DeepLearningExamples/PyTorch/SpeechSynthesis/FastPitch/export_torchscript.py
2020-07-04 02:24:45 +02:00

62 lines
2.8 KiB
Python

# *****************************************************************************
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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# *****************************************************************************
import argparse
import torch
from inference import load_and_setup_model
def parse_args(parser):
parser.add_argument('--generator-name', type=str, required=True,
choices=('Tacotron2', 'FastPitch'), help='model name')
parser.add_argument('--generator-checkpoint', type=str, required=True,
help='full path to the generator checkpoint file')
parser.add_argument('-o', '--output', type=str, default="trtis_repo/tacotron/1/model.pt",
help='filename for the Tacotron 2 TorchScript model')
parser.add_argument('--amp', action='store_true',
help='inference with AMP')
return parser
def main():
parser = argparse.ArgumentParser(description='Export models to TorchScript')
parser = parse_args(parser)
args = parser.parse_args()
model = load_and_setup_model(
args.generator_name, parser, args.generator_checkpoint,
args.amp, device='cpu', forward_is_infer=True, polyak=False,
jitable=True)
torch.jit.save(torch.jit.script(model), args.output)
if __name__ == '__main__':
main()