from pathlib import Path
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import os
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import argparse
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from funasr.utils.types import str2bool
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parser = argparse.ArgumentParser()
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parser.add_argument('--model-name', type=str, required=True)
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parser.add_argument('--export-dir', type=str, required=True)
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parser.add_argument('--type', type=str, default='onnx', help='["onnx", "torch"]')
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parser.add_argument('--device', type=str, default='cpu', help='["cpu", "cuda"]')
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parser.add_argument('--quantize', type=str2bool, default=False, help='export quantized model')
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parser.add_argument('--fallback-num', type=int, default=0, help='amp fallback number')
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parser.add_argument('--audio_in', type=str, default=None, help='["wav", "wav.scp"]')
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parser.add_argument('--calib_num', type=int, default=200, help='calib max num')
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args = parser.parse_args()
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model_dir = args.model_name
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if not Path(args.model_name).exists():
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from modelscope.hub.snapshot_download import snapshot_download
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try:
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model_dir = snapshot_download(args.model_name, cache_dir=args.export_dir)
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except:
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raise "model_dir must be model_name in modelscope or local path downloaded from modelscope, but is {}".format \
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(model_dir)
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model_file = os.path.join(model_dir, 'model.onnx')
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if args.quantize:
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model_file = os.path.join(model_dir, 'model_quant.onnx')
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if not os.path.exists(model_file):
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print(".onnx is not exist, begin to export onnx")
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from funasr.export.export_model import ModelExport
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export_model = ModelExport(
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cache_dir=args.export_dir,
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onnx=True,
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device="cpu",
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quant=args.quantize,
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)
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export_model.export(model_dir)
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