inference.py

# import sengiri
import re
import torch
import commons
import utils
from models import SynthesizerTrn
from text.symbols import symbols
from text import text_to_sequence


def get_text(text, hps):
    text_norm = text_to_sequence(text, hps.data.text_cleaners)
    if hps.data.add_blank:
        text_norm = commons.intersperse(text_norm, 0)
    text_norm = torch.LongTensor(text_norm)
    return text_norm


hps = utils.get_hparams_from_file(f"pretrained_model/arona_ms_istft_vits_config.json")
net_g = SynthesizerTrn(
    len(symbols),
    hps.data.filter_length // 2 + 1,
    hps.train.segment_size // hps.data.hop_length,
    n_speakers=hps.data.n_speakers,
    **hps.model).cuda()
_ = net_g.eval()

_ = utils.load_checkpoint(f"pretrained_model/arona_ms_istft_vits.pth", net_g, None)

text = '物語は嘘から始まる。'
SPEECH_SPEED = 1
stn_tst = get_text(text, hps)
with torch.no_grad():
    x_tst = stn_tst.cuda().unsqueeze(0)
    x_tst_lengths = torch.LongTensor([stn_tst.size(0)]).cuda()
    audio = net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.8, length_scale=1/SPEECH_SPEED)[0][0,0].data.cpu().float().numpy()