mirror of https://github.com/coqui-ai/TTS.git
Merge pull request #113 from idiap/pytorch
fix: only enable load with weights_only in pytorch>=2.4
This commit is contained in:
Enno Hermann
GitHub
commit
6314032fd7
|
|
@ -13,17 +13,15 @@ jobs:
|
|||
fail-fast: false
|
||||
matrix:
|
||||
python-version: [3.9]
|
||||
experimental: [false]
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
architecture: x64
|
||||
cache: 'pip'
|
||||
cache-dependency-path: 'requirements*'
|
||||
- name: Install/upgrade dev dependencies
|
||||
run: python3 -m pip install -r requirements.dev.txt
|
||||
version: "0.4.27"
|
||||
enable-cache: true
|
||||
cache-dependency-glob: "**/pyproject.toml"
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
run: uv python install ${{ matrix.python-version }}
|
||||
- name: Lint check
|
||||
run: make lint
|
||||
|
|
|
|||
|
|
@ -16,17 +16,14 @@ jobs:
|
|||
subset: ["data_tests", "inference_tests", "test_aux", "test_text", "test_tts", "test_tts2", "test_vocoder", "test_xtts", "test_zoo0", "test_zoo1", "test_zoo2"]
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
architecture: x64
|
||||
cache: 'pip'
|
||||
cache-dependency-path: 'requirements*'
|
||||
- name: check OS
|
||||
run: cat /etc/os-release
|
||||
- name: set ENV
|
||||
run: export TRAINER_TELEMETRY=0
|
||||
version: "0.4.27"
|
||||
enable-cache: true
|
||||
cache-dependency-glob: "**/pyproject.toml"
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
run: uv python install ${{ matrix.python-version }}
|
||||
- name: Install Espeak
|
||||
if: contains(fromJSON('["inference_tests", "test_text", "test_tts", "test_tts2", "test_xtts", "test_zoo0", "test_zoo1", "test_zoo2"]'), matrix.subset)
|
||||
run: |
|
||||
|
|
@ -37,21 +34,17 @@ jobs:
|
|||
sudo apt-get update
|
||||
sudo apt-get install -y --no-install-recommends git make gcc
|
||||
make system-deps
|
||||
- name: Install/upgrade Python setup deps
|
||||
run: python3 -m pip install --upgrade pip setuptools wheel uv
|
||||
- name: Replace scarf urls
|
||||
if: contains(fromJSON('["data_tests", "inference_tests", "test_aux", "test_tts", "test_tts2", "test_xtts", "test_zoo0", "test_zoo1", "test_zoo2"]'), matrix.subset)
|
||||
run: |
|
||||
sed -i 's/https:\/\/coqui.gateway.scarf.sh\//https:\/\/github.com\/coqui-ai\/TTS\/releases\/download\//g' TTS/.models.json
|
||||
- name: Install TTS
|
||||
- name: Unit tests
|
||||
run: |
|
||||
resolution=highest
|
||||
if [ "${{ matrix.python-version }}" == "3.9" ]; then
|
||||
resolution=lowest-direct
|
||||
fi
|
||||
python3 -m uv pip install --resolution=$resolution --system "coqui-tts[dev,server,languages] @ ."
|
||||
- name: Unit tests
|
||||
run: make ${{ matrix.subset }}
|
||||
uv run --resolution=$resolution --extra server --extra languages make ${{ matrix.subset }}
|
||||
- name: Upload coverage data
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
|
|
@ -65,18 +58,17 @@ jobs:
|
|||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/setup-python@v5
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v3
|
||||
with:
|
||||
python-version: "3.12"
|
||||
version: "0.4.27"
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
pattern: coverage-data-*
|
||||
merge-multiple: true
|
||||
- name: Combine coverage
|
||||
run: |
|
||||
python -Im pip install --upgrade coverage[toml]
|
||||
|
||||
python -Im coverage combine
|
||||
python -Im coverage html --skip-covered --skip-empty
|
||||
|
||||
python -Im coverage report --format=markdown >> $GITHUB_STEP_SUMMARY
|
||||
uv python install
|
||||
uvx coverage combine
|
||||
uvx coverage html --skip-covered --skip-empty
|
||||
uvx coverage report --format=markdown >> $GITHUB_STEP_SUMMARY
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
uv.lock
|
||||
|
||||
WadaSNR/
|
||||
.idea/
|
||||
*.pyc
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
repos:
|
||||
- repo: "https://github.com/pre-commit/pre-commit-hooks"
|
||||
rev: v4.5.0
|
||||
rev: v5.0.0
|
||||
hooks:
|
||||
- id: check-yaml
|
||||
- id: end-of-file-fixer
|
||||
|
|
@ -11,14 +11,7 @@ repos:
|
|||
- id: black
|
||||
language_version: python3
|
||||
- repo: https://github.com/astral-sh/ruff-pre-commit
|
||||
rev: v0.3.0
|
||||
rev: v0.7.0
|
||||
hooks:
|
||||
- id: ruff
|
||||
args: [--fix, --exit-non-zero-on-fix]
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: generate_requirements.py
|
||||
name: generate_requirements.py
|
||||
language: system
|
||||
entry: python scripts/generate_requirements.py
|
||||
files: "pyproject.toml|requirements.*\\.txt|tools/generate_requirements.py"
|
||||
|
|
|
|||
|
|
@ -44,29 +44,37 @@ If you have a new feature, a model to implement, or a bug to squash, go ahead an
|
|||
Please use the following steps to send a ✨**PR**✨.
|
||||
Let us know if you encounter a problem along the way.
|
||||
|
||||
The following steps are tested on an Ubuntu system.
|
||||
The following steps are tested on an Ubuntu system and require
|
||||
[uv](https://docs.astral.sh/uv/) for virtual environment management. Choose your
|
||||
preferred [installation
|
||||
method](https://docs.astral.sh/uv/getting-started/installation/), e.g. the
|
||||
standalone installer:
|
||||
|
||||
```bash
|
||||
curl -LsSf https://astral.sh/uv/install.sh | sh
|
||||
```
|
||||
|
||||
1. Fork 🐸TTS[https://github.com/idiap/coqui-ai-TTS] by clicking the fork button at the top right corner of the project page.
|
||||
|
||||
2. Clone 🐸TTS and add the main repo as a new remote named ```upstream```.
|
||||
|
||||
```bash
|
||||
$ git clone git@github.com:<your Github name>/coqui-ai-TTS.git
|
||||
$ cd coqui-ai-TTS
|
||||
$ git remote add upstream https://github.com/idiap/coqui-ai-TTS.git
|
||||
git clone git@github.com:<your Github name>/coqui-ai-TTS.git
|
||||
cd coqui-ai-TTS
|
||||
git remote add upstream https://github.com/idiap/coqui-ai-TTS.git
|
||||
```
|
||||
|
||||
3. Install 🐸TTS for development.
|
||||
|
||||
```bash
|
||||
$ make system-deps # intended to be used on Ubuntu (Debian). Let us know if you have a different OS.
|
||||
$ make install_dev
|
||||
make system-deps # intended to be used on Ubuntu (Debian). Let us know if you have a different OS.
|
||||
make install_dev
|
||||
```
|
||||
|
||||
4. Create a new branch with an informative name for your goal.
|
||||
|
||||
```bash
|
||||
$ git checkout -b an_informative_name_for_my_branch
|
||||
git checkout -b an_informative_name_for_my_branch
|
||||
```
|
||||
|
||||
5. Implement your changes on your new branch.
|
||||
|
|
@ -75,39 +83,42 @@ The following steps are tested on an Ubuntu system.
|
|||
|
||||
7. Add your tests to our test suite under ```tests``` folder. It is important to show that your code works, edge cases are considered, and inform others about the intended use.
|
||||
|
||||
8. Run the tests to see how your updates work with the rest of the project. You can repeat this step multiple times as you implement your changes to make sure you are on the right direction.
|
||||
8. Run the tests to see how your updates work with the rest of the project. You
|
||||
can repeat this step multiple times as you implement your changes to make
|
||||
sure you are on the right direction. **NB: running all tests takes a long time,
|
||||
it is better to leave this to the CI.**
|
||||
|
||||
```bash
|
||||
$ make test # stop at the first error
|
||||
$ make test_all # run all the tests, report all the errors
|
||||
uv run make test # stop at the first error
|
||||
uv run make test_all # run all the tests, report all the errors
|
||||
```
|
||||
|
||||
9. Format your code. We use ```black``` for code formatting.
|
||||
|
||||
```bash
|
||||
$ make style
|
||||
make style
|
||||
```
|
||||
|
||||
10. Run the linter and correct the issues raised. We use ```ruff``` for linting. It helps to enforce a coding standard, offers simple refactoring suggestions.
|
||||
|
||||
```bash
|
||||
$ make lint
|
||||
make lint
|
||||
```
|
||||
|
||||
11. When things are good, add new files and commit your changes.
|
||||
|
||||
```bash
|
||||
$ git add my_file1.py my_file2.py ...
|
||||
$ git commit
|
||||
git add my_file1.py my_file2.py ...
|
||||
git commit
|
||||
```
|
||||
|
||||
It's a good practice to regularly sync your local copy of the project with the upstream code to keep up with the recent updates.
|
||||
|
||||
```bash
|
||||
$ git fetch upstream
|
||||
$ git rebase upstream/main
|
||||
git fetch upstream
|
||||
git rebase upstream/main
|
||||
# or for the development version
|
||||
$ git rebase upstream/dev
|
||||
git rebase upstream/dev
|
||||
```
|
||||
|
||||
12. Send a PR to ```dev``` branch.
|
||||
|
|
@ -115,7 +126,7 @@ The following steps are tested on an Ubuntu system.
|
|||
Push your branch to your fork.
|
||||
|
||||
```bash
|
||||
$ git push -u origin an_informative_name_for_my_branch
|
||||
git push -u origin an_informative_name_for_my_branch
|
||||
```
|
||||
|
||||
Then go to your fork's Github page and click on 'Pull request' to send your ✨**PR**✨.
|
||||
|
|
@ -137,9 +148,9 @@ If you prefer working within a Docker container as your development environment,
|
|||
2. Clone 🐸TTS and add the main repo as a new remote named ```upsteam```.
|
||||
|
||||
```bash
|
||||
$ git clone git@github.com:<your Github name>/coqui-ai-TTS.git
|
||||
$ cd coqui-ai-TTS
|
||||
$ git remote add upstream https://github.com/idiap/coqui-ai-TTS.git
|
||||
git clone git@github.com:<your Github name>/coqui-ai-TTS.git
|
||||
cd coqui-ai-TTS
|
||||
git remote add upstream https://github.com/idiap/coqui-ai-TTS.git
|
||||
```
|
||||
|
||||
3. Build the Docker Image as your development environment (it installs all of the dependencies for you):
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ RUN rm -rf /root/.cache/pip
|
|||
WORKDIR /root
|
||||
COPY . /root
|
||||
|
||||
RUN make install
|
||||
RUN pip3 install -e .[all]
|
||||
|
||||
ENTRYPOINT ["tts"]
|
||||
CMD ["--help"]
|
||||
|
|
|
|||
17
Makefile
17
Makefile
|
|
@ -1,5 +1,5 @@
|
|||
.DEFAULT_GOAL := help
|
||||
.PHONY: test system-deps dev-deps style lint install install_dev help docs
|
||||
.PHONY: test system-deps style lint install install_dev help docs
|
||||
|
||||
help:
|
||||
@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
|
||||
|
|
@ -50,27 +50,24 @@ test_failed: ## only run tests failed the last time.
|
|||
coverage run -m nose2 -F -v -B tests
|
||||
|
||||
style: ## update code style.
|
||||
black ${target_dirs}
|
||||
uv run --only-dev black ${target_dirs}
|
||||
|
||||
lint: ## run linters.
|
||||
ruff check ${target_dirs}
|
||||
black ${target_dirs} --check
|
||||
uv run --only-dev ruff check ${target_dirs}
|
||||
uv run --only-dev black ${target_dirs} --check
|
||||
|
||||
system-deps: ## install linux system deps
|
||||
sudo apt-get install -y libsndfile1-dev
|
||||
|
||||
dev-deps: ## install development deps
|
||||
pip install -r requirements.dev.txt
|
||||
|
||||
build-docs: ## build the docs
|
||||
cd docs && make clean && make build
|
||||
|
||||
install: ## install 🐸 TTS
|
||||
pip install -e .[all]
|
||||
uv sync --all-extras
|
||||
|
||||
install_dev: ## install 🐸 TTS for development.
|
||||
pip install -e .[all,dev]
|
||||
pre-commit install
|
||||
uv sync --all-extras
|
||||
uv run pre-commit install
|
||||
|
||||
docs: ## build the docs
|
||||
$(MAKE) -C docs clean && $(MAKE) -C docs html
|
||||
|
|
|
|||
28
README.md
28
README.md
|
|
@ -1,16 +1,13 @@
|
|||
|
||||
## 🐸Coqui TTS News
|
||||
- 📣 Fork of the [original, unmaintained repository](https://github.com/coqui-ai/TTS). New PyPI package: [coqui-tts](https://pypi.org/project/coqui-tts)
|
||||
- 📣 Prebuilt wheels are now also published for Mac and Windows (in addition to Linux as before) for easier installation across platforms.
|
||||
- 📣 ⓍTTSv2 is here with 16 languages and better performance across the board.
|
||||
- 📣 ⓍTTS fine-tuning code is out. Check the [example recipes](https://github.com/idiap/coqui-ai-TTS/tree/dev/recipes/ljspeech).
|
||||
- 📣 ⓍTTS can now stream with <200ms latency.
|
||||
- 📣 ⓍTTS, our production TTS model that can speak 13 languages, is released [Blog Post](https://coqui.ai/blog/tts/open_xtts), [Demo](https://huggingface.co/spaces/coqui/xtts), [Docs](https://coqui-tts.readthedocs.io/en/latest/models/xtts.html)
|
||||
- 📣 [🐶Bark](https://github.com/suno-ai/bark) is now available for inference with unconstrained voice cloning. [Docs](https://coqui-tts.readthedocs.io/en/latest/models/bark.html)
|
||||
- 📣 You can use [~1100 Fairseq models](https://github.com/facebookresearch/fairseq/tree/main/examples/mms) with 🐸TTS.
|
||||
- 📣 🐸TTS now supports 🐢Tortoise with faster inference. [Docs](https://coqui-tts.readthedocs.io/en/latest/models/tortoise.html)
|
||||
|
||||
<div align="center">
|
||||
<img src="https://static.scarf.sh/a.png?x-pxid=cf317fe7-2188-4721-bc01-124bb5d5dbb2" />
|
||||
|
||||
## <img src="https://raw.githubusercontent.com/idiap/coqui-ai-TTS/main/images/coqui-log-green-TTS.png" height="56"/>
|
||||
|
||||
|
|
@ -27,7 +24,6 @@ ______________________________________________________________________
|
|||
[](https://discord.gg/5eXr5seRrv)
|
||||
[](https://opensource.org/licenses/MPL-2.0)
|
||||
[](https://badge.fury.io/py/coqui-tts)
|
||||
[](https://github.com/idiap/coqui-ai-TTS/blob/main/CODE_OF_CONDUCT.md)
|
||||
[](https://pepy.tech/project/coqui-tts)
|
||||
[](https://zenodo.org/badge/latestdoi/265612440)
|
||||
|
||||
|
|
@ -43,12 +39,11 @@ ______________________________________________________________________
|
|||
## 💬 Where to ask questions
|
||||
Please use our dedicated channels for questions and discussion. Help is much more valuable if it's shared publicly so that more people can benefit from it.
|
||||
|
||||
| Type | Platforms |
|
||||
| ------------------------------- | --------------------------------------- |
|
||||
| 🚨 **Bug Reports** | [GitHub Issue Tracker] |
|
||||
| 🎁 **Feature Requests & Ideas** | [GitHub Issue Tracker] |
|
||||
| 👩💻 **Usage Questions** | [GitHub Discussions] |
|
||||
| 🗯 **General Discussion** | [GitHub Discussions] or [Discord] |
|
||||
| Type | Platforms |
|
||||
| -------------------------------------------- | ----------------------------------- |
|
||||
| 🚨 **Bug Reports, Feature Requests & Ideas** | [GitHub Issue Tracker] |
|
||||
| 👩💻 **Usage Questions** | [GitHub Discussions] |
|
||||
| 🗯 **General Discussion** | [GitHub Discussions] or [Discord] |
|
||||
|
||||
[github issue tracker]: https://github.com/idiap/coqui-ai-TTS/issues
|
||||
[github discussions]: https://github.com/idiap/coqui-ai-TTS/discussions
|
||||
|
|
@ -66,15 +61,10 @@ repository are also still a useful source of information.
|
|||
| 💼 **Documentation** | [ReadTheDocs](https://coqui-tts.readthedocs.io/en/latest/)
|
||||
| 💾 **Installation** | [TTS/README.md](https://github.com/idiap/coqui-ai-TTS/tree/dev#installation)|
|
||||
| 👩💻 **Contributing** | [CONTRIBUTING.md](https://github.com/idiap/coqui-ai-TTS/blob/main/CONTRIBUTING.md)|
|
||||
| 📌 **Road Map** | [Main Development Plans](https://github.com/coqui-ai/TTS/issues/378)
|
||||
| 🚀 **Released Models** | [Standard models](https://github.com/idiap/coqui-ai-TTS/blob/dev/TTS/.models.json) and [Fairseq models in ~1100 languages](https://github.com/idiap/coqui-ai-TTS#example-text-to-speech-using-fairseq-models-in-1100-languages-)|
|
||||
| 📰 **Papers** | [TTS Papers](https://github.com/erogol/TTS-papers)|
|
||||
|
||||
## Features
|
||||
- High-performance Deep Learning models for Text2Speech tasks.
|
||||
- Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech).
|
||||
- Speaker Encoder to compute speaker embeddings efficiently.
|
||||
- Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN)
|
||||
- High-performance Deep Learning models for Text2Speech tasks. See lists of models below.
|
||||
- Fast and efficient model training.
|
||||
- Detailed training logs on the terminal and Tensorboard.
|
||||
- Support for Multi-speaker TTS.
|
||||
|
|
@ -180,8 +170,8 @@ pip install -e .[server,ja]
|
|||
If you are on Ubuntu (Debian), you can also run following commands for installation.
|
||||
|
||||
```bash
|
||||
$ make system-deps # intended to be used on Ubuntu (Debian). Let us know if you have a different OS.
|
||||
$ make install
|
||||
make system-deps # intended to be used on Ubuntu (Debian). Let us know if you have a different OS.
|
||||
make install
|
||||
```
|
||||
|
||||
If you are on Windows, 👑@GuyPaddock wrote installation instructions
|
||||
|
|
|
|||
|
|
@ -1,29 +1,33 @@
|
|||
import _codecs
|
||||
import importlib.metadata
|
||||
from collections import defaultdict
|
||||
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
from TTS.config.shared_configs import BaseDatasetConfig
|
||||
from TTS.tts.configs.xtts_config import XttsConfig
|
||||
from TTS.tts.models.xtts import XttsArgs, XttsAudioConfig
|
||||
from TTS.utils.radam import RAdam
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
__version__ = importlib.metadata.version("coqui-tts")
|
||||
|
||||
|
||||
torch.serialization.add_safe_globals([dict, defaultdict, RAdam])
|
||||
if is_pytorch_at_least_2_4():
|
||||
import _codecs
|
||||
from collections import defaultdict
|
||||
|
||||
# Bark
|
||||
torch.serialization.add_safe_globals(
|
||||
[
|
||||
np.core.multiarray.scalar,
|
||||
np.dtype,
|
||||
np.dtypes.Float64DType,
|
||||
_codecs.encode, # TODO: safe by default from Pytorch 2.5
|
||||
]
|
||||
)
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
# XTTS
|
||||
torch.serialization.add_safe_globals([BaseDatasetConfig, XttsConfig, XttsAudioConfig, XttsArgs])
|
||||
from TTS.config.shared_configs import BaseDatasetConfig
|
||||
from TTS.tts.configs.xtts_config import XttsConfig
|
||||
from TTS.tts.models.xtts import XttsArgs, XttsAudioConfig
|
||||
from TTS.utils.radam import RAdam
|
||||
|
||||
torch.serialization.add_safe_globals([dict, defaultdict, RAdam])
|
||||
|
||||
# Bark
|
||||
torch.serialization.add_safe_globals(
|
||||
[
|
||||
np.core.multiarray.scalar,
|
||||
np.dtype,
|
||||
np.dtypes.Float64DType,
|
||||
_codecs.encode, # TODO: safe by default from Pytorch 2.5
|
||||
]
|
||||
)
|
||||
|
||||
# XTTS
|
||||
torch.serialization.add_safe_globals([BaseDatasetConfig, XttsConfig, XttsAudioConfig, XttsArgs])
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import tqdm
|
|||
|
||||
from TTS.tts.layers.bark.model import GPT, GPTConfig
|
||||
from TTS.tts.layers.bark.model_fine import FineGPT, FineGPTConfig
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
if (
|
||||
torch.cuda.is_available()
|
||||
|
|
@ -118,7 +119,7 @@ def load_model(ckpt_path, device, config, model_type="text"):
|
|||
logger.info(f"{model_type} model not found, downloading...")
|
||||
_download(config.REMOTE_MODEL_PATHS[model_type]["path"], ckpt_path, config.CACHE_DIR)
|
||||
|
||||
checkpoint = torch.load(ckpt_path, map_location=device, weights_only=True)
|
||||
checkpoint = torch.load(ckpt_path, map_location=device, weights_only=is_pytorch_at_least_2_4())
|
||||
# this is a hack
|
||||
model_args = checkpoint["model_args"]
|
||||
if "input_vocab_size" not in model_args:
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ import torchaudio
|
|||
from transformers import LogitsWarper
|
||||
|
||||
from TTS.tts.layers.tortoise.xtransformers import ContinuousTransformerWrapper, RelativePositionBias
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
|
||||
def zero_module(module):
|
||||
|
|
@ -332,7 +333,7 @@ class TorchMelSpectrogram(nn.Module):
|
|||
self.mel_norm_file = mel_norm_file
|
||||
if self.mel_norm_file is not None:
|
||||
with fsspec.open(self.mel_norm_file) as f:
|
||||
self.mel_norms = torch.load(f, weights_only=True)
|
||||
self.mel_norms = torch.load(f, weights_only=is_pytorch_at_least_2_4())
|
||||
else:
|
||||
self.mel_norms = None
|
||||
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import torchaudio
|
|||
from scipy.io.wavfile import read
|
||||
|
||||
from TTS.utils.audio.torch_transforms import TorchSTFT
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -124,7 +125,7 @@ def load_voice(voice: str, extra_voice_dirs: List[str] = []):
|
|||
voices = get_voices(extra_voice_dirs)
|
||||
paths = voices[voice]
|
||||
if len(paths) == 1 and paths[0].endswith(".pth"):
|
||||
return None, torch.load(paths[0], weights_only=True)
|
||||
return None, torch.load(paths[0], weights_only=is_pytorch_at_least_2_4())
|
||||
else:
|
||||
conds = []
|
||||
for cond_path in paths:
|
||||
|
|
|
|||
|
|
@ -9,6 +9,8 @@ import torch.nn.functional as F
|
|||
import torchaudio
|
||||
from einops import rearrange
|
||||
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
|
|
@ -46,7 +48,7 @@ def dvae_wav_to_mel(
|
|||
mel = mel_stft(wav)
|
||||
mel = torch.log(torch.clamp(mel, min=1e-5))
|
||||
if mel_norms is None:
|
||||
mel_norms = torch.load(mel_norms_file, map_location=device, weights_only=True)
|
||||
mel_norms = torch.load(mel_norms_file, map_location=device, weights_only=is_pytorch_at_least_2_4())
|
||||
mel = mel / mel_norms.unsqueeze(0).unsqueeze(-1)
|
||||
return mel
|
||||
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ from torch.nn.utils.parametrizations import weight_norm
|
|||
from torch.nn.utils.parametrize import remove_parametrizations
|
||||
from trainer.io import load_fsspec
|
||||
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
from TTS.vocoder.models.hifigan_generator import get_padding
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
|
@ -328,7 +329,7 @@ class HifiganGenerator(torch.nn.Module):
|
|||
def load_checkpoint(
|
||||
self, config, checkpoint_path, eval=False, cache=False
|
||||
): # pylint: disable=unused-argument, redefined-builtin
|
||||
state = torch.load(checkpoint_path, map_location=torch.device("cpu"), weights_only=True)
|
||||
state = torch.load(checkpoint_path, map_location=torch.device("cpu"), weights_only=is_pytorch_at_least_2_4())
|
||||
self.load_state_dict(state["model"])
|
||||
if eval:
|
||||
self.eval()
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ from TTS.tts.layers.xtts.tokenizer import VoiceBpeTokenizer
|
|||
from TTS.tts.layers.xtts.trainer.dataset import XTTSDataset
|
||||
from TTS.tts.models.base_tts import BaseTTS
|
||||
from TTS.tts.models.xtts import Xtts, XttsArgs, XttsAudioConfig
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -91,7 +92,9 @@ class GPTTrainer(BaseTTS):
|
|||
|
||||
# load GPT if available
|
||||
if self.args.gpt_checkpoint:
|
||||
gpt_checkpoint = torch.load(self.args.gpt_checkpoint, map_location=torch.device("cpu"), weights_only=True)
|
||||
gpt_checkpoint = torch.load(
|
||||
self.args.gpt_checkpoint, map_location=torch.device("cpu"), weights_only=is_pytorch_at_least_2_4()
|
||||
)
|
||||
# deal with coqui Trainer exported model
|
||||
if "model" in gpt_checkpoint.keys() and "config" in gpt_checkpoint.keys():
|
||||
logger.info("Coqui Trainer checkpoint detected! Converting it!")
|
||||
|
|
@ -184,7 +187,9 @@ class GPTTrainer(BaseTTS):
|
|||
|
||||
self.dvae.eval()
|
||||
if self.args.dvae_checkpoint:
|
||||
dvae_checkpoint = torch.load(self.args.dvae_checkpoint, map_location=torch.device("cpu"), weights_only=True)
|
||||
dvae_checkpoint = torch.load(
|
||||
self.args.dvae_checkpoint, map_location=torch.device("cpu"), weights_only=is_pytorch_at_least_2_4()
|
||||
)
|
||||
self.dvae.load_state_dict(dvae_checkpoint, strict=False)
|
||||
logger.info("DVAE weights restored from: %s", self.args.dvae_checkpoint)
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -1,9 +1,11 @@
|
|||
import torch
|
||||
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
|
||||
class SpeakerManager:
|
||||
def __init__(self, speaker_file_path=None):
|
||||
self.speakers = torch.load(speaker_file_path, weights_only=True)
|
||||
self.speakers = torch.load(speaker_file_path, weights_only=is_pytorch_at_least_2_4())
|
||||
|
||||
@property
|
||||
def name_to_id(self):
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ from TTS.tts.models.base_tts import BaseTTS
|
|||
from TTS.tts.utils.speakers import SpeakerManager
|
||||
from TTS.tts.utils.text.tokenizer import TTSTokenizer
|
||||
from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
|
||||
from TTS.utils.generic_utils import format_aux_input
|
||||
from TTS.utils.generic_utils import format_aux_input, is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -107,7 +107,7 @@ class NeuralhmmTTS(BaseTTS):
|
|||
|
||||
def preprocess_batch(self, text, text_len, mels, mel_len):
|
||||
if self.mean.item() == 0 or self.std.item() == 1:
|
||||
statistics_dict = torch.load(self.mel_statistics_parameter_path, weights_only=True)
|
||||
statistics_dict = torch.load(self.mel_statistics_parameter_path, weights_only=is_pytorch_at_least_2_4())
|
||||
self.update_mean_std(statistics_dict)
|
||||
|
||||
mels = self.normalize(mels)
|
||||
|
|
@ -292,7 +292,9 @@ class NeuralhmmTTS(BaseTTS):
|
|||
"Data parameters found for: %s. Loading mel normalization parameters...",
|
||||
trainer.config.mel_statistics_parameter_path,
|
||||
)
|
||||
statistics = torch.load(trainer.config.mel_statistics_parameter_path, weights_only=True)
|
||||
statistics = torch.load(
|
||||
trainer.config.mel_statistics_parameter_path, weights_only=is_pytorch_at_least_2_4()
|
||||
)
|
||||
data_mean, data_std, init_transition_prob = (
|
||||
statistics["mean"],
|
||||
statistics["std"],
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ from TTS.tts.models.base_tts import BaseTTS
|
|||
from TTS.tts.utils.speakers import SpeakerManager
|
||||
from TTS.tts.utils.text.tokenizer import TTSTokenizer
|
||||
from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
|
||||
from TTS.utils.generic_utils import format_aux_input
|
||||
from TTS.utils.generic_utils import format_aux_input, is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -120,7 +120,7 @@ class Overflow(BaseTTS):
|
|||
|
||||
def preprocess_batch(self, text, text_len, mels, mel_len):
|
||||
if self.mean.item() == 0 or self.std.item() == 1:
|
||||
statistics_dict = torch.load(self.mel_statistics_parameter_path, weights_only=True)
|
||||
statistics_dict = torch.load(self.mel_statistics_parameter_path, weights_only=is_pytorch_at_least_2_4())
|
||||
self.update_mean_std(statistics_dict)
|
||||
|
||||
mels = self.normalize(mels)
|
||||
|
|
@ -308,7 +308,9 @@ class Overflow(BaseTTS):
|
|||
"Data parameters found for: %s. Loading mel normalization parameters...",
|
||||
trainer.config.mel_statistics_parameter_path,
|
||||
)
|
||||
statistics = torch.load(trainer.config.mel_statistics_parameter_path, weights_only=True)
|
||||
statistics = torch.load(
|
||||
trainer.config.mel_statistics_parameter_path, weights_only=is_pytorch_at_least_2_4()
|
||||
)
|
||||
data_mean, data_std, init_transition_prob = (
|
||||
statistics["mean"],
|
||||
statistics["std"],
|
||||
|
|
|
|||
|
|
@ -23,6 +23,7 @@ from TTS.tts.layers.tortoise.tokenizer import VoiceBpeTokenizer
|
|||
from TTS.tts.layers.tortoise.vocoder import VocConf, VocType
|
||||
from TTS.tts.layers.tortoise.wav2vec_alignment import Wav2VecAlignment
|
||||
from TTS.tts.models.base_tts import BaseTTS
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -171,7 +172,11 @@ def classify_audio_clip(clip, model_dir):
|
|||
distribute_zero_label=False,
|
||||
)
|
||||
classifier.load_state_dict(
|
||||
torch.load(os.path.join(model_dir, "classifier.pth"), map_location=torch.device("cpu"), weights_only=True)
|
||||
torch.load(
|
||||
os.path.join(model_dir, "classifier.pth"),
|
||||
map_location=torch.device("cpu"),
|
||||
weights_only=is_pytorch_at_least_2_4(),
|
||||
)
|
||||
)
|
||||
clip = clip.cpu().unsqueeze(0)
|
||||
results = F.softmax(classifier(clip), dim=-1)
|
||||
|
|
@ -490,7 +495,7 @@ class Tortoise(BaseTTS):
|
|||
torch.load(
|
||||
os.path.join(self.models_dir, "rlg_auto.pth"),
|
||||
map_location=torch.device("cpu"),
|
||||
weights_only=True,
|
||||
weights_only=is_pytorch_at_least_2_4(),
|
||||
)
|
||||
)
|
||||
self.rlg_diffusion = RandomLatentConverter(2048).eval()
|
||||
|
|
@ -498,7 +503,7 @@ class Tortoise(BaseTTS):
|
|||
torch.load(
|
||||
os.path.join(self.models_dir, "rlg_diffuser.pth"),
|
||||
map_location=torch.device("cpu"),
|
||||
weights_only=True,
|
||||
weights_only=is_pytorch_at_least_2_4(),
|
||||
)
|
||||
)
|
||||
with torch.no_grad():
|
||||
|
|
@ -885,17 +890,17 @@ class Tortoise(BaseTTS):
|
|||
|
||||
if os.path.exists(ar_path):
|
||||
# remove keys from the checkpoint that are not in the model
|
||||
checkpoint = torch.load(ar_path, map_location=torch.device("cpu"), weights_only=True)
|
||||
checkpoint = torch.load(ar_path, map_location=torch.device("cpu"), weights_only=is_pytorch_at_least_2_4())
|
||||
|
||||
# strict set False
|
||||
# due to removed `bias` and `masked_bias` changes in Transformers
|
||||
self.autoregressive.load_state_dict(checkpoint, strict=False)
|
||||
|
||||
if os.path.exists(diff_path):
|
||||
self.diffusion.load_state_dict(torch.load(diff_path, weights_only=True), strict=strict)
|
||||
self.diffusion.load_state_dict(torch.load(diff_path, weights_only=is_pytorch_at_least_2_4()), strict=strict)
|
||||
|
||||
if os.path.exists(clvp_path):
|
||||
self.clvp.load_state_dict(torch.load(clvp_path, weights_only=True), strict=strict)
|
||||
self.clvp.load_state_dict(torch.load(clvp_path, weights_only=is_pytorch_at_least_2_4()), strict=strict)
|
||||
|
||||
if os.path.exists(vocoder_checkpoint_path):
|
||||
self.vocoder.load_state_dict(
|
||||
|
|
@ -903,7 +908,7 @@ class Tortoise(BaseTTS):
|
|||
torch.load(
|
||||
vocoder_checkpoint_path,
|
||||
map_location=torch.device("cpu"),
|
||||
weights_only=True,
|
||||
weights_only=is_pytorch_at_least_2_4(),
|
||||
)
|
||||
)
|
||||
)
|
||||
|
|
|
|||
|
|
@ -16,6 +16,7 @@ from TTS.tts.layers.xtts.stream_generator import init_stream_support
|
|||
from TTS.tts.layers.xtts.tokenizer import VoiceBpeTokenizer, split_sentence
|
||||
from TTS.tts.layers.xtts.xtts_manager import LanguageManager, SpeakerManager
|
||||
from TTS.tts.models.base_tts import BaseTTS
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
|
@ -65,7 +66,7 @@ def wav_to_mel_cloning(
|
|||
mel = mel_stft(wav)
|
||||
mel = torch.log(torch.clamp(mel, min=1e-5))
|
||||
if mel_norms is None:
|
||||
mel_norms = torch.load(mel_norms_file, map_location=device, weights_only=True)
|
||||
mel_norms = torch.load(mel_norms_file, map_location=device, weights_only=is_pytorch_at_least_2_4())
|
||||
mel = mel / mel_norms.unsqueeze(0).unsqueeze(-1)
|
||||
return mel
|
||||
|
||||
|
|
|
|||
|
|
@ -1,8 +1,10 @@
|
|||
import torch
|
||||
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
|
||||
def rehash_fairseq_vits_checkpoint(checkpoint_file):
|
||||
chk = torch.load(checkpoint_file, map_location=torch.device("cpu"), weights_only=True)["model"]
|
||||
chk = torch.load(checkpoint_file, map_location=torch.device("cpu"), weights_only=is_pytorch_at_least_2_4())["model"]
|
||||
new_chk = {}
|
||||
for k, v in chk.items():
|
||||
if "enc_p." in k:
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ import torch
|
|||
from TTS.config import load_config
|
||||
from TTS.encoder.utils.generic_utils import setup_encoder_model
|
||||
from TTS.utils.audio import AudioProcessor
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
|
||||
|
||||
def load_file(path: str):
|
||||
|
|
@ -17,7 +18,7 @@ def load_file(path: str):
|
|||
return json.load(f)
|
||||
elif path.endswith(".pth"):
|
||||
with fsspec.open(path, "rb") as f:
|
||||
return torch.load(f, map_location="cpu", weights_only=True)
|
||||
return torch.load(f, map_location="cpu", weights_only=is_pytorch_at_least_2_4())
|
||||
else:
|
||||
raise ValueError("Unsupported file type")
|
||||
|
||||
|
|
|
|||
|
|
@ -6,6 +6,9 @@ import re
|
|||
from pathlib import Path
|
||||
from typing import Dict, Optional
|
||||
|
||||
import torch
|
||||
from packaging.version import Version
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
|
|
@ -131,3 +134,8 @@ def setup_logger(
|
|||
sh = logging.StreamHandler()
|
||||
sh.setFormatter(formatter)
|
||||
lg.addHandler(sh)
|
||||
|
||||
|
||||
def is_pytorch_at_least_2_4() -> bool:
|
||||
"""Check if the installed Pytorch version is 2.4 or higher."""
|
||||
return Version(torch.__version__) >= Version("2.4")
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import urllib.request
|
|||
import torch
|
||||
from trainer.io import get_user_data_dir
|
||||
|
||||
from TTS.utils.generic_utils import is_pytorch_at_least_2_4
|
||||
from TTS.vc.modules.freevc.wavlm.wavlm import WavLM, WavLMConfig
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
|
@ -26,7 +27,7 @@ def get_wavlm(device="cpu"):
|
|||
logger.info("Downloading WavLM model to %s ...", output_path)
|
||||
urllib.request.urlretrieve(model_uri, output_path)
|
||||
|
||||
checkpoint = torch.load(output_path, map_location=torch.device(device), weights_only=True)
|
||||
checkpoint = torch.load(output_path, map_location=torch.device(device), weights_only=is_pytorch_at_least_2_4())
|
||||
cfg = WavLMConfig(checkpoint["cfg"])
|
||||
wavlm = WavLM(cfg).to(device)
|
||||
wavlm.load_state_dict(checkpoint["model"])
|
||||
|
|
|
|||
|
|
@ -20,4 +20,4 @@ RUN rm -rf /root/.cache/pip
|
|||
WORKDIR /root
|
||||
COPY . /root
|
||||
|
||||
RUN make install
|
||||
RUN pip3 install -e .[all,dev]
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ include = ["TTS*"]
|
|||
|
||||
[project]
|
||||
name = "coqui-tts"
|
||||
version = "0.24.2"
|
||||
version = "0.24.3"
|
||||
description = "Deep learning for Text to Speech."
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.9, <3.13"
|
||||
|
|
@ -47,8 +47,8 @@ dependencies = [
|
|||
"numpy>=1.25.2,<2.0",
|
||||
"cython>=3.0.0",
|
||||
"scipy>=1.11.2",
|
||||
"torch>=2.4",
|
||||
"torchaudio",
|
||||
"torch>=2.1",
|
||||
"torchaudio>=2.1.0",
|
||||
"soundfile>=0.12.0",
|
||||
"librosa>=0.10.1",
|
||||
"inflect>=5.6.0",
|
||||
|
|
@ -77,15 +77,6 @@ dependencies = [
|
|||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
# Development dependencies
|
||||
dev = [
|
||||
"black==24.2.0",
|
||||
"coverage[toml]>=7",
|
||||
"nose2>=0.15",
|
||||
"pre-commit>=3",
|
||||
"ruff==0.4.9",
|
||||
"tomli>=2; python_version < '3.11'",
|
||||
]
|
||||
# Dependencies for building the documentation
|
||||
docs = [
|
||||
"furo>=2023.5.20",
|
||||
|
|
@ -115,6 +106,7 @@ ko = [
|
|||
"hangul_romanize>=0.1.0",
|
||||
"jamo>=0.4.1",
|
||||
"g2pkk>=0.1.1",
|
||||
"pip>=22.2",
|
||||
]
|
||||
# Japanese
|
||||
ja = [
|
||||
|
|
@ -136,6 +128,15 @@ all = [
|
|||
"coqui-tts[notebooks,server,bn,ja,ko,zh]",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
"black==24.2.0",
|
||||
"coverage[toml]>=7",
|
||||
"nose2>=0.15",
|
||||
"pre-commit>=3",
|
||||
"ruff==0.7.0",
|
||||
]
|
||||
|
||||
[project.urls]
|
||||
Homepage = "https://github.com/idiap/coqui-ai-TTS"
|
||||
Documentation = "https://coqui-tts.readthedocs.io"
|
||||
|
|
@ -151,13 +152,12 @@ tts-server = "TTS.server.server:main"
|
|||
constraint-dependencies = ["numba>0.58.0"]
|
||||
|
||||
[tool.ruff]
|
||||
target-version = "py39"
|
||||
line-length = 120
|
||||
extend-exclude = ["*.ipynb"]
|
||||
lint.extend-select = [
|
||||
"B033", # duplicate-value
|
||||
"C416", # unnecessary-comprehension
|
||||
"D419", # empty-docstring
|
||||
"E999", # syntax-error
|
||||
"F401", # unused-import
|
||||
"F704", # yield-outside-function
|
||||
"F706", # return-outside-function
|
||||
|
|
|
|||
|
|
@ -1,8 +0,0 @@
|
|||
# Generated via scripts/generate_requirements.py and pre-commit hook.
|
||||
# Do not edit this file; modify pyproject.toml instead.
|
||||
black==24.2.0
|
||||
coverage[toml]>=7
|
||||
nose2>=0.15
|
||||
pre-commit>=3
|
||||
ruff==0.4.9
|
||||
tomli>=2; python_version < '3.11'
|
||||
|
|
@ -1,39 +0,0 @@
|
|||
#!/usr/bin/env python
|
||||
"""Generate requirements/*.txt files from pyproject.toml.
|
||||
|
||||
Adapted from:
|
||||
https://github.com/numpy/numpydoc/blob/e7c6baf00f5f73a4a8f8318d0cb4e04949c9a5d1/tools/generate_requirements.py
|
||||
"""
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
try: # standard module since Python 3.11
|
||||
import tomllib as toml
|
||||
except ImportError:
|
||||
try: # available for older Python via pip
|
||||
import tomli as toml
|
||||
except ImportError:
|
||||
sys.exit("Please install `tomli` first: `pip install tomli`")
|
||||
|
||||
script_pth = Path(__file__)
|
||||
repo_dir = script_pth.parent.parent
|
||||
script_relpth = script_pth.relative_to(repo_dir)
|
||||
header = [
|
||||
f"# Generated via {script_relpth.as_posix()} and pre-commit hook.",
|
||||
"# Do not edit this file; modify pyproject.toml instead.",
|
||||
]
|
||||
|
||||
|
||||
def generate_requirement_file(name: str, req_list: list[str]) -> None:
|
||||
req_fname = repo_dir / f"requirements.{name}.txt"
|
||||
req_fname.write_text("\n".join(header + req_list) + "\n")
|
||||
|
||||
|
||||
def main() -> None:
|
||||
pyproject = toml.loads((repo_dir / "pyproject.toml").read_text())
|
||||
generate_requirement_file("dev", pyproject["project"]["optional-dependencies"]["dev"])
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Reference in New Issue