Python Hps.get_tuple Examples

Example #1

File: utt.py Project: Anjalikamath/voice_conversionn

def get_model(hps_path, model_path):
	hps = Hps()
	hps.load(hps_path)
	hps_tuple = hps.get_tuple()
	solver = Solver(hps_tuple, None, None)
	solver.load_model(model_path)
	return solver

Example #2

def get_model(
        hps_path='./hps/vctk.json',
        model_path='/storage/model/voice_conversion/vctk/clf/model.pkl-109999'
):
    hps = Hps()
    hps.load(hps_path)
    hps_tuple = hps.get_tuple()
    solver = Solver(hps_tuple, None)
    solver.load_model(model_path)
    return solver

Example #3

File: test.py Project: AlvinYC/cei_voice_converter

    parser.add_argument('-hps',
                        help='The path of hyper-parameter set',
                        default='vctk.json')
    parser.add_argument('-model', '-m', help='The path of model checkpoint')
    parser.add_argument('-source', '-s', help='The path of source .wav file')
    parser.add_argument(
        '-target',
        '-t',
        help=
        'Target speaker id (integer). Same order as the speaker list when preprocessing (en_speaker_used.txt)'
    )
    parser.add_argument('-output', '-o', help='output .wav path')
    parser.add_argument('-sample_rate', '-sr', default=16000, type=int)
    parser.add_argument('--use_gen', default=True, action='store_true')

    args = parser.parse_args()

    hps = Hps()
    hps.load(args.hps)
    hps_tuple = hps.get_tuple()
    solver = Solver(hps_tuple, None)
    solver.load_model(args.model)
    _, spec = get_spectrograms(args.source)
    spec_expand = np.expand_dims(spec, axis=0)
    spec_tensor = torch.from_numpy(spec_expand).type(torch.FloatTensor)
    c = Variable(torch.from_numpy(np.array([int(args.target)]))).cuda()
    result = solver.test_step(spec_tensor, c, gen=args.use_gen)
    result = result.squeeze(axis=0).transpose((1, 0))
    wav_data = spectrogram2wav(result)
    write(args.output, rate=args.sample_rate, data=wav_data)