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svc train -t
[00:14:03] INFO [00:14:03] Server binary (from Python package v0.7.2): server_ingester.py:290
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-pa
ckages/tensorboard_data_server/bin/server
NOTE: Using experimental fast data loading logic. To disable, pass
"--load_fast=false" and report issues on GitHub. More details:
https://github.com/tensorflow/tensorboard/issues/4784
[00:14:10] INFO [00:14:10] Using strategy: auto train.py:98
INFO: GPU available: True (cuda), used: True
INFO [00:14:10] GPU available: True (cuda), used: True rank_zero.py:63
INFO: TPU available: False, using: 0 TPU cores
INFO [00:14:10] TPU available: False, using: 0 TPU cores rank_zero.py:63
INFO: HPU available: False, using: 0 HPUs
INFO [00:14:10] HPU available: False, using: 0 HPUs rank_zero.py:63
WARNING [00:14:10] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
so_vits_svc_fork/modules/synthesizers.py:81: UserWarning: Unused
arguments: {'n_layers_q': 3, 'use_spectral_norm': False,
'pretrained': {'D_0.pth':
'https://huggingface.co/datasets/ms903/sovits4.0-768vec-layer12/res
olve/main/sovits_768l12_pre_large_320k/clean_D_320000.pth',
'G_0.pth':
'https://huggingface.co/datasets/ms903/sovits4.0-768vec-layer12/res
olve/main/sovits_768l12_pre_large_320k/clean_G_320000.pth'}}
warnings.warn(f"Unused arguments: {kwargs}")
INFO [00:14:10] Decoder type: hifi-gan synthesizers.py:100
WARNING [00:14:10] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
torch/nn/utils/weight_norm.py:143: FutureWarning:
`torch.nn.utils.weight_norm` is deprecated in favor of
`torch.nn.utils.parametrizations.weight_norm`.
WeightNorm.apply(module, name, dim)
[00:14:12] WARNING [00:14:12] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
so_vits_svc_fork/utils.py:246: UserWarning: Keys not found in
checkpoint state dict:['emb_g.weight']
warnings.warn(f"Keys not found in checkpoint state dict:"
f"{not_in_from}")
WARNING [00:14:12] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
so_vits_svc_fork/utils.py:264: UserWarning: Shape mismatch:
['dec.cond.weight: torch.Size([512, 256, 1]) -> torch.Size([512,
768, 1])', 'enc_q.enc.cond_layer.weight_v: torch.Size([6144, 256,
1]) -> torch.Size([6144, 768, 1])',
'flow.flows.0.enc.cond_layer.weight_v: torch.Size([1536, 256, 1])
-> torch.Size([1536, 768, 1])',
'flow.flows.2.enc.cond_layer.weight_v: torch.Size([1536, 256, 1])
-> torch.Size([1536, 768, 1])',
'flow.flows.4.enc.cond_layer.weight_v: torch.Size([1536, 256, 1])
-> torch.Size([1536, 768, 1])',
'flow.flows.6.enc.cond_layer.weight_v: torch.Size([1536, 256, 1])
-> torch.Size([1536, 768, 1])', 'f0_decoder.cond.weight:
torch.Size([192, 256, 1]) -> torch.Size([192, 768, 1])']
warnings.warn(
INFO [00:14:12] Loaded checkpoint 'logs/44k/G_0.pth' (epoch 0) utils.py:307
INFO [00:14:12] Loaded checkpoint 'logs/44k/D_0.pth' (epoch 0) utils.py:307
INFO: LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
INFO [00:14:12] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0] cuda.py:61
┏━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━┓
┃ ┃ Name ┃ Type ┃ Params ┃ Mode ┃
┡━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━┩
│ 0 │ net_g │ SynthesizerTrn │ 45.6 M │ train │
│ 1 │ net_d │ MultiPeriodDiscriminator │ 46.7 M │ train │
└───┴───────┴──────────────────────────┴────────┴───────┘
Trainable params: 92.4 M
Non-trainable params: 0
Total params: 92.4 M
Total estimated model params size (MB): 369
Modules in train mode: 486
Modules in eval mode: 0
WARNING [00:14:12] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
lightning/pytorch/trainer/connectors/data_connector.py:425: The
'val_dataloader' does not have many workers which may be a
bottleneck. Consider increasing the value of the `num_workers`
argument` to `num_workers=7` in the `DataLoader` to improve
performance.
WARNING [00:14:12] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
lightning/pytorch/loops/fit_loop.py:310: The number of training
batches (1) is smaller than the logging interval
Trainer(log_every_n_steps=50). Set a lower value for
log_every_n_steps if you want to see logs for the training epoch.
INFO [00:14:12] Setting current epoch to 0 train.py:311
INFO [00:14:12] Setting total batch idx to 0 train.py:327
INFO [00:14:12] Setting global step to 0 train.py:317
[00:14:14] WARNING [00:14:14] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
torch/functional.py:704: UserWarning: stft with
return_complex=False is deprecated. In a future pytorch release,
stft will return complex tensors for all inputs, and
return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output
to recover the old return format. (Triggered internally at
../aten/src/ATen/native/SpectralOps.cpp:873.)
return _VF.stft( # type: ignore[attr-defined]
[00:14:15] WARNING [00:14:15] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
so_vits_svc_fork/train.py:447: FutureWarning:
`torch.cuda.amp.autocast(args...)` is deprecated. Please use
`torch.amp.autocast('cuda', args...)` instead.
with autocast(enabled=False):
[00:14:18] WARNING [00:14:18] warnings.py:109
/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/
so_vits_svc_fork/train.py:523: FutureWarning:
`torch.cuda.amp.autocast(args...)` is deprecated. Please use
`torch.amp.autocast('cuda', args...)` instead.
with autocast(enabled=False):
Epoch 98/189999 ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0/1 0:00:00 • 0:00:00 0.00it/s v_num: 0.000 loss/g/total:
31.428 loss/g/fm: 6.895
loss/g/mel: 21.074
loss/g/kl: 0.897 loss/g/lf0:
0.000 loss/d/total: 2.785
Traceback (most recent call last):
File "/home/zeus/miniconda3/envs/cloudspace/bin/svc", line 8, in <module>
sys.exit(cli())
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/so_vits_svc_fork/__main__.py", line 128, in train
train(
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/so_vits_svc_fork/train.py", line 149, in train
trainer.fit(model, datamodule=datamodule)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 539, in fit
call._call_and_handle_interrupt(
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/call.py", line 47, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 575, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 982, in _run
results = self._run_stage()
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 1026, in _run_stage
self.fit_loop.run()
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/fit_loop.py", line 216, in run
self.advance()
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/fit_loop.py", line 455, in advance
self.epoch_loop.run(self._data_fetcher)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 150, in run
self.advance(data_fetcher)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 322, in advance
batch_output = self.manual_optimization.run(kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/manual.py", line 94, in run
self.advance(kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/manual.py", line 114, in advance
training_step_output = call._call_strategy_hook(trainer, "training_step", *kwargs.values())
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/trainer/call.py", line 323, in _call_strategy_hook
output = fn(*args, **kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/lightning/pytorch/strategies/strategy.py", line 391, in training_step
return self.lightning_module.training_step(*args, **kwargs)
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/so_vits_svc_fork/train.py", line 483, in training_step
"slice/mel_org": utils.plot_spectrogram_to_numpy(
File "/home/zeus/miniconda3/envs/cloudspace/lib/python3.10/site-packages/so_vits_svc_fork/utils.py", line 403, in plot_spectrogram_to_numpy
data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep="")
AttributeError: 'FigureCanvasAgg' object has no attribute 'tostring_rgb'. Did you mean: 'tostring_argb'?
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