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Build error
| import torch | |
| from inference.base_tts_infer import BaseTTSInfer | |
| from utils.ckpt_utils import load_ckpt, get_last_checkpoint | |
| from utils.hparams import hparams | |
| from modules.GenerSpeech.model.generspeech import GenerSpeech | |
| import os | |
| import numpy as np | |
| from functools import partial | |
| class GenerSpeechInfer(BaseTTSInfer): | |
| def build_model(self): | |
| f0_stats_fn = f'{hparams["binary_data_dir"]}/train_f0s_mean_std.npy' | |
| if os.path.exists(f0_stats_fn): | |
| hparams['f0_mean'], hparams['f0_std'] = np.load(f0_stats_fn) | |
| hparams['f0_mean'] = float(hparams['f0_mean']) | |
| hparams['f0_std'] = float(hparams['f0_std']) | |
| model = GenerSpeech(self.ph_encoder) | |
| model.eval() | |
| load_ckpt(model, hparams['work_dir'], 'model') | |
| return model | |
| def forward_model(self, inp): | |
| sample = self.input_to_batch(inp) | |
| txt_tokens = sample['txt_tokens'] # [B, T_t] | |
| with torch.no_grad(): | |
| output = self.model(txt_tokens, ref_mel2ph=sample['mel2ph'], ref_mel2word=sample['mel2word'], ref_mels=sample['mels'], | |
| spk_embed=sample['spk_embed'], emo_embed=sample['emo_embed'], global_steps=300000, infer=True) | |
| mel_out = output['mel_out'] | |
| wav_out = self.run_vocoder(mel_out) | |
| wav_out = wav_out.squeeze().cpu().numpy() | |
| return wav_out | |
| if __name__ == '__main__': | |
| GenerSpeechInfer.example_run() | |