

[tool.pytest.ini_options]
addopts = "--cov=tf2onnx"
norecursedirs = ["tests/keras2onnx_applications", "tests/keras2onnx_unit_tests"]
filterwarnings = [
    "ignore:.*AtomicFunction.*:pytest.PytestUnraisableExceptionWarning",
]

[tool.ruff]
target-version = "py310"
line-length = 120

[tool.ruff.lint]
select = [
    "E",  # pycodestyle errors
    "F",  # pyflakes
    "W",  # pycodestyle warnings
    "I",  # isort
]
ignore = [
    "E501",  # line too long (let formatter handle it)
    "E741",  # ambiguous variable name (too many in codebase)
    "F841",  # local variable assigned but never used (pylint didn't enforce)
]

[tool.ruff.lint.per-file-ignores]
"tf2onnx/version.py" = ["E", "F", "W", "I"]
"tf2onnx/tflite*" = ["E", "F", "W", "I"]
# Probe import used only to test availability of the optional package
"tests/common.py" = ["F401", "I001"]
# Bare except is intentional (tf.contrib may not exist in TF 2.x)
"tests/run_pretrained_models.py" = ["E722"]
# Test files: wildcard imports from common, lambda test helpers, bare excepts, etc.
"tests/test_*.py" = ["E701", "E722", "E731", "F403", "F405", "F811", "I001"]
# Legacy source files: patterns widespread in existing code, not worth fixing en masse
"tf2onnx/*.py" = ["E402", "E701", "E722", "E731", "F401", "I001"]
# Wildcard import from rewriter is intentional; all exported names are in __all__
"tf2onnx/tfonnx.py" = ["F403", "F405"]
# __init__.py re-exports: imports are for side-effects / re-export, not direct use
"tf2onnx/**/__init__.py" = ["F401"]
# Undefined names are conditional imports or skia-opt codepaths
"tf2onnx/onnx_opset/nn.py" = ["F821"]
"tf2onnx/optimizer/einsum_optimizer.py" = ["F821"]
# Single-line guards are idiomatic in these files
"tf2onnx/onnx_opset/math.py" = ["E701"]
"tf2onnx/rewriter/gemm_rewriter.py" = ["E701"]
# Tools: legacy scripts, bare excepts and redefined logging are intentional
"tools/*.py" = ["E722", "F811"]