mirror of
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
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
import os
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import shutil
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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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files = [
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"models/__init__.py",
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"models/cnv_2w2a.ini",
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"models/common.py",
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"models/model.py",
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"models/tensor_norm.py",
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"experiments/CNV_2W2A_2W2A_20221114_131345/checkpoints/best.tar",
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]
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# Copy files
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for file_name in files:
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source = Path(path_of_script / f"../../cifar/cifar_brevitas_training/{file_name}").resolve()
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target = Path(path_of_script / file_name).resolve()
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if not target.exists():
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print(f"{source} -> {target}")
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target.parent.mkdir(parents=True, exist_ok=True)
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shutil.copyfile(src=source, dst=target)
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# Build image
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os.chdir(path_of_script)
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command = f'docker build --tag compile_cifar --file "{path_of_script}/Dockerfile.compile" . && \
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docker run --name compile_cifar compile_cifar && \
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docker cp compile_cifar:/project/dev . && \
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docker rm "$(docker ps -a --filter name=compile_cifar -q)"'
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subprocess.check_output(command, shell=True)
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# Remove files
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for file_name in files:
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target = Path(path_of_script / file_name).resolve()
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target.unlink()
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if __name__ == "__main__":
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main()
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