| | |
| | | self, |
| | | cache_dir: Union[Path, str] = None, |
| | | onnx: bool = True, |
| | | device: str = "cpu", |
| | | quant: bool = True, |
| | | fallback_num: int = 0, |
| | | audio_in: str = None, |
| | |
| | | ) |
| | | print("output dir: {}".format(self.cache_dir)) |
| | | self.onnx = onnx |
| | | self.device = device |
| | | self.quant = quant |
| | | self.fallback_num = fallback_num |
| | | self.frontend = None |
| | |
| | | dummy_input = model.get_dummy_inputs(enc_size) |
| | | else: |
| | | dummy_input = model.get_dummy_inputs() |
| | | |
| | | if self.device == 'cuda': |
| | | model = model.cuda() |
| | | dummy_input = tuple([i.cuda() for i in dummy_input]) |
| | | |
| | | # model_script = torch.jit.script(model) |
| | | model_script = torch.jit.trace(model, dummy_input) |
| | |
| | | parser.add_argument('--model-name', type=str, required=True) |
| | | parser.add_argument('--export-dir', type=str, required=True) |
| | | parser.add_argument('--type', type=str, default='onnx', help='["onnx", "torch"]') |
| | | parser.add_argument('--device', type=str, default='cpu', help='["cpu", "cuda"]') |
| | | parser.add_argument('--quantize', type=str2bool, default=False, help='export quantized model') |
| | | parser.add_argument('--fallback-num', type=int, default=0, help='amp fallback number') |
| | | parser.add_argument('--audio_in', type=str, default=None, help='["wav", "wav.scp"]') |
| | |
| | | export_model = ModelExport( |
| | | cache_dir=args.export_dir, |
| | | onnx=args.type == 'onnx', |
| | | device=args.device, |
| | | quant=args.quantize, |
| | | fallback_num=args.fallback_num, |
| | | audio_in=args.audio_in, |