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https://github.com/luxfhe/ml-sdk.git
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zeekay
bde2e2531b
Machine Learning with FHE - fork of Zama Concrete-ML - Built-in FHE-friendly ML models - scikit-learn compatible API - PyTorch model conversion - Quantization-aware training
102 lines
2.5 KiB
Python
102 lines
2.5 KiB
Python
"""Script to generate custom GitHub actions test matrices."""
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import argparse
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import enum
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import json
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from pathlib import Path
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class EnumEncoder(json.JSONEncoder):
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"""JSON encoder for python enumerates"""
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def default(self, o):
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if isinstance(o, enum.Enum):
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return o.value
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return json.JSONEncoder.default(self, o)
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class PythonVersion(enum.Enum):
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"""Enumerate for python versions"""
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V_3_8 = "3.8"
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V_3_9 = "3.9"
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V_3_10 = "3.10"
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V_3_11 = "3.11"
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V_3_12 = "3.12"
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class OS(enum.Enum):
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"""Enumerate for OS"""
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LINUX = "linux"
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MACOS = "macos"
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OS_VERSIONS = {
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OS.LINUX: "ubuntu-20.04",
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OS.MACOS: ["macos-13", "macos-14"],
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}
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def main(args):
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"""Entry point to generate CI test matrix.
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Args:
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args (List[str]): a list of arguments
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"""
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github_action_matrix = []
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for python_version in args.linux_python_versions:
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github_action_matrix.append(
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{
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"os_kind": OS.LINUX,
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"runs_on": OS_VERSIONS[OS.LINUX],
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"python_version": python_version,
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}
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)
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for python_version in args.macos_python_versions:
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for macos_os in OS_VERSIONS[OS.MACOS]:
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github_action_matrix.append(
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{
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"os_kind": OS.MACOS,
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"runs_on": macos_os,
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"python_version": python_version,
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}
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)
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print(json.dumps(github_action_matrix, indent=4, cls=EnumEncoder))
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output_json_path = args.output_json.resolve()
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with open(output_json_path, "w", encoding="utf-8") as f:
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json.dump(github_action_matrix, f, cls=EnumEncoder)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser("Generate GHA test matrices", allow_abbrev=False)
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parser.add_argument(
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"--macos-python-versions",
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dest="macos_python_versions",
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nargs="*",
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required=True,
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type=PythonVersion,
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default=[],
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choices=set(PythonVersion),
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help="Python versions to use on mac systems",
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)
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parser.add_argument(
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"--linux-python-versions",
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dest="linux_python_versions",
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nargs="*",
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required=True,
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type=PythonVersion,
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default=[],
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choices=set(PythonVersion),
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help="Python versions to use on linux systems",
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)
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parser.add_argument(
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"--output-json", type=Path, required=True, help="Where to output the matrix as json data"
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)
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cli_args = parser.parse_args()
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main(cli_args)
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