Fabio
c36510c21e
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32 lines
1.2 KiB
Python
32 lines
1.2 KiB
Python
#!/usr/bin/env python3
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"""Convert the three official OpenWakeWord Alexa ONNX checkpoints into one GGUF."""
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import argparse
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from pathlib import Path
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import sys
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import numpy as np
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from conversion import write_model
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--source-repo", type=Path, required=True)
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parser.add_argument("--models", type=Path, required=True)
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parser.add_argument("--output", type=Path, required=True)
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args = parser.parse_args()
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sys.path.insert(0, str(args.source_repo.resolve()))
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from openwakeword.model import Model
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# The official initializer computes features from random startup noise. Cache a
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# fixed initialization so backend A/B runs have identical state and no startup inference.
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np.random.seed(0)
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model = Model(wakeword_models=[str(args.models / "alexa_v0.1.onnx")],
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melspec_model_path=str(args.models / "melspectrogram.onnx"),
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embedding_model_path=str(args.models / "embedding_model.onnx"),
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inference_framework="onnx", ncpu=1)
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args.output.parent.mkdir(parents=True, exist_ok=True)
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write_model(args.models, args.output, model.preprocessor.feature_buffer)
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if __name__ == "__main__":
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main()
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