--- Logging error ---
Traceback (most recent call last):
File "D:\ProgramData\Anaconda3\envs\vits\lib\logging_init_.py", line 1028, in emit
stream.write(msg + self.terminator)
UnicodeEncodeError: 'gbk' codec can't encode character '\u0283' in position 1329: illegal multibyte sequence
Call stack:
File "", line 1, in
File "D:\ProgramData\Anaconda3\envs\vits\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "D:\ProgramData\Anaconda3\envs\vits\lib\multiprocessing\spawn.py", line 118, in _main
return self._bootstrap()
File "D:\ProgramData\Anaconda3\envs\vits\lib\multiprocessing\process.py", line 297, in _bootstrap
self.run()
File "D:\ProgramData\Anaconda3\envs\vits\lib\multiprocessing\process.py", line 99, in run
self._target(*self._args, **self.kwargs)
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\multiprocessing\spawn.py", line 69, in wrap
fn(i, *args)
File "D:\vits-main\train.py", line 62, in run
logger.info(hps)
Message: {'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 25000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 13, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/list.txt.cleaned', 'validation_files': 'filelists/list_val.txt.cleaned', 'text_cleaners': ['japanese_cleaners'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 0, 'cleaned_text': True}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [8, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256}, 'symbols': ['', ',', '.', '!', '?', '-', 'A', 'E', 'I', 'N', 'O', 'Q', 'U', 'a', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'm', 'n', 'o', 'p', 'r', 's', 't', 'u', 'v', 'w', 'y', 'z', 'ʃ', 'ʧ', '↓', '↑', ' '], 'model_dir': 'D:/rem'}
Arguments: ()
INFO:rem:{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 25000, 'learning_rate': 0.0002, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 13, 'fp16_run': True, 'lr_decay': 0.999875, 'segment_size': 8192, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0}, 'data': {'training_files': 'filelists/list.txt.cleaned', 'validation_files': 'filelists/list_val.txt.cleaned', 'text_cleaners': ['japanese_cleaners'], 'max_wav_value': 32768.0, 'sampling_rate': 22050, 'filter_length': 1024, 'hop_length': 256, 'win_length': 1024, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None, 'add_blank': True, 'n_speakers': 0, 'cleaned_text': True}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [8, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256}, 'symbols': ['', ',', '.', '!', '?', '-', 'A', 'E', 'I', 'N', 'O', 'Q', 'U', 'a', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'm', 'n', 'o', 'p', 'r', 's', 't', 'u', 'v', 'w', 'y', 'z', 'ʃ', 'ʧ', '↓', '↑', ' '], 'model_dir': 'D:/rem'}
WARNING:rem:D:\vits-main is not a git repository, therefore hash value comparison will be ignored.
INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0
INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.
D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4 (cpuset is not taken into account), which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
cpuset_checked))
Exception ignored in: <function _MultiProcessingDataLoaderIter.del at 0x000001BA73DB9798>
Traceback (most recent call last):
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 1466, in del
self._shutdown_workers()
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 1397, in _shutdown_workers
if not self._shutdown:
AttributeError: '_MultiProcessingDataLoaderIter' object has no attribute '_shutdown'
Traceback (most recent call last):
File "train.py", line 301, in
main()
File "train.py", line 55, in main
mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,))
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\multiprocessing\spawn.py", line 240, in spawn
return start_processes(fn, args, nprocs, join, daemon, start_method='spawn')
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\multiprocessing\spawn.py", line 198, in start_processes
while not context.join():
File "D:\ProgramData\Anaconda3\envs\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 "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\multiprocessing\spawn.py", line 69, in _wrap
fn(i, *args)
File "D:\vits-main\train.py", line 122, in run
train_and_evaluate(rank, epoch, hps, [net_g, net_d], [optim_g, optim_d], [scheduler_g, scheduler_d], scaler, [train_loader, eval_loader], logger, [writer, writer_eval])
File "D:\vits-main\train.py", line 142, in train_and_evaluate
for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths) in enumerate(train_loader):
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 435, in iter
return self._get_iterator()
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 381, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 988, in init
super(_MultiProcessingDataLoaderIter, self).init(loader)
File "D:\ProgramData\Anaconda3\envs\vits\lib\site-packages\torch\utils\data\dataloader.py", line 598, in init
self._sampler_iter = iter(self._index_sampler)
File "D:\vits-main\data_utils.py", line 358, in iter
ids_bucket = ids_bucket + ids_bucket * (rem // len_bucket) + ids_bucket[:(rem % len_bucket)]
ZeroDivisionError: integer division or modulo by zero
vits copied to clipboard
jaywalnut310
