(self, sample, batch_idx)
| 189 | return outputs |
| 190 | |
| 191 | def test_step(self, sample, batch_idx): |
| 192 | spk_embed = sample.get('spk_embed') if not hparams['use_spk_id'] else sample.get('spk_ids') |
| 193 | txt_tokens = sample['txt_tokens'] |
| 194 | energy = sample['energy'] |
| 195 | if hparams['profile_infer']: |
| 196 | pass |
| 197 | else: |
| 198 | mel2ph, uv, f0 = None, None, None |
| 199 | if hparams['use_gt_dur']: |
| 200 | mel2ph = sample['mel2ph'] |
| 201 | if hparams['use_gt_f0']: |
| 202 | f0 = sample['f0'] |
| 203 | uv = sample['uv'] |
| 204 | fs2_mel = sample['fs2_mels'] |
| 205 | outputs = self.model( |
| 206 | txt_tokens, spk_embed=spk_embed, mel2ph=mel2ph, f0=f0, uv=uv, ref_mels=[None, fs2_mel], energy=energy, |
| 207 | infer=True) |
| 208 | sample['outputs'] = self.model.out2mel(outputs['mel_out']) |
| 209 | sample['mel2ph_pred'] = outputs['mel2ph'] |
| 210 | |
| 211 | if hparams.get('pe_enable') is not None and hparams['pe_enable']: |
| 212 | sample['f0'] = self.pe(sample['mels'])['f0_denorm_pred'] # pe predict from GT mel |
| 213 | sample['f0_pred'] = self.pe(sample['outputs'])['f0_denorm_pred'] # pe predict from Pred mel |
| 214 | else: |
| 215 | sample['f0'] = denorm_f0(sample['f0'], sample['uv'], hparams) |
| 216 | sample['f0_pred'] = outputs.get('f0_denorm') |
| 217 | return self.after_infer(sample) |
no test coverage detected