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import torch | |
# from inference.tts.fs import FastSpeechInfer | |
# from modules.tts.fs2_orig import FastSpeech2Orig | |
from inference.m4singer.base_svs_infer import BaseSVSInfer | |
from utils import load_ckpt | |
from utils.hparams import hparams | |
from usr.diff.shallow_diffusion_tts import GaussianDiffusion | |
from usr.diffsinger_task import DIFF_DECODERS | |
from modules.fastspeech.pe import PitchExtractor | |
import utils | |
class DiffSingerE2EInfer(BaseSVSInfer): | |
def build_model(self): | |
model = GaussianDiffusion( | |
phone_encoder=self.ph_encoder, | |
out_dims=hparams['audio_num_mel_bins'], denoise_fn=DIFF_DECODERS[hparams['diff_decoder_type']](hparams), | |
timesteps=hparams['timesteps'], | |
K_step=hparams['K_step'], | |
loss_type=hparams['diff_loss_type'], | |
spec_min=hparams['spec_min'], spec_max=hparams['spec_max'], | |
) | |
model.eval() | |
load_ckpt(model, hparams['work_dir'], 'model') | |
if hparams.get('pe_enable') is not None and hparams['pe_enable']: | |
self.pe = PitchExtractor().to(self.device) | |
utils.load_ckpt(self.pe, hparams['pe_ckpt'], 'model', strict=True) | |
self.pe.eval() | |
return model | |
def forward_model(self, inp): | |
sample = self.input_to_batch(inp) | |
txt_tokens = sample['txt_tokens'] # [B, T_t] | |
spk_id = sample.get('spk_ids') | |
with torch.no_grad(): | |
output = self.model(txt_tokens, spk_embed=spk_id, ref_mels=None, infer=True, | |
pitch_midi=sample['pitch_midi'], midi_dur=sample['midi_dur'], | |
is_slur=sample['is_slur']) | |
mel_out = output['mel_out'] # [B, T,80] | |
if hparams.get('pe_enable') is not None and hparams['pe_enable']: | |
f0_pred = self.pe(mel_out)['f0_denorm_pred'] # pe predict from Pred mel | |
else: | |
f0_pred = output['f0_denorm'] | |
wav_out = self.run_vocoder(mel_out, f0=f0_pred) | |
wav_out = wav_out.cpu().numpy() | |
return wav_out[0] | |
if __name__ == '__main__': | |
inp = { | |
'spk_name': 'Tenor-1', | |
'text': 'AP你要相信AP相信我们会像童话故事里AP', | |
'notes': 'rest | G#3 | A#3 C4 | D#4 | D#4 F4 | rest | E4 F4 | F4 | D#4 A#3 | A#3 | A#3 | C#4 | B3 C4 | C#4 | B3 C4 | A#3 | G#3 | rest', | |
'notes_duration': '0.14 | 0.47 | 0.1905 0.1895 | 0.41 | 0.3005 0.3895 | 0.21 | 0.2391 0.1809 | 0.32 | 0.4105 0.2095 | 0.35 | 0.43 | 0.45 | 0.2309 0.2291 | 0.48 | 0.225 0.195 | 0.29 | 0.71 | 0.14', | |
'input_type': 'word', | |
} | |
c = { | |
'spk_name': 'Tenor-1', | |
'text': '你要相信相信我们会像童话故事里', | |
'ph_seq': '<AP> n i iao iao x iang x in in <AP> x iang iang x in uo uo m en h uei x iang t ong ong h ua g u u sh i l i <AP>', | |
'note_seq': 'rest G#3 G#3 A#3 C4 D#4 D#4 D#4 D#4 F4 rest E4 E4 F4 F4 F4 D#4 A#3 A#3 A#3 A#3 A#3 C#4 C#4 B3 B3 C4 C#4 C#4 B3 B3 C4 A#3 A#3 G#3 G#3 rest', | |
'note_dur_seq': '0.14 0.47 0.47 0.1905 0.1895 0.41 0.41 0.3005 0.3005 0.3895 0.21 0.2391 0.2391 0.1809 0.32 0.32 0.4105 0.2095 0.35 0.35 0.43 0.43 0.45 0.45 0.2309 0.2309 0.2291 0.48 0.48 0.225 0.225 0.195 0.29 0.29 0.71 0.71 0.14', | |
'is_slur_seq': '0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0', | |
'input_type': 'phoneme' | |
} | |
DiffSingerE2EInfer.example_run(inp) | |