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ML examples: - credit_scoring: Credit risk prediction with HMEQ data - disease_prediction: Healthcare ML on encrypted records - cifar: Encrypted image classification - federated_learning: Distributed FHE training - hybrid_model: Mixed FHE/plaintext inference Deployment: - breast_cancer: Cancer detection API - sentiment_analysis: Encrypted NLP - server: FHE inference server Blockchain: - hardhat-template: Solidity + FHE - react-template: Full dApp with FHE
19 lines
398 B
Python
19 lines
398 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 = (
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f'docker build --tag cml_client_breast_cancer --file "{path_of_script}/Dockerfile.client" .'
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)
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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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