danruta / xva-trainer Goto Github PK
View Code? Open in Web Editor NEWUI app for training TTS/VC machine learning models for xVASynth, with several audio pre-processing tools, and dataset creation/management.
UI app for training TTS/VC machine learning models for xVASynth, with several audio pre-processing tools, and dataset creation/management.
Title. I'm pretty sure this is an electron app but I have no idea which of these files to do anything with.
Output:
18:41:18 | New Session
18:41:18 | No graphs.json file found. Starting anew.
18:41:18 | Dataset: C:/Program Files (x86)/Steam/steamapps/common/xVATrainer/resources/app/datasets//rdfvd_paimon
18:41:18 | Language: English
18:41:18 | Checkpoint: ./resources/app/python/xvapitch/pretrained_models/xVAPitch_5820651.pt
18:41:18 | CUDA device IDs: 0
18:41:18 | FP16: Disabled
18:41:18 | Batch size: 6 (Base: 6, GPUs mult: 1) | GAM: 67 -> (402) | Target: 400
18:41:18 | Outputting model backups every 3 checkpoints
18:41:19 | Loading model and optimizer state from ./resources/app/python/xvapitch/pretrained_models/xVAPitch_5820651.pt
18:41:20 | New voice
18:41:20 | Workers: 3
18:41:38 | Fine-tune dataset files: 7
18:45:00 | Priors datasets files: 179007 | Number of datasets: 28
Error:
Traceback (most recent call last):
File "server.py", line 227, in handleTrainingLoop
File "python\xvapitch\xva_train.py", line 137, in handleTrainer
File "python\xvapitch\xva_train.py", line 557, in start
File "python\xvapitch\xva_train.py", line 604, in iteration
File "python\xvapitch\xva_train.py", line 391, in init
File "C:\Program Files (x86)\Steam\steamapps\common\xVATrainer\.\resources\app\python\xvapitch\get_dataset_emb.py", line 18, in get_emb
kmeans = KMeans(n_clusters=n_clusters, random_state=0).fit(embs)
File "sklearn\cluster\_kmeans.py", line 1376, in fit
self._check_params(X)
File "sklearn\cluster\_kmeans.py", line 1307, in _check_params
super()._check_params(X)
File "sklearn\cluster\_kmeans.py", line 828, in _check_params
raise ValueError(
ValueError: n_samples=7 should be >= n_clusters=10.
Given that it can take quite some time to train 2500 steps, it would be convenient to create manual checkpoints so training can resume from that.
UI error message:
ERROR:Traceback (most recent call last):
File "server.py", line 200, in websocket_handler
File "python\make_srt\model.py", line 91, in make_srt
KeyError: 'diarization'
server.log of version 1.2.0
Traceback (most recent call last):
File "python\models_manager.py", line 37, in init_model
File "python\speaker_diarization\model.py", line 26, in __init__
File "python\speaker_diarization\model.py", line 129, in load_model
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pyannote\audio\features\__init__.py", line 33, in <module>
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pyannote\audio\features\base.py", line 38, in <module>
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pyannote\database\__init__.py", line 37, in <module>
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pyannote\database\database.py", line 31, in <module>
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pyannote\database\util.py", line 32, in <module>
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\__init__.py", line 22, in <module>
from pandas.compat import (
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\compat\__init__.py", line 15, in <module>
from pandas.compat.numpy import (
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\compat\numpy\__init__.py", line 7, in <module>
from pandas.util.version import Version
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\util\__init__.py", line 1, in <module>
from pandas.util._decorators import ( # noqa
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\util\_decorators.py", line 14, in <module>
from pandas._libs.properties import cache_readonly # noqa
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\_libs\__init__.py", line 13, in <module>
from pandas._libs.interval import Interval
File "pandas\_libs\interval.pyx", line 1, in init pandas._libs.interval
File "pandas\_libs\hashtable.pyx", line 1, in init pandas._libs.hashtable
File "pandas\_libs\missing.pyx", line 1, in init pandas._libs.missing
File "PyInstaller\loader\pyimod03_importers.py", line 495, in exec_module
File "pandas\_libs\tslibs\__init__.py", line 31, in <module>
from pandas._libs.tslibs.conversion import (
File "pandas\_libs\tslibs\conversion.pyx", line 1, in init pandas._libs.tslibs.conversion
ModuleNotFoundError: No module named 'pandas._libs.tslibs.base'
server.log of version 1.2.1
Traceback (most recent call last):
File "python\models_manager.py", line 37, in init_model
File "python\speaker_diarization\model.py", line 26, in __init__
File "python\speaker_diarization\model.py", line 129, in load_model
ImportError: cannot import name 'Pretrained' from 'pyannote.audio.features' (C:\Program Files (x86)\Steam\steamapps\common\xVATrainer\resources\app\cpython_gpu\pyannote\audio\features\__init__.pyc)
Hi, I see that the PRIORS datasets are synthetic. I plan to replace them with more natural sounding datasets (either synthetic and/or human). This will help for a better and more natural pronunciation and intonation in voice synthesis?
I also plan to make an improvement on Arpabet, since it has a problem with the double R ("RR"), in Spanish, and does not read accents.
Is it possible to improve the dictionary?
I have a mod I made some time ago for Tacotron for the Spanish language, but I don't know if it can be implemented here. I leave the link to the files below. Thanks!
https://drive.google.com/file/d/19AGqgfWiMc8MYHuH_705phCbm8-GGIDa/view?usp=drive_link
Multiple issues. Checking data files through Steam didn't show any error. Cleaning up the dataset didn't help.
Traceback (most recent call last):
File "server.py", line 227, in handleTrainingLoop
File "python\xvapitch\xva_train.py", line 137, in handleTrainer
File "python\xvapitch\xva_train.py", line 554, in start
File "python\xvapitch\xva_train.py", line 601, in iteration
File "python\xvapitch\xva_train.py", line 377, in init
File "python\xvapitch\xva_train.py", line 1206, in setup_dataloaders
File "C:\Program Files (x86)\Steam\steamapps\common\xVATrainer\.\resources\app\python\xvapitch\util.py", line 410, in get_language_weighted_sampler
return WeightedRandomSampler(dataset_samples_weight, len(dataset_samples_weight))
File "torch\utils\data\sampler.py", line 186, in __init__
raise ValueError("num_samples should be a positive integer "
ValueError: num_samples should be a positive integer value, but got num_samples=0
The line numbers there don't match up with xva_train.py
, changes to that file to debug this are completely ignored, whereas changes to e.g. dataset.py
are working fine. Throwing an exception in read_datasets
shows that at least one point it's returning the correct dataset.
Hello! Is it possible to run Whisper from GPU? When transcribing the audios, I see that it uses my CPU and takes forever. I haven't seen the option to switch Whisper from CPU to GPU. I have a RTX 3060 Ti with CUDA installed. Thank you.
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