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| # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. | |
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| # ***************************************************************************** | |
| import os | |
| from scipy.io.wavfile import write | |
| import torch | |
| from mel2samp import files_to_list, MAX_WAV_VALUE | |
| from denoiser import Denoiser | |
| def main(mel_files, waveglow_path, sigma, output_dir, sampling_rate, is_fp16, | |
| denoiser_strength): | |
| mel_files = files_to_list(mel_files) | |
| waveglow = torch.load(waveglow_path)['model'] | |
| waveglow = waveglow.remove_weightnorm(waveglow) | |
| waveglow.cuda().eval() | |
| if is_fp16: | |
| from apex import amp | |
| waveglow, _ = amp.initialize(waveglow, [], opt_level="O3") | |
| if denoiser_strength > 0: | |
| denoiser = Denoiser(waveglow).cuda() | |
| for i, file_path in enumerate(mel_files): | |
| file_name = os.path.splitext(os.path.basename(file_path))[0] | |
| mel = torch.load(file_path) | |
| mel = torch.autograd.Variable(mel.cuda()) | |
| mel = torch.unsqueeze(mel, 0) | |
| mel = mel.half() if is_fp16 else mel | |
| with torch.no_grad(): | |
| audio = waveglow.infer(mel, sigma=sigma) | |
| if denoiser_strength > 0: | |
| audio = denoiser(audio, denoiser_strength) | |
| audio = audio * MAX_WAV_VALUE | |
| audio = audio.squeeze() | |
| audio = audio.cpu().numpy() | |
| audio = audio.astype('int16') | |
| audio_path = os.path.join( | |
| output_dir, "{}_synthesis.wav".format(file_name)) | |
| write(audio_path, sampling_rate, audio) | |
| print(audio_path) | |
| if __name__ == "__main__": | |
| import argparse | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('-f', "--filelist_path", required=True) | |
| parser.add_argument('-w', '--waveglow_path', | |
| help='Path to waveglow decoder checkpoint with model') | |
| parser.add_argument('-o', "--output_dir", required=True) | |
| parser.add_argument("-s", "--sigma", default=1.0, type=float) | |
| parser.add_argument("--sampling_rate", default=22050, type=int) | |
| parser.add_argument("--is_fp16", action="store_true") | |
| parser.add_argument("-d", "--denoiser_strength", default=0.0, type=float, | |
| help='Removes model bias. Start with 0.1 and adjust') | |
| args = parser.parse_args() | |
| main(args.filelist_path, args.waveglow_path, args.sigma, args.output_dir, | |
| args.sampling_rate, args.is_fp16, args.denoiser_strength) | |