Out Of Memory Error on RTX 2060

[madey83]

Traceback (most recent call last):
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 1605, in fit
self._fit()
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 1557, in _fit
self.train_epoch()
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 1273, in train_epoch
outputs, _ = self.train_step(batch, batch_num_steps, cur_step, loader_start_time)
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 1152, in train_step
outputs, loss_dict_new, step_time = self.optimize(
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 995, in optimize
outputs, loss_dict = self._compute_loss(
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 925, in _compute_loss
outputs, loss_dict = self._model_train_step(batch, model, criterion, optimizer_idx=optimizer_idx)
File "D:\TTS-Training\TTS-Training\lib\site-packages\trainer\trainer.py", line 882, in _model_train_step
return model.train_step(*input_args)
File "D:\TTS-Training\TTS-Training\coqui-ai-TTS\TTS\tts\models\vits.py", line 1275, in train_step
scores_disc_fake, _, scores_disc_real, _ = self.disc(
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\coqui-ai-TTS\TTS\tts\layers\vits\discriminator.py", line 82, in forward
x_score, x_feat = net(x)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\coqui-ai-TTS\TTS\vocoder\models\hifigan_discriminator.py", line 69, in forward
x = l(x)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\conv.py", line 554, in forward
return self._conv_forward(input, self.weight, self.bias)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\utils\parametrize.py", line 407, in get_parametrized
return parametrization()
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\utils\parametrize.py", line 303, in forward
x = self0
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "D:\TTS-Training\TTS-Training\lib\site-packages\torch\nn\utils\parametrizations.py", line 325, in forward
return torch._weight_norm(weight_v, weight_g, self.dim)

torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 20.00 MiB. GPU 0 has a total capacity of 6.00 GiB of which 0 bytes is free. Of the allocated memory 10.57 GiB is allocated by PyTorch, and 640.80 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

this is my config:

config = VitsConfig(
	audio=audio_config,
	run_name="Vits-TTS-PL",
	batch_size=14,
	eval_batch_size=7,
	batch_group_size=5,
	num_loader_workers=4,
	num_eval_loader_workers=2,
	run_eval=True,
	test_delay_epochs=-1,
	epochs=1000,
    save_step=5000,
    save_checkpoints=True,
    save_n_checkpoints=2,
    save_best_after=10000,
    add_blank=True,                      
	text_cleaner="multilingual_cleaners",
	use_phonemes=True,
	phoneme_language="pl",
	phoneme_cache_path=os.path.join(output_path, "phoneme_cache"),
	compute_input_seq_cache=True,
	print_step=25,
	print_eval=True,
	mixed_precision=False,
	output_path=output_path,
	datasets=[dataset_config],
	cudnn_benchmark=False,

Does anyone could point me out which parameters need to be adjusted?

[eginhard]

Batch size and if you have some long audios max_audio_len