fixed voicefixing not working as intended, load TTS before Gradio in the webui due to how long it takes to initialize tortoise (instead of just having a block to preload it)

This commit is contained in:
mrq 2023-02-12 20:05:59 +00:00
parent 4d01bbd429
commit 824ad38cca
3 changed files with 7 additions and 7 deletions

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@ -132,6 +132,7 @@ I'll try and make a list of "common" (or what I feel may be common that I experi
* `torch.cuda.OutOfMemoryError: CUDA out of memory.`: You most likely have a GPU with low VRAM (~4GiB), and the small optimizations with keeping data on the GPU is enough to OOM. Please open the `start.bat` file and add `--low-vram` to the command (for example: `py app.py --low-vram`) to disable those small optimizations.
* `WavFileWarning: Chunk (non-data) not understood, skipping it.`: something about your WAVs are funny, and its best to remux your audio files with FFMPEG (included batch file in `.\convert\`).
- Honestly, I don't know if this does impact output quality, as I feel it's placebo when I do try and correct this.
* `Unable to find a valid cuDNN algorithm to run convolution`: a rather weird error message that occurs in the colab notebook. The vanilla auto-batch size calculation is a bit flawed, so try and reduce it to a fixed number in `Settings`, like eight or so.
#### Non-"""Issues"""

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@ -42,8 +42,7 @@
"%cd tortoise-tts\n",
"!python -m pip install --upgrade pip\n",
"!pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116\n",
"!python -m pip install -r ./requirements.txt\n",
"!python setup.py install"
"!python -m pip install -r ./requirements.txt\n"
]
},
{
@ -78,9 +77,9 @@
"sys.argv = [\"\"]\n",
"\n",
"mrq.args = mrq.setup_args()\n",
"mrq.tts = mrq.setup_tortoise()\n",
"mrq.webui = mrq.setup_gradio()\n",
"mrq.webui.launch(share=True, prevent_thread_lock=True, height=1000)\n",
"mrq.tts = mrq.setup_tortoise()\n",
"mrq.webui.block_thread()"
],
"metadata":{

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@ -190,7 +190,7 @@ def generate(
'time': run_time
}
# save here in case some error happens mid-batch
torchaudio.save(f'{outdir}/{voice}_{name}.wav', audio, args.output_sample_rate)
torchaudio.save(f'{outdir}/{voice}_{name}.wav', audio, tts.output_sample_rate)
for k in audio_cache:
audio = audio_cache[k]['audio']
@ -265,10 +265,10 @@ def generate(
if args.voice_fixer and voicefixer:
# we could do this on the pieces before they get stiched up anyways to save some compute
# but the stitching would need to read back from disk, defeating the point of caching the waveform
for path in progress.tqdm(audio_cache, desc="Running voicefix..."):
for path in progress.tqdm(output_voices, desc="Running voicefix..."):
voicefixer.restore(
input=f'{outdir}/{voice}_{k}.wav',
output=f'{outdir}/{voice}_{k}.wav',
input=path,
output=path,
#cuda=False,
#mode=mode,
)