运行train_ms.py后报ValueError错

[ecchiaru114514]

在正确地执行完预处理和情感embedding提取的步骤（其中的报错已自行解决）后，运行

python train_ms.py -c configs/mako.json -m mako

随后，在输出

INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.

后出现报错，在实例化TextAudioSpeakerLoader对象时出现了valueerror错误，报错全文如下：

Traceback (most recent call last): File "train_ms.py", line 314, in main() File "train_ms.py", line 49, in main mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,)) File "C:\Users\Henry\anaconda3\envs\e-vits\lib\site-packages\torch\multiprocessing\spawn.py", line 240, in spawn return start_processes(fn, args, nprocs, join, daemon, start_method='spawn') File "C:\Users\Henry\anaconda3\envs\e-vits\lib\site-packages\torch\multiprocessing\spawn.py", line 198, in start_processes while not context.join(): File "C:\Users\Henry\anaconda3\envs\e-vits\lib\site-packages\torch\multiprocessing\spawn.py", line 160, in join raise ProcessRaisedException(msg, error_index, failed_process.pid) torch.multiprocessing.spawn.ProcessRaisedException:

-- Process 0 terminated with the following error:
Traceback (most recent call last):
File "C:\Users\Henry\anaconda3\envs\e-vits\lib\site-packages\torch\multiprocessing\spawn.py", line 69, in _wrap
fn(i, *args)
File "D:\DL\emotional-vits\train_ms.py", line 77, in run
eval_dataset = TextAudioSpeakerLoader(hps.data.validation_files, hps.data)
File "D:\DL\emotional-vits\data_utils.py", line 183, in init
self._filter()
File "D:\DL\emotional-vits\data_utils.py", line 195, in _filter
for audiopath, sid, text in self.audiopaths_sid_text:
ValueError: too many values to unpack (expected 3)

系统为Windows10，python版本为3.7，所有依赖都已经正确的安装。如果需要更多的上下文信息，我会尽力提供。

值得一提的是，在此前执行

python emotion_extract.py --filelists filelists/train.txt filelists/val.txt

这一命令时，遇到了UnicodeDecodeError: 'gbk' codec can't decode byte 0x80 in position 38: illegal multibyte sequence报错。为解决这个问题，我对emotion_extract.py的第132行进行了修改，修改后的代码为

with open(filelist,'r',encoding='UTF-8') as f:


此后，命令能够正常执行。不清楚这个修改是否与valueerror报错有关。如果有恰当的解决方案，请及时提出和讨论，万分感激🙏