按照视频的方法换了作者的数据集之后，再运行报错

[zhuhero2012]

Checkpoint path: synthesizer\saved_models\mandarin\mandarin.pt
Loading training data from: I:\视频剪辑\配音人家\数据处理\SV2TTS\synthesizer\train.txt
Using model: Tacotron
Using device: cuda

Initialising Tacotron Model...

WARNING: you are using compatible mode due to wrong sympols length, please modify varible _characters in utils\symbols.py
\Loading the json with %s
{'sample_rate': 16000, 'n_fft': 800, 'num_mels': 80, 'hop_size': 200, 'win_size': 800, 'fmin': 55, 'min_level_db': -100, 'ref_level_db': 20, 'max_abs_value': 4.0, 'preemphasis': 0.97, 'preemphasize': True, 'tts_embed_dims': 512, 'tts_encoder_dims': 256, 'tts_decoder_dims': 128, 'tts_postnet_dims': 512, 'tts_encoder_K': 5, 'tts_lstm_dims': 1024, 'tts_postnet_K': 5, 'tts_num_highways': 4, 'tts_dropout': 0.5, 'tts_cleaner_names': ['basic_cleaners'], 'tts_stop_threshold': -3.4, 'tts_schedule': [[2, 0.001, 10000, 12], [2, 0.0005, 15000, 12], [2, 0.0002, 20000, 12], [2, 0.0001, 30000, 12], [2, 5e-05, 40000, 12], [2, 1e-05, 60000, 12], [2, 5e-06, 160000, 12], [2, 3e-06, 320000, 12], [2, 1e-06, 640000, 12]], 'tts_clip_grad_norm': 1.0, 'tts_eval_interval': 500, 'tts_eval_num_samples': 1, 'tts_finetune_layers': [], 'max_mel_frames': 900, 'rescale': True, 'rescaling_max': 0.9, 'synthesis_batch_size': 16, 'signal_normalization': True, 'power': 1.5, 'griffin_lim_iters': 60, 'fmax': 7600, 'allow_clipping_in_normalization': True, 'clip_mels_length': True, 'use_lws': False, 'symmetric_mels': True, 'trim_silence': True, 'speaker_embedding_size': 256, 'silence_min_duration_split': 0.4, 'utterance_min_duration': 1.6, 'use_gst': True, 'use_ser_for_gst': True}
Trainable Parameters: 0.000M

Loading weights at synthesizer\saved_models\mandarin\mandarin.pt
Traceback (most recent call last):
File "D:\MockingBird-main\synthesizer_train.py", line 37, in
train(**vars(args))
File "D:\MockingBird-main\synthesizer\train.py", line 121, in train
model.load(weights_fpath, device, optimizer)
File "D:\MockingBird-main\synthesizer\models\base.py", line 51, in load
self.load_state_dict(checkpoint["model_state"], strict=False)
File "C:\Users\zhuhero\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\nn\modules\module.py", line 1604, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Tacotron:
size mismatch for encoder.embedding.weight: copying a param with shape torch.Size([75, 512]) from checkpoint, the shape in current model is torch.Size([70, 512]).

[babysor]

#37

[Aurelyano]

#37
what's the '_characters' for your new modle 'my_run8_25k.pt'?
it seems like a new char set

RuntimeError: Error(s) in loading state_dict for Tacotron: size mismatch for encoder.embedding.weight: copying a param with shape torch.Size([75, 512]) from checkpoint, the shape in current model is torch.Size([70, 512]). size mismatch for gst.stl.attention.W_query.weight: copying a param with shape torch.Size([512, 256]) from checkpoint, the shape in current model is torch.Size([512, 512]).