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from model import SampleRNN, Predictor, Generator
from trainer import Trainer, sequence_nll_loss
from dataset import FolderDataset, DataLoader
import torch
from torch.utils.trainer import plugins
from librosa.output import write_wav
from time import time
def main():
model = SampleRNN(
frame_sizes=[16, 4], n_rnn=1, dim=1024, learn_h0=True, q_levels=256
)
predictor = Predictor(model).cuda()
predictor.load_state_dict(torch.load('model.tar'))
generator = Generator(predictor.model, cuda=True)
t = time()
samples = generator(5, 16000)
print('generated in {}s'.format(time() - t))
write_wav(
'sample.wav',
samples.cpu().float().numpy()[0, :],
sr=16000,
norm=True
)
if __name__ == '__main__':
main()
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