Comments (3)
Hi! Unfortunately I have no idea how to optimize for apple silicon chips, neither do I have access to a Mac or even any device running MacOS.
I update the requirements from time to time and make sure that pip install -r requirements.txt
is sufficient to get everything running on windows and most linux systems. There are very few dependencies, I try to keep everything self-contained. And I'm always looking to remove existing dependencies and replace them with self-contained solutions. The speaker embedding will soon be replaced with something built in-house, but for phonemizing, espeak-ng will probably remain as the most tricky dependency if it's not shipped by default with a system.
IMS-Toucan is somewhere between a toolkit, a framework and a library, but mostly leaning towards toolkit. So it is not meant as a standalone application, it's just my way to share my research in a somewhat practical format. The way we use it in other projects is that we take the components that we need for that project and integrate them in the other codebase. If you want to figure out installation instructions for Apple Silicon devices, I'll gladly add them to the readme though :)
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Okay. I will take a look and see what I can figure out.
Thanks for the response!
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The following Dockerfile builds and installs everything from requirements.txt
for IMS-Toucan, though I haven't tested calling into the toolkit to ensure everything is linked properly (as I'm guessing running via Rosetta 2 even inference will be very slow), and for the reasons I mention below.
FROM python:3.8.13
# install deps for python packages
RUN apt update
RUN apt install -y make cmake gcc g++ gfortran
WORKDIR app/
# install python packages
COPY requirements.txt .
RUN pip install -r requirements.txt
RUN pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 torchaudio==0.10.1 -f https://download.pytorch.org/whl/torch_stable.html
COPY . .
Unfortunately, CherokeeLanguage/IMS-Toucan has diverged slightly and now uses conda, so I'm looking into a micromamba-based image for CherokeeLanguage/IMS-Toucan.
That said, I will leave the pip-based image here in case anyone starting a new project wants a working docker build.
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Related Issues (20)
- New ToucanTTS model gives far worse results after finetuning HOT 13
- RuntimeError + Indexerror when fine tuning on v25 HOT 1
- build_path_to_transcript_dict_ljspeech doesn't match official ljspeech dataset HOT 1
- How to read scorer output ? HOT 5
- v2.4: RuntimeError: language "en-us" is not supported by the espeak backend HOT 8
- Finetuning example: Error(s) in loading state_dict for ToucanTTS HOT 2
- Emotional Voice HOT 3
- Fix for Hugging Face Spaces: PoeticTTS SpeechCloning doesn't work HOT 8
- How does the quality of the model change after running weight averaging on a single checkpoint ? HOT 2
- Why is bigvgan better than Avovodo ? HOT 2
- How does Audiobook to Audioplay work ? HOT 2
- Handling of abbreviations/ single letters HOT 4
- For info ThisSpeakerDoesNotExist UI on HuggingFace doesn't load HOT 1
- Quality of exact style cloning HOT 1
- Clone a Voice. How to improve? HOT 6
- Nasal ɛ̃ ("in" in French) mispronounced only on female voices (not on male voices) HOT 8
- AttributeError: 'Tag' object has no attribute 'value' HOT 2
- RuntimeError: Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same HOT 3
- Error pulseaudio
- What'are the goals of the different branches ? HOT 3
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