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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
17 lines
374 B
Python
17 lines
374 B
Python
import os
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import subprocess
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from pathlib import Path
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def main():
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path_of_script = Path(__file__).parent.resolve()
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# Build image
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os.chdir(path_of_script)
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command = f'docker build --tag cml_client_cifar --file "{path_of_script}/Dockerfile.client" .'
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print(command)
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subprocess.check_output(command, shell=True)
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if __name__ == "__main__":
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main()
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