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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
62 lines
1.5 KiB
Python
62 lines
1.5 KiB
Python
"""Helper script to disable admonitions but keep line numbers untouched."""
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import argparse
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import multiprocessing
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import re
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import sys
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from pathlib import Path
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def process_file(file_str: str):
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"""Deactivate admonitions in a file.
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Args:
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file_str (str): the path to the file to process.
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Returns:
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True if everything went alright.
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"""
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verbose = False
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file_path = Path(file_str).resolve()
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if verbose:
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print(f"Removing admonitions for: {str(file_path)}")
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file_content = None
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with open(file_path, "r", encoding="utf-8") as f:
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file_content = "".join(f.readlines())
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# Check https://regex101.com/ with python gms flags to understand why this works
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processed_content = re.sub(
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r"(```{)(.*?)(```)", r"ignore\1\2ignore\3", file_content, flags=re.DOTALL
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)
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with open(file_path, "w", encoding="utf-8") as f:
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f.write(processed_content)
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return True
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def main(args):
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"""Entry point.
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Args:
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args: a Namespace object
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"""
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with multiprocessing.Pool(multiprocessing.cpu_count()) as pool:
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res = pool.map(process_file, args.files)
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# Exit 0 if all went well as True == 1
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sys.exit(not all(res))
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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"Deactivate admonitions without changing line numbers", allow_abbrev=False
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)
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parser.add_argument(
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"--files", type=str, nargs="+", required=True, help="The files to modify in place"
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)
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cli_args = parser.parse_args()
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main(cli_args)
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