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rust:main rust:dependabot/cargo/axum-0.8.8 rust:ndarray-update rust:revert-274-dependabot/cargo/ndarray-0.17.1 rust:renovate/esbuild-0.x-lockfile rust:renovate/onnxruntime-web-1.x-lockfile rust:renovate/node-22.x-lockfile rust:marine rust:mecab rust:v0.1.x
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..
compare: rust:marine
Branches Tags
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1 Commits
commit-7c0 ... marine

Author SHA1 Message Date
tuna2134
5ce4f647c8 move 2024-11-28 12:59:28 +00:00
79 changed files with 1267 additions and 3352 deletions
Expand all files Collapse all files

3
.env.sample
View File

@@ -3,5 +3,4 @@ MODEL_PATH=models/tsukuyomi.sbv2
MODELS_PATH=models
TOKENIZER_PATH=models/tokenizer.json
ADDR=localhost:3000
RUST_LOG=warn
HOLDER_MAX_LOADED_MODElS=20
RUST_LOG=warn

15
.github/dependabot.yml vendored
View File

@@ -1,15 +0,0 @@
# To get started with Dependabot version updates, you'll need to specify which
# package ecosystems to update and where the package manifests are located.
# Please see the documentation for all configuration options:
# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
version: 2
updates:
- package-ecosystem: "cargo" # See documentation for possible values
directory: "/" # Location of package manifests
schedule:
interval: "weekly"
- package-ecosystem: "npm" # See documentation for possible values
directory: "/" # Location of package manifests
schedule:
interval: "weekly"

147
.github/workflows/build.yml → .github/workflows/CI.yml vendored
View File

@@ -1,34 +1,39 @@
name: Build
# This file is autogenerated by maturin v1.7.1
# To update, run
#
# maturin generate-ci github
#
name: CI
on:
push:
branches:
- main
- master
tags:
- '*'
pull_request:
workflow_dispatch:
permissions:
contents: write
contents: read
id-token: write
packages: write
jobs:
python-linux:
linux:
runs-on: ${{ matrix.platform.runner }}
strategy:
matrix:
platform:
- runner: ubuntu-latest
target: x86_64
- runner: ubuntu-24.04-arm
- runner: ubuntu-latest
target: aarch64
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: 3.x
- run: docker build . -f .github/workflows/build.Dockerfile --tag ci
- name: Build wheels
uses: PyO3/maturin-action@v1
with:
@@ -36,15 +41,14 @@ jobs:
args: --release --out dist --find-interpreter
sccache: 'true'
manylinux: auto
container: ci
working-directory: ./crates/sbv2_bindings
working-directory: sbv2_bindings
- name: Upload wheels
uses: actions/upload-artifact@v4
with:
name: wheels-linux-${{ matrix.platform.target }}
path: ./crates/sbv2_bindings/dist
path: sbv2_bindings/dist
python-windows:
windows:
runs-on: ${{ matrix.platform.runner }}
strategy:
matrix:
@@ -63,18 +67,20 @@ jobs:
target: ${{ matrix.platform.target }}
args: --release --out dist --find-interpreter
sccache: 'true'
working-directory: ./crates/sbv2_bindings
working-directory: sbv2_bindings
- name: Upload wheels
uses: actions/upload-artifact@v4
with:
name: wheels-windows-${{ matrix.platform.target }}
path: ./crates/sbv2_bindings/dist
path: sbv2_bindings/dist
python-macos:
macos:
runs-on: ${{ matrix.platform.runner }}
strategy:
matrix:
platform:
- runner: macos-12
target: x86_64
- runner: macos-14
target: aarch64
steps:
@@ -88,14 +94,14 @@ jobs:
target: ${{ matrix.platform.target }}
args: --release --out dist --find-interpreter
sccache: 'true'
working-directory: ./crates/sbv2_bindings
working-directory: sbv2_bindings
- name: Upload wheels
uses: actions/upload-artifact@v4
with:
name: wheels-macos-${{ matrix.platform.target }}
path: ./crates/sbv2_bindings/dist
path: sbv2_bindings/dist
python-sdist:
sdist:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
@@ -104,117 +110,54 @@ jobs:
with:
command: sdist
args: --out dist
working-directory: ./crates/sbv2_bindings
working-directory: sbv2_bindings
- name: Upload sdist
uses: actions/upload-artifact@v4
with:
name: wheels-sdist
path: ./crates/sbv2_bindings/dist
path: sbv2_bindings/dist
python-wheel:
name: Wheel Upload
runs-on: ubuntu-latest
needs: [python-linux, python-windows, python-macos, python-sdist]
env:
GH_TOKEN: ${{ github.token }}
steps:
- uses: actions/checkout@v4
- run: gh run download ${{ github.run_id }} -p wheels-*
- name: release
run: |
gh release create commit-${GITHUB_SHA:0:8} --prerelease wheels-*/*
python-release:
release:
name: Release
runs-on: ubuntu-latest
if: "startsWith(github.ref, 'refs/tags/')"
needs: [python-linux, python-windows, python-macos, python-sdist]
needs: [linux, windows, macos, sdist]
environment: release
env:
GH_TOKEN: ${{ github.token }}
steps:
- uses: actions/checkout@v4
- run: gh run download ${{ github.run_id }} -p wheels-*
- uses: actions/download-artifact@v4
- name: Publish to PyPI
uses: PyO3/maturin-action@v1
with:
command: upload
args: --non-interactive --skip-existing wheels-*/*
docker:
runs-on: ${{ matrix.machine.runner }}
push-docker:
runs-on: ubuntu-latest
if: "startsWith(github.ref, 'refs/tags/')"
permissions:
contents: read
packages: write
strategy:
fail-fast: false
matrix:
machine:
- platform: amd64
runner: ubuntu-latest
- platform: arm64
runner: ubuntu-24.04-arm
tag: [cpu, cuda]
steps:
- name: Prepare
run: |
platform=${{ matrix.machine.platform }}
echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: |
ghcr.io/${{ github.repository }}
- name: Login to GHCR
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- uses: actions/checkout@v4
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Build and push by digest
id: build
uses: docker/build-push-action@v6
with:
labels: ${{ steps.meta.outputs.labels }}
file: ./scripts/docker/${{ matrix.tag }}.Dockerfile
push: true
tags: |
ghcr.io/${{ github.repository }}:latest-${{ matrix.tag }}-${{ matrix.machine.platform }}
docker-merge:
runs-on: ubuntu-latest
needs:
- docker
steps:
- name: Download digests
uses: actions/download-artifact@v4
with:
path: ${{ runner.temp }}/digests
pattern: digests-*
merge-multiple: true
- name: Login to GHCR
- name: Login to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Merge
run: |
docker buildx imagetools create -t ghcr.io/${{ github.repository }}:cuda \
ghcr.io/${{ github.repository }}:latest-cuda-amd64 \
ghcr.io/${{ github.repository }}:latest-cuda-arm64
docker buildx imagetools create -t ghcr.io/${{ github.repository }}:cpu \
ghcr.io/${{ github.repository }}:latest-cpu-amd64 \
ghcr.io/${{ github.repository }}:latest-cpu-arm64
- name: Build and push image
uses: docker/build-push-action@v6
with:
context: .
push: true
tags: |
ghcr.io/${{ github.repository }}:${{ matrix.tag }}
file: docker/${{ matrix.tag }}.Dockerfile
platforms: linux/amd64, linux/arm64

4
.github/workflows/build.Dockerfile vendored
View File

@@ -1,4 +0,0 @@
FROM ubuntu:latest
RUN apt update && apt install openssl libssl-dev curl pkg-config software-properties-common -y && add-apt-repository ppa:deadsnakes/ppa && apt update && apt install python3.7 python3.8 python3.9 python3.10 python3.11 python3.12 python3.13 python3-pip python3 -y
ENV PIP_BREAK_SYSTEM_PACKAGES=1
RUN mkdir -p /root/.cache/sbv2 && curl https://huggingface.co/neody/sbv2-api-assets/resolve/main/dic/all.bin -o /root/.cache/sbv2/all.bin -L

26
.github/workflows/lint.yml vendored
View File

@@ -1,26 +0,0 @@
name: Lint
on:
pull_request:
jobs:
check:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
components:
- rustfmt
- clippy
steps:
- name: Setup
uses: actions/checkout@v4
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
components: ${{ matrix.components }}
- name: Format
if: ${{ matrix.components == 'rustfmt' }}
run: cargo fmt --all -- --check
- name: Lint
if: ${{ matrix.components == 'clippy' }}
run: cargo clippy --all-targets --all-features -- -D warnings

10
.gitignore vendored
View File

@@ -1,10 +1,8 @@
target/
target
models/
!models/.gitkeep
venv/
.env
*.wav
node_modules/
dist/
*.csv
*.bin
output.wav
node_modules
dist/

2349
Cargo.lock generated
View File

File diff suppressed because it is too large Load Diff

26
Cargo.toml
View File

@@ -1,25 +1,15 @@
[workspace]
resolver = "3"
members = ["./crates/sbv2_api", "./crates/sbv2_core", "./crates/sbv2_bindings", "./crates/sbv2_wasm"]
[workspace.package]
version = "0.2.0"
edition = "2021"
description = "Style-Bert-VITSの推論ライブラリ"
license = "MIT"
readme = "./README.md"
repository = "https://github.com/neodyland/sbv2-api"
documentation = "https://docs.rs/sbv2_core"
resolver = "2"
members = ["sbv2_api", "sbv2_core", "sbv2_bindings", "sbv2_wasm"]
[workspace.dependencies]
anyhow = "1.0.100"
anyhow = "1.0.86"
dotenvy = "0.15.7"
env_logger = "0.11.6"
ndarray = "0.17.1"
once_cell = "1.20.3"
env_logger = "0.11.5"
ndarray = "0.16.1"
once_cell = "1.19.0"
[profile.release]
strip = true
opt-level = "z"
lto = true
codegen-units = 1
debug = false
strip = true

1
LICENSE.md → LICENSE
View File

@@ -1,7 +1,6 @@
MIT License
Copyright (c) 2024 tuna2134
Copyright (c) 2025- neodyland
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

48
README.md
View File

@@ -1,23 +1,11 @@
# SBV2-API
> [!CAUTION]
> 本バージョンはアルファ版です。
>
> 安定版を利用したい場合は[こちら](https://github.com/neodyland/sbv2-api/tree/v0.1.x)をご覧ください。
> [!CAUTION]
> オプションの辞書はLGPLです。
>
> オプションの辞書を使用する場合、バイナリの内部の辞書部分について、LGPLが適用されます。
> [!NOTE]
> このレポジトリはメンテナンスの都合上、[tuna2134](https:://github.com/tuna2134)氏の所属する[Neodyland](https://neody.land/)へとリポジトリ所在地を移動しました。
>
> 引き続きtuna2134氏がメインメンテナとして管理しています。
## 注意：本バージョンはアルファ版です。
安定版を利用したい場合は[こちら](https://github.com/tuna2134/sbv2-api/tree/v0.1.x)をご覧ください。
## プログラミングに詳しくない方向け
[こちら](https://github.com/tuna2134/sbv2-gui)を参照してください。
[こちら](https://github.com/tuna2134/sbv2-gui?tab=readme-ov-file)を参照してください。
コマンドやpythonの知識なしで簡単に使えるバージョンです。(できることはほぼ同じ)
@@ -29,7 +17,7 @@ JP-Extra しか対応していません。(基本的に対応する予定もあ
## 変換方法
[こちら](https://github.com/neodyland/sbv2-api/tree/main/scripts/convert)を参照してください。
[こちら](https://github.com/tuna2134/sbv2-api/tree/main/convert)を参照してください。
## Todo
@@ -41,27 +29,23 @@ JP-Extra しか対応していません。(基本的に対応する予定もあ
- [x] GPU 対応(CUDA)
- [x] GPU 対応(DirectML)
- [x] GPU 対応(CoreML)
- [x] WASM 変換
- [ ] WASM 変換(依存ライブラリの関係により現在は不可)
- [x] arm64のdockerサポート
- [x] aivis形式のサポート
- [ ] MeCabを利用する
## 構造説明
- `crates/sbv2_api` - 推論用 REST API
- `crates/sbv2_core` - 推論コア部分
- `scripts/docker` - docker ビルドスクリプト
- `scripts/convert` - onnx, sbv2フォーマットへの変換スクリプト
- `sbv2_api` - 推論用 REST API
- `sbv2_core` - 推論コア部分
- `docker` - docker ビルドスクリプト
- `convert` - onnx, sbv2フォーマットへの変換スクリプト
## プログラミングある程度できる人向けREST API起動方法
### models をインストール
https://huggingface.co/neody/sbv2-api-assets/tree/main/deberta
から`tokenizer.json`,`debert.onnx`
https://huggingface.co/neody/sbv2-api-assets/tree/main/model
から`tsukuyomi.sbv2`
を models フォルダに配置
https://huggingface.co/googlefan/sbv2_onnx_models/tree/main
の`tokenizer.json`,`debert.onnx`,`tsukuyomi.sbv2`を models フォルダに配置
### .env ファイルの作成
@@ -75,7 +59,7 @@ CPUの場合は
```sh
docker run -it --rm -p 3000:3000 --name sbv2 \
-v ./models:/work/models --env-file .env \
ghcr.io/neodyland/sbv2-api:cpu
ghcr.io/tuna2134/sbv2-api:cpu
```
<details>
@@ -90,7 +74,7 @@ CPUの場合は
```bash
docker run --platform linux/amd64 -it --rm -p 3000:3000 --name sbv2 \
-v ./models:/work/models --env-file .env \
ghcr.io/neodyland/sbv2-api:cpu
ghcr.io/tuna2134/sbv2-api:cpu
```
</details>
@@ -99,7 +83,7 @@ CUDAの場合は
docker run -it --rm -p 3000:3000 --name sbv2 \
-v ./models:/work/models --env-file .env \
--gpus all \
ghcr.io/neodyland/sbv2-api:cuda
ghcr.io/tuna2134/sbv2-api:cuda
```
### 起動確認
@@ -130,10 +114,8 @@ curl http://localhost:3000/models
- `ADDR` `localhost:3000`などのようにサーバー起動アドレスをコントロールできます。
- `MODELS_PATH` sbv2モデルの存在するフォルダを指定できます。
- `RUST_LOG` おなじみlog levelです。
- `HOLDER_MAX_LOADED_MODElS` RAMにロードされるモデルの最大数を指定します。
## 謝辞
- [litagin02/Style-Bert-VITS2](https://github.com/litagin02/Style-Bert-VITS2) - このコードを書くにあたり、ベースとなる部分を参考にさせていただきました。
- [litagin02/Style-Bert-VITS2](https://github.com/litagin02/Style-Bert-VITS2) - このコードの書くにあたり、ベースとなる部分を参考にさせていただきました。
- [Googlefan](https://github.com/Googlefan256) - 彼にモデルを ONNX ヘ変換および効率化をする方法を教わりました。
- [Aivis Project](https://github.com/Aivis-Project/AivisSpeech-Engine) - 辞書部分

14
content.txt Normal file
View File

@@ -0,0 +1,14 @@
悪徳貴族として名高いヴェレット家の長男――オウガ・ヴェレットは転生者である。
ブラック企業に勤め、過労死した彼には一つの夢があった。
「可愛いハーレム作って、美味い物を食べる。領民の税金で楽して好き放題な生活を送ってみせる！」
素晴らしき異世界ライフを夢見た彼は実現へ向けて、努力を始めた。
ハーレムを築くためにいじめられてる平民の子を助けて恩を売ってやったり。
労働力を手に入れるために多くの孤児を雇って教育したり。
反乱を起きても鎮圧できるように魔法学院へ通って魔法を極める。
「クックック……！　順調、順調！　未来は明るいなぁ！」
――オウガはまだ知らない。
楽な生活を送るためにしてきたことが評価され、世間から『聖者』様として呼ばれる未来を。

0
scripts/convert/README.md → convert/README.md
View File

6
scripts/convert/convert_deberta.py → convert/convert_deberta.py
View File

@@ -5,7 +5,6 @@ from transformers import AutoModelForMaskedLM, AutoTokenizer
import torch
from torch import nn
from argparse import ArgumentParser
import os
parser = ArgumentParser()
parser.add_argument("--model", default="ku-nlp/deberta-v2-large-japanese-char-wwm")
@@ -16,7 +15,7 @@ bert_models.load_tokenizer(Languages.JP, model_name)
tokenizer = bert_models.load_tokenizer(Languages.JP)
converter = BertConverter(tokenizer)
tokenizer = converter.converted()
tokenizer.save("../../models/tokenizer.json")
tokenizer.save("../models/tokenizer.json")
class ORTDeberta(nn.Module):
@@ -43,10 +42,9 @@ inputs = AutoTokenizer.from_pretrained(model_name)(
torch.onnx.export(
model,
(inputs["input_ids"], inputs["token_type_ids"], inputs["attention_mask"]),
"../../models/deberta.onnx",
"../models/deberta.onnx",
input_names=["input_ids", "token_type_ids", "attention_mask"],
output_names=["output"],
verbose=True,
dynamic_axes={"input_ids": {1: "batch_size"}, "attention_mask": {1: "batch_size"}},
)
os.system("onnxsim ../../models/deberta.onnx ../../models/deberta.onnx")

18
scripts/convert/convert_model.py → convert/convert_model.py
View File

@@ -36,7 +36,7 @@ data = array.tolist()
hyper_parameters = HyperParameters.load_from_json(config_file)
out_name = hyper_parameters.model_name
with open(f"../../models/style_vectors_{out_name}.json", "w") as f:
with open(f"../models/style_vectors_{out_name}.json", "w") as f:
json.dump(
{
"data": data,
@@ -127,7 +127,7 @@ torch.onnx.export(
torch.tensor(0.6777),
torch.tensor(0.8),
),
f"../../models/model_{out_name}.onnx",
f"../models/model_{out_name}.onnx",
verbose=True,
dynamic_axes={
"x_tst": {0: "batch_size", 1: "x_tst_max_length"},
@@ -153,11 +153,11 @@ torch.onnx.export(
],
output_names=["output"],
)
os.system(f"onnxsim ../../models/model_{out_name}.onnx ../../models/model_{out_name}.onnx")
onnxfile = open(f"../../models/model_{out_name}.onnx", "rb").read()
stylefile = open(f"../../models/style_vectors_{out_name}.json", "rb").read()
os.system(f"onnxsim ../models/model_{out_name}.onnx ../models/model_{out_name}.onnx")
onnxfile = open(f"../models/model_{out_name}.onnx", "rb").read()
stylefile = open(f"../models/style_vectors_{out_name}.json", "rb").read()
version = bytes("1", "utf8")
with taropen(f"../../models/tmp_{out_name}.sbv2tar", "w") as w:
with taropen(f"../models/tmp_{out_name}.sbv2tar", "w") as w:
def add_tar(f, b):
t = TarInfo(f)
@@ -167,9 +167,9 @@ with taropen(f"../../models/tmp_{out_name}.sbv2tar", "w") as w:
add_tar("version.txt", version)
add_tar("model.onnx", onnxfile)
add_tar("style_vectors.json", stylefile)
open(f"../../models/{out_name}.sbv2", "wb").write(
open(f"../models/{out_name}.sbv2", "wb").write(
ZstdCompressor(threads=-1, level=22).compress(
open(f"../../models/tmp_{out_name}.sbv2tar", "rb").read()
open(f"../models/tmp_{out_name}.sbv2tar", "rb").read()
)
)
os.unlink(f"../../models/tmp_{out_name}.sbv2tar")
os.unlink(f"../models/tmp_{out_name}.sbv2tar")

5
convert/requirements.txt Normal file
View File

@@ -0,0 +1,5 @@
style-bert-vits2
onnxsim
numpy<2
zstandard
onnxruntime

29
crates/sbv2_api/Cargo.toml
View File

@@ -1,29 +0,0 @@
[package]
name = "sbv2_api"
version.workspace = true
edition.workspace = true
description.workspace = true
readme.workspace = true
repository.workspace = true
documentation.workspace = true
license.workspace = true
[dependencies]
anyhow.workspace = true
axum = "0.8.7"
dotenvy.workspace = true
env_logger.workspace = true
log = "0.4.29"
sbv2_core = { version = "0.2.0-alpha6", path = "../sbv2_core", features = ["aivmx"] }
serde = { version = "1.0.228", features = ["derive"] }
tokio = { version = "1.48.0", features = ["full"] }
utoipa = { version = "5.4.0", features = ["axum_extras"] }
utoipa-scalar = { version = "0.3.0", features = ["axum"] }
[features]
coreml = ["sbv2_core/coreml"]
cuda = ["sbv2_core/cuda"]
cuda_tf32 = ["sbv2_core/cuda_tf32"]
dynamic = ["sbv2_core/dynamic"]
directml = ["sbv2_core/directml"]
tensorrt = ["sbv2_core/tensorrt"]

24
crates/sbv2_bindings/Cargo.toml
View File

@@ -1,24 +0,0 @@
[package]
name = "sbv2_bindings"
version.workspace = true
edition.workspace = true
description.workspace = true
readme.workspace = true
repository.workspace = true
documentation.workspace = true
license.workspace = true
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[lib]
name = "sbv2_bindings"
crate-type = ["cdylib"]
[dependencies]
anyhow.workspace = true
ndarray.workspace = true
pyo3 = { version = "0.27.2", features = ["anyhow"] }
sbv2_core = { path = "../sbv2_core", features = ["std"], default-features = false }
[features]
agpl_dict = ["sbv2_core/agpl_dict"]
default = ["agpl_dict"]

31
crates/sbv2_core/build.rs
View File

@@ -1,31 +0,0 @@
use dirs::home_dir;
use std::env;
use std::fs;
use std::io::copy;
use std::path::PathBuf;
fn main() -> Result<(), Box<dyn std::error::Error>> {
let static_dir = home_dir().unwrap().join(".cache/sbv2");
let static_path = static_dir.join("all.bin");
let out_path = PathBuf::from(&env::var("OUT_DIR").unwrap()).join("all.bin");
println!("cargo:rerun-if-changed=build.rs");
if static_path.exists() {
println!("cargo:info=Dictionary file already exists, skipping download.");
} else {
println!("cargo:warning=Downloading dictionary file...");
let mut response =
ureq::get("https://huggingface.co/neody/sbv2-api-assets/resolve/main/dic/all.bin")
.call()?;
let mut response = response.body_mut().as_reader();
if !static_dir.exists() {
fs::create_dir_all(static_dir)?;
}
let mut file = fs::File::create(&static_path)?;
copy(&mut response, &mut file)?;
}
if !out_path.exists() && fs::hard_link(&static_path, &out_path).is_err() {
println!("cargo:warning=Failed to create hard link, copying instead.");
fs::copy(static_path, out_path)?;
}
Ok(())
}

22
crates/sbv2_core/src/bert.rs
View File

@@ -1,22 +0,0 @@
use crate::error::Result;
use ndarray::{Array2, Ix2};
use ort::session::Session;
use ort::value::TensorRef;
pub fn predict(
session: &mut Session,
token_ids: Vec<i64>,
attention_masks: Vec<i64>,
) -> Result<Array2<f32>> {
let outputs = session.run(
ort::inputs! {
"input_ids" => TensorRef::from_array_view((vec![1, token_ids.len() as i64], token_ids.as_slice()))?,
"attention_mask" => TensorRef::from_array_view((vec![1, attention_masks.len() as i64], attention_masks.as_slice()))?,
}
)?;
let output = outputs["output"]
.try_extract_array::<f32>()?
.into_dimensionality::<Ix2>()?
.to_owned();
Ok(output)
}

106
crates/sbv2_core/src/model.rs
View File

@@ -1,106 +0,0 @@
use crate::error::Result;
use ndarray::{array, Array1, Array2, Array3, Axis, Ix3};
use ort::session::{builder::GraphOptimizationLevel, Session};
#[allow(clippy::vec_init_then_push, unused_variables)]
pub fn load_model<P: AsRef<[u8]>>(model_file: P, bert: bool) -> Result<Session> {
let mut exp = Vec::new();
#[cfg(feature = "tensorrt")]
{
if bert {
exp.push(
ort::execution_providers::TensorRTExecutionProvider::default()
.with_fp16(true)
.with_profile_min_shapes("input_ids:1x1,attention_mask:1x1")
.with_profile_max_shapes("input_ids:1x100,attention_mask:1x100")
.with_profile_opt_shapes("input_ids:1x25,attention_mask:1x25")
.build(),
);
}
}
#[cfg(feature = "cuda")]
{
#[allow(unused_mut)]
let mut cuda = ort::execution_providers::CUDAExecutionProvider::default();
#[cfg(feature = "cuda_tf32")]
{
cuda = cuda.with_tf32(true);
}
exp.push(cuda.build());
}
#[cfg(feature = "directml")]
{
exp.push(ort::execution_providers::DirectMLExecutionProvider::default().build());
}
#[cfg(feature = "coreml")]
{
exp.push(ort::execution_providers::CoreMLExecutionProvider::default().build());
}
exp.push(ort::execution_providers::CPUExecutionProvider::default().build());
Ok(Session::builder()?
.with_execution_providers(exp)?
.with_optimization_level(GraphOptimizationLevel::Level3)?
.with_intra_threads(num_cpus::get_physical())?
.with_parallel_execution(true)?
.with_inter_threads(num_cpus::get_physical())?
.commit_from_memory(model_file.as_ref())?)
}
#[allow(clippy::too_many_arguments)]
pub fn synthesize(
session: &mut Session,
bert_ori: Array2<f32>,
x_tst: Array1<i64>,
mut spk_ids: Array1<i64>,
tones: Array1<i64>,
lang_ids: Array1<i64>,
style_vector: Array1<f32>,
sdp_ratio: f32,
length_scale: f32,
noise_scale: f32,
noise_scale_w: f32,
) -> Result<Array3<f32>> {
let bert_ori = bert_ori.insert_axis(Axis(0));
let bert_ori = bert_ori.as_standard_layout();
let bert = ort::value::TensorRef::from_array_view(&bert_ori)?;
let mut x_tst_lengths = array![x_tst.shape()[0] as i64];
let x_tst_lengths = ort::value::TensorRef::from_array_view(&mut x_tst_lengths)?;
let mut x_tst = x_tst.insert_axis(Axis(0));
let x_tst = ort::value::TensorRef::from_array_view(&mut x_tst)?;
let mut lang_ids = lang_ids.insert_axis(Axis(0));
let lang_ids = ort::value::TensorRef::from_array_view(&mut lang_ids)?;
let mut tones = tones.insert_axis(Axis(0));
let tones = ort::value::TensorRef::from_array_view(&mut tones)?;
let mut style_vector = style_vector.insert_axis(Axis(0));
let style_vector = ort::value::TensorRef::from_array_view(&mut style_vector)?;
let sid = ort::value::TensorRef::from_array_view(&mut spk_ids)?;
let sdp_ratio = vec![sdp_ratio];
let sdp_ratio = ort::value::TensorRef::from_array_view((vec![1_i64], sdp_ratio.as_slice()))?;
let length_scale = vec![length_scale];
let length_scale =
ort::value::TensorRef::from_array_view((vec![1_i64], length_scale.as_slice()))?;
let noise_scale = vec![noise_scale];
let noise_scale =
ort::value::TensorRef::from_array_view((vec![1_i64], noise_scale.as_slice()))?;
let noise_scale_w = vec![noise_scale_w];
let noise_scale_w =
ort::value::TensorRef::from_array_view((vec![1_i64], noise_scale_w.as_slice()))?;
let outputs = session.run(ort::inputs! {
"x_tst" => x_tst,
"x_tst_lengths" => x_tst_lengths,
"sid" => sid,
"tones" => tones,
"language" => lang_ids,
"bert" => bert,
"style_vec" => style_vector,
"sdp_ratio" => sdp_ratio,
"length_scale" => length_scale,
"noise_scale" => noise_scale,
"noise_scale_w" => noise_scale_w,
})?;
let audio_array = outputs["output"]
.try_extract_array::<f32>()?
.into_dimensionality::<Ix3>()?
.to_owned();
Ok(audio_array)
}

19
crates/sbv2_editor/Cargo.toml
View File

@@ -1,19 +0,0 @@
[package]
name = "sbv2_editor"
version.workspace = true
edition.workspace = true
description.workspace = true
license.workspace = true
readme.workspace = true
repository.workspace = true
documentation.workspace = true
[dependencies]
anyhow.workspace = true
axum = "0.8.1"
dotenvy.workspace = true
env_logger.workspace = true
log = "0.4.27"
sbv2_core = { version = "0.2.0-alpha6", path = "../sbv2_core", features = ["aivmx"] }
serde = { version = "1.0.219", features = ["derive"] }
tokio = { version = "1.44.1", features = ["full"] }

2
crates/sbv2_editor/README.md
View File

@@ -1,2 +0,0 @@
# sbv2-voicevox
sbv2-apiをvoicevox化します。

226
crates/sbv2_editor/query2.json
View File

@@ -1,226 +0,0 @@
{
"accent_phrases": [
{
"moras": [
{
"text": "コ",
"consonant": "k",
"consonant_length": 0.10002632439136505,
"vowel": "o",
"vowel_length": 0.15740256011486053,
"pitch": 5.749961853027344
},
{
"text": "ン",
"consonant": null,
"consonant_length": null,
"vowel": "N",
"vowel_length": 0.08265873789787292,
"pitch": 5.89122200012207
},
{
"text": "ニ",
"consonant": "n",
"consonant_length": 0.03657080978155136,
"vowel": "i",
"vowel_length": 0.1175866425037384,
"pitch": 5.969866752624512
},
{
"text": "チ",
"consonant": "ch",
"consonant_length": 0.09005842357873917,
"vowel": "i",
"vowel_length": 0.08666137605905533,
"pitch": 5.958892822265625
},
{
"text": "ワ",
"consonant": "w",
"consonant_length": 0.07833231985569,
"vowel": "a",
"vowel_length": 0.21250136196613312,
"pitch": 5.949411392211914
}
],
"accent": 5,
"pause_mora": {
"text": "、",
"consonant": null,
"consonant_length": null,
"vowel": "pau",
"vowel_length": 0.4723339378833771,
"pitch": 0.0
},
"is_interrogative": false
},
{
"moras": [
{
"text": "オ",
"consonant": null,
"consonant_length": null,
"vowel": "o",
"vowel_length": 0.22004225850105286,
"pitch": 5.6870927810668945
},
{
"text": "ン",
"consonant": null,
"consonant_length": null,
"vowel": "N",
"vowel_length": 0.09161105751991272,
"pitch": 5.93472957611084
},
{
"text": "セ",
"consonant": "s",
"consonant_length": 0.08924821764230728,
"vowel": "e",
"vowel_length": 0.14142127335071564,
"pitch": 6.121850490570068
},
{
"text": "エ",
"consonant": null,
"consonant_length": null,
"vowel": "e",
"vowel_length": 0.10636933892965317,
"pitch": 6.157896041870117
},
{
"text": "ゴ",
"consonant": "g",
"consonant_length": 0.07600915431976318,
"vowel": "o",
"vowel_length": 0.09598273783922195,
"pitch": 6.188933849334717
},
{
"text": "オ",
"consonant": null,
"consonant_length": null,
"vowel": "o",
"vowel_length": 0.1079121008515358,
"pitch": 6.235202789306641
},
{
"text": "セ",
"consonant": "s",
"consonant_length": 0.09591838717460632,
"vowel": "e",
"vowel_length": 0.10286372154951096,
"pitch": 6.153214454650879
},
{
"text": "エ",
"consonant": null,
"consonant_length": null,
"vowel": "e",
"vowel_length": 0.08992656320333481,
"pitch": 6.02571439743042
},
{
"text": "ノ",
"consonant": "n",
"consonant_length": 0.05660202354192734,
"vowel": "o",
"vowel_length": 0.09676017612218857,
"pitch": 5.711844444274902
}
],
"accent": 5,
"pause_mora": null,
"is_interrogative": false
},
{
"moras": [
{
"text": "セ",
"consonant": "s",
"consonant_length": 0.07805486768484116,
"vowel": "e",
"vowel_length": 0.09617523103952408,
"pitch": 5.774399280548096
},
{
"text": "カ",
"consonant": "k",
"consonant_length": 0.06712044775485992,
"vowel": "a",
"vowel_length": 0.148829385638237,
"pitch": 6.063965797424316
},
{
"text": "イ",
"consonant": null,
"consonant_length": null,
"vowel": "i",
"vowel_length": 0.11061104387044907,
"pitch": 6.040698051452637
},
{
"text": "エ",
"consonant": null,
"consonant_length": null,
"vowel": "e",
"vowel_length": 0.13046696782112122,
"pitch": 5.806027889251709
}
],
"accent": 1,
"pause_mora": null,
"is_interrogative": false
},
{
"moras": [
{
"text": "ヨ",
"consonant": "y",
"consonant_length": 0.07194744795560837,
"vowel": "o",
"vowel_length": 0.08622600883245468,
"pitch": 5.694094657897949
},
{
"text": "オ",
"consonant": null,
"consonant_length": null,
"vowel": "o",
"vowel_length": 0.10635452717542648,
"pitch": 5.787222385406494
},
{
"text": "コ",
"consonant": "k",
"consonant_length": 0.07077334076166153,
"vowel": "o",
"vowel_length": 0.09248624742031097,
"pitch": 5.793357849121094
},
{
"text": "ソ",
"consonant": "s",
"consonant_length": 0.08705667406320572,
"vowel": "o",
"vowel_length": 0.2238258570432663,
"pitch": 5.643765449523926
}
],
"accent": 1,
"pause_mora": null,
"is_interrogative": false
}
],
"speedScale": 1.0,
"pitchScale": 0.0,
"intonationScale": 1.0,
"volumeScale": 1.0,
"prePhonemeLength": 0.1,
"postPhonemeLength": 0.1,
"pauseLength": null,
"pauseLengthScale": 1.0,
"outputSamplingRate": 24000,
"outputStereo": false,
"kana": "コンニチワ'、オンセエゴ'オセエノ/セ'カイエ/ヨ'オコソ"
}

27
crates/sbv2_editor/src/error.rs
View File

@@ -1,27 +0,0 @@
use axum::{
http::StatusCode,
response::{IntoResponse, Response},
};
pub type AppResult<T> = std::result::Result<T, AppError>;
pub struct AppError(anyhow::Error);
impl IntoResponse for AppError {
fn into_response(self) -> Response {
(
StatusCode::INTERNAL_SERVER_ERROR,
format!("Something went wrong: {}", self.0),
)
.into_response()
}
}
impl<E> From<E> for AppError
where
E: Into<anyhow::Error>,
{
fn from(err: E) -> Self {
Self(err.into())
}
}

197
crates/sbv2_editor/src/main.rs
View File

@@ -1,197 +0,0 @@
use axum::extract::State;
use axum::{
extract::Query,
http::header::CONTENT_TYPE,
response::IntoResponse,
routing::{get, post},
Json, Router,
};
use sbv2_core::tts_util::kata_tone2phone_tone;
use sbv2_core::{
tts::{SynthesizeOptions, TTSModelHolder},
tts_util::preprocess_parse_text,
};
use serde::{Deserialize, Serialize};
use tokio::{fs, net::TcpListener, sync::Mutex};
use std::env;
use std::sync::Arc;
use error::AppResult;
mod error;
#[derive(Deserialize)]
struct RequestCreateAudioQuery {
text: String,
}
#[derive(Serialize, Deserialize)]
struct AudioQuery {
kana: String,
tone: i32,
}
#[derive(Serialize)]
struct ResponseCreateAudioQuery {
audio_query: Vec<AudioQuery>,
text: String,
}
async fn create_audio_query(
State(state): State<AppState>,
Query(request): Query<RequestCreateAudioQuery>,
) -> AppResult<impl IntoResponse> {
let (text, process) = {
let tts_model = state.tts_model.lock().await;
preprocess_parse_text(&request.text, &tts_model.jtalk)?
};
let kana_tone_list = process.g2kana_tone()?;
let audio_query = kana_tone_list
.iter()
.map(|(kana, tone)| AudioQuery {
kana: kana.clone(),
tone: *tone,
})
.collect::<Vec<_>>();
Ok(Json(ResponseCreateAudioQuery { audio_query, text }))
}
#[derive(Deserialize)]
pub struct RequestSynthesis {
text: String,
speaker_id: i64,
sdp_ratio: f32,
length_scale: f32,
style_id: i32,
audio_query: Vec<AudioQuery>,
ident: String,
}
async fn synthesis(
State(state): State<AppState>,
Json(request): Json<RequestSynthesis>,
) -> AppResult<impl IntoResponse> {
let phone_tone = request
.audio_query
.iter()
.map(|query| (query.kana.clone(), query.tone))
.collect::<Vec<_>>();
let phone_tone = kata_tone2phone_tone(phone_tone);
let tones = phone_tone.iter().map(|(_, tone)| *tone).collect::<Vec<_>>();
let buffer = {
let mut tts_model = state.tts_model.lock().await;
tts_model.easy_synthesize_neo(
&request.ident,
&request.text,
Some(tones),
request.style_id,
request.speaker_id,
SynthesizeOptions {
sdp_ratio: request.sdp_ratio,
length_scale: request.length_scale,
..Default::default()
},
)?
};
Ok(([(CONTENT_TYPE, "audio/wav")], buffer))
}
#[derive(Clone)]
struct AppState {
tts_model: Arc<Mutex<TTSModelHolder>>,
}
impl AppState {
pub async fn new() -> anyhow::Result<Self> {
let mut tts_model = TTSModelHolder::new(
&fs::read(env::var("BERT_MODEL_PATH")?).await?,
&fs::read(env::var("TOKENIZER_PATH")?).await?,
env::var("HOLDER_MAX_LOADED_MODElS")
.ok()
.and_then(|x| x.parse().ok()),
)?;
let models = env::var("MODELS_PATH").unwrap_or("models".to_string());
let mut f = fs::read_dir(&models).await?;
let mut entries = vec![];
while let Ok(Some(e)) = f.next_entry().await {
let name = e.file_name().to_string_lossy().to_string();
if name.ends_with(".onnx") && name.starts_with("model_") {
let name_len = name.len();
let name = name.chars();
entries.push(
name.collect::<Vec<_>>()[6..name_len - 5]
.iter()
.collect::<String>(),
);
} else if name.ends_with(".sbv2") {
let entry = &name[..name.len() - 5];
log::info!("Try loading: {entry}");
let sbv2_bytes = match fs::read(format!("{models}/{entry}.sbv2")).await {
Ok(b) => b,
Err(e) => {
log::warn!("Error loading sbv2_bytes from file {entry}: {e}");
continue;
}
};
if let Err(e) = tts_model.load_sbv2file(entry, sbv2_bytes) {
log::warn!("Error loading {entry}: {e}");
};
log::info!("Loaded: {entry}");
} else if name.ends_with(".aivmx") {
let entry = &name[..name.len() - 6];
log::info!("Try loading: {entry}");
let aivmx_bytes = match fs::read(format!("{models}/{entry}.aivmx")).await {
Ok(b) => b,
Err(e) => {
log::warn!("Error loading aivmx bytes from file {entry}: {e}");
continue;
}
};
if let Err(e) = tts_model.load_aivmx(entry, aivmx_bytes) {
log::error!("Error loading {entry}: {e}");
}
log::info!("Loaded: {entry}");
}
}
for entry in entries {
log::info!("Try loading: {entry}");
let style_vectors_bytes =
match fs::read(format!("{models}/style_vectors_{entry}.json")).await {
Ok(b) => b,
Err(e) => {
log::warn!("Error loading style_vectors_bytes from file {entry}: {e}");
continue;
}
};
let vits2_bytes = match fs::read(format!("{models}/model_{entry}.onnx")).await {
Ok(b) => b,
Err(e) => {
log::warn!("Error loading vits2_bytes from file {entry}: {e}");
continue;
}
};
if let Err(e) = tts_model.load(&entry, style_vectors_bytes, vits2_bytes) {
log::warn!("Error loading {entry}: {e}");
};
log::info!("Loaded: {entry}");
}
Ok(Self {
tts_model: Arc::new(Mutex::new(tts_model)),
})
}
}
#[tokio::main]
async fn main() -> anyhow::Result<()> {
dotenvy::dotenv_override().ok();
env_logger::init();
let app = Router::new()
.route("/", get(|| async { "Hello, world!" }))
.route("/audio_query", get(create_audio_query))
.route("/synthesis", post(synthesis))
.with_state(AppState::new().await?);
let listener = TcpListener::bind("0.0.0.0:8080").await?;
axum::serve(listener, app).await?;
Ok(())
}

2
crates/sbv2_wasm/README.md
View File

@@ -1,2 +0,0 @@
# StyleBertVITS2 wasm
refer to https://github.com/neodyland/sbv2-api

8
crates/sbv2_wasm/build.sh
View File

@@ -1,8 +0,0 @@
#!/bin/sh
wasm-pack build --target web ./crates/sbv2_wasm --release
wasm-opt -O3 -o ./crates/sbv2_wasm/pkg/sbv2_wasm_bg.wasm ./crates/sbv2_wasm/pkg/sbv2_wasm_bg.wasm
wasm-strip ./crates/sbv2_wasm/pkg/sbv2_wasm_bg.wasm
mkdir -p ./crates/sbv2_wasm/dist
cp ./crates/sbv2_wasm/pkg/sbv2_wasm_bg.wasm ./crates/sbv2_wasm/dist/sbv2_wasm_bg.wasm
cd ./crates/sbv2_wasm
pnpm build

9
docker/cpu.Dockerfile Normal file
View File

@@ -0,0 +1,9 @@
FROM rust AS builder
WORKDIR /work
COPY . .
RUN cargo build -r --bin sbv2_api
FROM gcr.io/distroless/cc-debian12
WORKDIR /work
COPY --from=builder /work/target/release/sbv2_api /work/main
COPY --from=builder /work/target/release/*.so /work
CMD ["/work/main"]

13
scripts/docker/cuda.Dockerfile → docker/cuda.Dockerfile
View File

@@ -2,16 +2,9 @@ FROM rust AS builder
WORKDIR /work
COPY . .
RUN cargo build -r --bin sbv2_api -F cuda,cuda_tf32
FROM ubuntu AS upx
WORKDIR /work
RUN apt update && apt-get install -y upx binutils
COPY --from=builder /work/target/release/sbv2_api /work/main
COPY --from=builder /work/target/release/*.so /work
RUN upx --best --lzma /work/main
RUN find /work -maxdepth 1 -name "*.so" -exec strip --strip-unneeded {} +
FROM nvidia/cuda:12.3.2-cudnn9-runtime-ubuntu22.04
WORKDIR /work
COPY --from=upx /work/main /work/main
COPY --from=upx /work/*.so /work
COPY --from=builder /work/target/release/sbv2_api /work/main
COPY --from=builder /work/target/release/*.so /work
ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/work
CMD ["/work/main"]
CMD ["/work/main"]

2
scripts/docker/run_cpu.sh → docker/run_cpu.sh
View File

@@ -1,3 +1,3 @@
docker run -it --rm -p 3000:3000 --name sbv2 \
-v ./models:/work/models --env-file .env \
ghcr.io/neodyland/sbv2-api:cpu
ghcr.io/tuna2134/sbv2-api:cpu

2
scripts/docker/run_cuda.sh → docker/run_cuda.sh
View File

@@ -1,4 +1,4 @@
docker run -it --rm -p 3000:3000 --name sbv2 \
-v ./models:/work/models --env-file .env \
--gpus all \
ghcr.io/neodyland/sbv2-api:cuda
ghcr.io/tuna2134/sbv2-api:cuda

24
sbv2_api/Cargo.toml Normal file
View File

@@ -0,0 +1,24 @@
[package]
name = "sbv2_api"
version = "0.2.0-alpha4"
edition = "2021"
[dependencies]
anyhow.workspace = true
axum = "0.7.5"
dotenvy.workspace = true
env_logger.workspace = true
log = "0.4.22"
sbv2_core = { version = "0.2.0-alpha2", path = "../sbv2_core", features = ["aivmx"] }
serde = { version = "1.0.210", features = ["derive"] }
tokio = { version = "1.40.0", features = ["full"] }
utoipa = { version = "5.0.0", features = ["axum_extras"] }
utoipa-scalar = { version = "0.2.0", features = ["axum"] }
[features]
coreml = ["sbv2_core/coreml"]
cuda = ["sbv2_core/cuda"]
cuda_tf32 = ["sbv2_core/cuda_tf32"]
dynamic = ["sbv2_core/dynamic"]
directml = ["sbv2_core/directml"]
tensorrt = ["sbv2_core/tensorrt"]

0
crates/sbv2_api/build.rs → sbv2_api/build.rs
View File

0
crates/sbv2_api/src/error.rs → sbv2_api/src/error.rs
View File

4
crates/sbv2_api/src/main.rs → sbv2_api/src/main.rs
View File

@@ -53,16 +53,12 @@ struct SynthesizeRequest {
text: String,
ident: String,
#[serde(default = "sdp_default")]
#[schema(example = 0.0_f32)]
sdp_ratio: f32,
#[serde(default = "length_default")]
#[schema(example = 1.0_f32)]
length_scale: f32,
#[serde(default = "style_id_default")]
#[schema(example = 0_i32)]
style_id: i32,
#[serde(default = "speaker_id_default")]
#[schema(example = 0_i64)]
speaker_id: i64,
}

15
sbv2_bindings/Cargo.toml Normal file
View File

@@ -0,0 +1,15 @@
[package]
name = "sbv2_bindings"
version = "0.2.0-alpha4"
edition = "2021"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[lib]
name = "sbv2_bindings"
crate-type = ["cdylib"]
[dependencies]
anyhow.workspace = true
ndarray.workspace = true
pyo3 = { version = "0.22.0", features = ["anyhow"] }
sbv2_core = { version = "0.2.0-alpha2", path = "../sbv2_core" }

2
scripts/sbv2-bindings-colab.ipynb → sbv2_bindings/examples/basic.ipynb
View File

@@ -16,7 +16,7 @@
"outputs": [],
"source": [
"# 必要なパッケージのインストール\n",
"%pip install sbv2_bindings\n",
"!pip install sbv2_bindings\n",
"\n",
"# 必要なモジュールのインポート\n",
"import os\n",

6
scripts/sbv2-test-bindings.py → sbv2_bindings/examples/basic.py
View File

@@ -3,16 +3,16 @@ from sbv2_bindings import TTSModel
def main():
print("Loading models...")
model = TTSModel.from_path("./models/debert.onnx", "./models/tokenizer.json")
model = TTSModel.from_path("../models/debert.onnx", "../models/tokenizer.json")
print("Models loaded!")
model.load_sbv2file_from_path("amitaro", "./models/amitaro.sbv2")
model.load_sbv2file_from_path("amitaro", "../models/amitaro.sbv2")
print("All setup is done!")
style_vector = model.get_style_vector("amitaro", 0, 1.0)
with open("output.wav", "wb") as f:
f.write(
model.synthesize("おはようございます。", "amitaro", 0, 0, 0.0, 0.5)
model.synthesize("おはようございます。", "amitaro", style_vector, 0.0, 0.5)
)

0
crates/sbv2_bindings/pyproject.toml → sbv2_bindings/pyproject.toml
View File

0
crates/sbv2_bindings/src/lib.rs → sbv2_bindings/src/lib.rs
View File

7
crates/sbv2_bindings/src/sbv2.rs → sbv2_bindings/src/sbv2.rs
View File

@@ -107,7 +107,7 @@ impl TTSModel {
/// style_vector : StyleVector
/// スタイルベクトル
fn get_style_vector(
&mut self,
&self,
ident: String,
style_id: i32,
weight: f32,
@@ -136,7 +136,6 @@ impl TTSModel {
/// -------
/// voice_data : bytes
/// 音声データ
#[allow(clippy::too_many_arguments)]
fn synthesize<'p>(
&'p mut self,
py: Python<'p>,
@@ -146,7 +145,7 @@ impl TTSModel {
speaker_id: i64,
sdp_ratio: f32,
length_scale: f32,
) -> anyhow::Result<Bound<'p, PyBytes>> {
) -> anyhow::Result<Bound<PyBytes>> {
let data = self.model.easy_synthesize(
ident.as_str(),
&text,
@@ -158,7 +157,7 @@ impl TTSModel {
..Default::default()
},
)?;
Ok(PyBytes::new(py, &data))
Ok(PyBytes::new_bound(py, &data))
}
fn unload(&mut self, ident: String) -> bool {

0
crates/sbv2_bindings/src/style.rs → sbv2_bindings/src/style.rs
View File

39
crates/sbv2_core/Cargo.toml → sbv2_core/Cargo.toml
View File

@@ -1,12 +1,12 @@
[package]
name = "sbv2_core"
version.workspace = true
edition.workspace = true
description.workspace = true
readme.workspace = true
repository.workspace = true
documentation.workspace = true
license.workspace = true
description = "Style-Bert-VITSの推論ライブラリ"
version = "0.2.0-alpha4"
edition = "2021"
license = "MIT"
readme = "../README.md"
repository = "https://github.com/tuna2134/sbv2-api"
documentation = "https://docs.rs/sbv2_core"
[dependencies]
anyhow.workspace = true
@@ -14,34 +14,29 @@ base64 = { version = "0.22.1", optional = true }
dotenvy.workspace = true
env_logger.workspace = true
hound = "3.5.1"
jpreprocess = { version = "0.13.2", features = ["naist-jdic"] }
jpreprocess = { version = "0.10.0", features = ["naist-jdic"] }
ndarray.workspace = true
npyz = { version = "0.8.4", optional = true }
num_cpus = "1.17.0"
npyz = { version = "0.8.3", optional = true }
num_cpus = "1.16.0"
once_cell.workspace = true
ort = { git = "https://github.com/pykeio/ort.git", version = "2.0.0-rc.9", optional = true }
regex = "1.12.2"
serde = { version = "1.0.228", features = ["derive"] }
serde_json = "1.0.145"
ort = { git = "https://github.com/pykeio/ort.git", version = "2.0.0-rc.8", optional = true }
regex = "1.10.6"
serde = { version = "1.0.210", features = ["derive"] }
serde_json = "1.0.128"
tar = "0.4.41"
thiserror = "2.0.17"
tokenizers = { version = "0.22.2", default-features = false }
thiserror = "1.0.63"
tokenizers = { version = "0.20.0", default-features = false }
zstd = "0.13.2"
[features]
cuda = ["ort/cuda", "std"]
cuda_tf32 = ["std", "cuda"]
agpl_dict = []
std = ["dep:ort", "tokenizers/progressbar", "tokenizers/onig", "tokenizers/esaxx_fast"]
dynamic = ["ort/load-dynamic", "std"]
directml = ["ort/directml", "std"]
tensorrt = ["ort/tensorrt", "std"]
coreml = ["ort/coreml", "std"]
default = ["std", "agpl_dict"]
default = ["std"]
no_std = ["tokenizers/unstable_wasm"]
aivmx = ["npyz", "base64"]
base64 = ["dep:base64"]
[build-dependencies]
dirs = "6.0.0"
ureq = "3.1.4"

0
crates/sbv2_core/mora_convert.py → sbv2_core/mora_convert.py
View File

23
sbv2_core/src/bert.rs Normal file
View File

@@ -0,0 +1,23 @@
use crate::error::Result;
use ndarray::{Array2, Ix2};
use ort::Session;
pub fn predict(
session: &Session,
token_ids: Vec<i64>,
attention_masks: Vec<i64>,
) -> Result<Array2<f32>> {
let outputs = session.run(
ort::inputs! {
"input_ids" => Array2::from_shape_vec((1, token_ids.len()), token_ids).unwrap(),
"attention_mask" => Array2::from_shape_vec((1, attention_masks.len()), attention_masks).unwrap(),
}?
)?;
let output = outputs["output"]
.try_extract_tensor::<f32>()?
.into_dimensionality::<Ix2>()?
.to_owned();
Ok(output)
}

4
crates/sbv2_core/src/error.rs → sbv2_core/src/error.rs
View File

@@ -6,8 +6,6 @@ pub enum Error {
TokenizerError(#[from] tokenizers::Error),
#[error("JPreprocess error: {0}")]
JPreprocessError(#[from] jpreprocess::error::JPreprocessError),
#[error("Lindera error: {0}")]
LinderaError(String),
#[cfg(feature = "std")]
#[error("ONNX error: {0}")]
OrtError(#[from] ort::Error),
@@ -28,8 +26,6 @@ pub enum Error {
Base64Error(#[from] base64::DecodeError),
#[error("other")]
OtherError(String),
#[error("Style error: {0}")]
StyleError(String),
}
pub type Result<T> = std::result::Result<T, Error>;

265
crates/sbv2_core/src/jtalk.rs → sbv2_core/src/jtalk.rs
View File

@@ -1,204 +1,21 @@
/*
このファイルのコードは
https://github.com/litagin02/Style-Bert-VITS2/blob/master/style_bert_vits2/nlp/japanese/g2p.py
を参考にRustに書き換えています。
以下はライセンスです。
GNU LESSER GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
This version of the GNU Lesser General Public License incorporates
the terms and conditions of version 3 of the GNU General Public
License, supplemented by the additional permissions listed below.
0. Additional Definitions.
As used herein, "this License" refers to version 3 of the GNU Lesser
General Public License, and the "GNU GPL" refers to version 3 of the GNU
General Public License.
"The Library" refers to a covered work governed by this License,
other than an Application or a Combined Work as defined below.
An "Application" is any work that makes use of an interface provided
by the Library, but which is not otherwise based on the Library.
Defining a subclass of a class defined by the Library is deemed a mode
of using an interface provided by the Library.
A "Combined Work" is a work produced by combining or linking an
Application with the Library. The particular version of the Library
with which the Combined Work was made is also called the "Linked
Version".
The "Minimal Corresponding Source" for a Combined Work means the
Corresponding Source for the Combined Work, excluding any source code
for portions of the Combined Work that, considered in isolation, are
based on the Application, and not on the Linked Version.
The "Corresponding Application Code" for a Combined Work means the
object code and/or source code for the Application, including any data
and utility programs needed for reproducing the Combined Work from the
Application, but excluding the System Libraries of the Combined Work.
1. Exception to Section 3 of the GNU GPL.
You may convey a covered work under sections 3 and 4 of this License
without being bound by section 3 of the GNU GPL.
2. Conveying Modified Versions.
If you modify a copy of the Library, and, in your modifications, a
facility refers to a function or data to be supplied by an Application
that uses the facility (other than as an argument passed when the
facility is invoked), then you may convey a copy of the modified
version:
a) under this License, provided that you make a good faith effort to
ensure that, in the event an Application does not supply the
function or data, the facility still operates, and performs
whatever part of its purpose remains meaningful, or
b) under the GNU GPL, with none of the additional permissions of
this License applicable to that copy.
3. Object Code Incorporating Material from Library Header Files.
The object code form of an Application may incorporate material from
a header file that is part of the Library. You may convey such object
code under terms of your choice, provided that, if the incorporated
material is not limited to numerical parameters, data structure
layouts and accessors, or small macros, inline functions and templates
(ten or fewer lines in length), you do both of the following:
a) Give prominent notice with each copy of the object code that the
Library is used in it and that the Library and its use are
covered by this License.
b) Accompany the object code with a copy of the GNU GPL and this license
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4. Combined Works.
You may convey a Combined Work under terms of your choice that,
taken together, effectively do not restrict modification of the
portions of the Library contained in the Combined Work and reverse
engineering for debugging such modifications, if you also do each of
the following:
a) Give prominent notice with each copy of the Combined Work that
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b) Accompany the Combined Work with a copy of the GNU GPL and this license
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c) For a Combined Work that displays copyright notices during
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e) Provide Installation Information, but only if you would otherwise
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GNU GPL, and only to the extent that such information is
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Combined Work produced by recombining or relinking the
Application with a modified version of the Linked Version. (If
you use option 4d0, the Installation Information must accompany
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for conveying Corresponding Source.)
5. Combined Libraries.
You may place library facilities that are a work based on the
Library side by side in a single library together with other library
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b) Give prominent notice with the combined library that part of it
is a work based on the Library, and explaining where to find the
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6. Revised Versions of the GNU Lesser General Public License.
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Library as you received it specifies that a certain numbered version
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If the Library as you received it specifies that a proxy can decide
whether future versions of the GNU Lesser General Public License shall
apply, that proxy's public statement of acceptance of any version is
permanent authorization for you to choose that version for the
Library.
*/
use crate::error::{Error, Result};
use crate::mora::{CONSONANTS, MORA_KATA_TO_MORA_PHONEMES, MORA_PHONEMES_TO_MORA_KATA, VOWELS};
use crate::mora::{MORA_KATA_TO_MORA_PHONEMES, VOWELS};
use crate::norm::{replace_punctuation, PUNCTUATIONS};
use jpreprocess::{kind, DefaultTokenizer, JPreprocess, SystemDictionaryConfig, UserDictionary};
use jpreprocess::*;
use once_cell::sync::Lazy;
use regex::Regex;
use std::cmp::Reverse;
use std::collections::HashSet;
use std::sync::Arc;
type JPreprocessType = JPreprocess<DefaultTokenizer>;
#[cfg(feature = "agpl_dict")]
fn agpl_dict() -> Result<Option<UserDictionary>> {
Ok(Some(
UserDictionary::load(include_bytes!(concat!(env!("OUT_DIR"), "/all.bin")))
.map_err(|e| Error::LinderaError(e.to_string()))?,
))
}
#[cfg(not(feature = "agpl_dict"))]
fn agpl_dict() -> Result<Option<UserDictionary>> {
Ok(None)
}
type JPreprocessType = JPreprocess<DefaultFetcher>;
fn initialize_jtalk() -> Result<JPreprocessType> {
let sdic =
SystemDictionaryConfig::Bundled(kind::JPreprocessDictionaryKind::NaistJdic).load()?;
let jpreprocess = JPreprocess::with_dictionaries(sdic, agpl_dict()?);
let config = JPreprocessConfig {
dictionary: SystemDictionaryConfig::Bundled(kind::JPreprocessDictionaryKind::NaistJdic),
user_dictionary: None,
};
let jpreprocess = JPreprocess::from_config(config)?;
Ok(jpreprocess)
}
@@ -248,34 +65,6 @@ static MORA_PATTERN: Lazy<Vec<String>> = Lazy::new(|| {
});
static LONG_PATTERN: Lazy<Regex> = Lazy::new(|| Regex::new(r"(\w)(ー*)").unwrap());
fn phone_tone_to_kana(phones: Vec<String>, tones: Vec<i32>) -> Vec<(String, i32)> {
let phones = &phones[1..];
let tones = &tones[1..];
let mut results = Vec::new();
let mut current_mora = String::new();
for ((phone, _next_phone), (&tone, &next_tone)) in phones
.iter()
.zip(phones.iter().skip(1))
.zip(tones.iter().zip(tones.iter().skip(1)))
{
if PUNCTUATIONS.contains(&phone.clone().as_str()) {
results.push((phone.to_string(), tone));
continue;
}
if CONSONANTS.contains(&phone.clone()) {
assert_eq!(current_mora, "");
assert_eq!(tone, next_tone);
current_mora = phone.to_string()
} else {
current_mora += phone;
let kana = MORA_PHONEMES_TO_MORA_KATA.get(&current_mora).unwrap();
results.push((kana.to_string(), tone));
current_mora = String::new();
}
}
results
}
pub struct JTalkProcess {
jpreprocess: Arc<JPreprocessType>,
parsed: Vec<String>,
@@ -295,24 +84,24 @@ impl JTalkProcess {
.map(|(_letter, tone)| *tone)
.collect();
if tone_values.len() == 1 {
assert!(tone_values == hash_set![0], "{tone_values:?}");
assert!(tone_values == hash_set![0], "{:?}", tone_values);
Ok(phone_tone_list)
} else if tone_values.len() == 2 {
if tone_values == hash_set![0, 1] {
Ok(phone_tone_list)
return Ok(phone_tone_list);
} else if tone_values == hash_set![-1, 0] {
Ok(phone_tone_list
return Ok(phone_tone_list
.iter()
.map(|x| {
let new_tone = if x.1 == -1 { 0 } else { 1 };
(x.0.clone(), new_tone)
})
.collect())
.collect());
} else {
Err(Error::ValueError("Invalid tone values 0".to_string()))
return Err(Error::ValueError("Invalid tone values 0".to_string()));
}
} else {
Err(Error::ValueError("Invalid tone values 1".to_string()))
return Err(Error::ValueError("Invalid tone values 1".to_string()));
}
}
@@ -365,11 +154,6 @@ impl JTalkProcess {
Ok((phones, tones, new_word2ph))
}
pub fn g2kana_tone(&self) -> Result<Vec<(String, i32)>> {
let (phones, tones, _) = self.g2p()?;
Ok(phone_tone_to_kana(phones, tones))
}
fn distribute_phone(n_phone: i32, n_word: i32) -> Vec<i32> {
let mut phones_per_word = vec![0; n_word as usize];
for _ in 0..n_phone {
@@ -398,12 +182,12 @@ impl JTalkProcess {
} else if PUNCTUATIONS.contains(&phone.as_str()) {
result.push((phone, 0));
} else {
println!("phones {phone_with_punct:?}");
println!("phone_tone_list: {phone_tone_list:?}");
println!("result: {result:?}");
println!("tone_index: {tone_index:?}");
println!("phone: {phone:?}");
return Err(Error::ValueError(format!("Mismatched phoneme: {phone}")));
println!("phones {:?}", phone_with_punct);
println!("phone_tone_list: {:?}", phone_tone_list);
println!("result: {:?}", result);
println!("tone_index: {:?}", tone_index);
println!("phone: {:?}", phone);
return Err(Error::ValueError(format!("Mismatched phoneme: {}", phone)));
}
}
@@ -448,7 +232,8 @@ impl JTalkProcess {
}
if !KATAKANA_PATTERN.is_match(&text) {
return Err(Error::ValueError(format!(
"Input must be katakana only: {text}"
"Input must be katakana only: {}",
text
)));
}
@@ -456,7 +241,7 @@ impl JTalkProcess {
let mora = mora.to_string();
let (consonant, vowel) = MORA_KATA_TO_MORA_PHONEMES.get(&mora).unwrap();
if consonant.is_none() {
text = text.replace(&mora, &format!(" {vowel}"));
text = text.replace(&mora, &format!(" {}", vowel));
} else {
text = text.replace(
&mora,
@@ -490,7 +275,7 @@ impl JTalkProcess {
let (string, pron) = self.parse_to_string_and_pron(parts.clone());
let mut yomi = pron.replace('’', "");
let word = replace_punctuation(string);
assert!(!yomi.is_empty(), "Empty yomi: {word}");
assert!(!yomi.is_empty(), "Empty yomi: {}", word);
if yomi == "、" {
if !word
.chars()
@@ -501,7 +286,7 @@ impl JTalkProcess {
yomi = word.clone();
}
} else if yomi == "？" {
assert!(word == "?", "yomi `？` comes from: {word}");
assert!(word == "?", "yomi `？` comes from: {}", word);
yomi = "?".to_string();
}
seq_text.push(word);

0
crates/sbv2_core/src/lib.rs → sbv2_core/src/lib.rs
View File

15
crates/sbv2_core/src/main.rs → sbv2_core/src/main.rs
View File

@@ -6,7 +6,7 @@ fn main_inner() -> anyhow::Result<()> {
use sbv2_core::tts;
dotenvy::dotenv_override().ok();
env_logger::init();
let text = "今日の天気は快晴です。";
let text = fs::read_to_string("content.txt")?;
let ident = "aaa";
let mut tts_holder = tts::TTSModelHolder::new(
&fs::read(env::var("BERT_MODEL_PATH")?)?,
@@ -15,22 +15,17 @@ fn main_inner() -> anyhow::Result<()> {
.ok()
.and_then(|x| x.parse().ok()),
)?;
let mp = env::var("MODEL_PATH")?;
let b = fs::read(&mp)?;
#[cfg(not(feature = "aivmx"))]
{
tts_holder.load_sbv2file(ident, b)?;
tts_holder.load_sbv2file(ident, fs::read(env::var("MODEL_PATH")?)?)?;
}
#[cfg(feature = "aivmx")]
{
if mp.ends_with(".sbv2") {
tts_holder.load_sbv2file(ident, b)?;
} else {
tts_holder.load_aivmx(ident, b)?;
}
tts_holder.load_aivmx(ident, fs::read(env::var("MODEL_PATH")?)?)?;
}
let audio = tts_holder.easy_synthesize(ident, text, 0, 0, tts::SynthesizeOptions::default())?;
let audio =
tts_holder.easy_synthesize(ident, &text, 0, 0, tts::SynthesizeOptions::default())?;
fs::write("output.wav", audio)?;
Ok(())

90
sbv2_core/src/model.rs Normal file
View File

@@ -0,0 +1,90 @@
use crate::error::Result;
use ndarray::{array, Array1, Array2, Array3, Axis, Ix3};
use ort::{GraphOptimizationLevel, Session};
#[allow(clippy::vec_init_then_push, unused_variables)]
pub fn load_model<P: AsRef<[u8]>>(model_file: P, bert: bool) -> Result<Session> {
let mut exp = Vec::new();
#[cfg(feature = "tensorrt")]
{
if bert {
exp.push(
ort::TensorRTExecutionProvider::default()
.with_fp16(true)
.with_profile_min_shapes("input_ids:1x1,attention_mask:1x1")
.with_profile_max_shapes("input_ids:1x100,attention_mask:1x100")
.with_profile_opt_shapes("input_ids:1x25,attention_mask:1x25")
.build(),
);
}
}
#[cfg(feature = "cuda")]
{
#[allow(unused_mut)]
let mut cuda = ort::CUDAExecutionProvider::default()
.with_conv_algorithm_search(ort::CUDAExecutionProviderCuDNNConvAlgoSearch::Default);
#[cfg(feature = "cuda_tf32")]
{
cuda = cuda.with_tf32(true);
}
exp.push(cuda.build());
}
#[cfg(feature = "directml")]
{
exp.push(ort::DirectMLExecutionProvider::default().build());
}
#[cfg(feature = "coreml")]
{
exp.push(ort::CoreMLExecutionProvider::default().build());
}
exp.push(ort::CPUExecutionProvider::default().build());
Ok(Session::builder()?
.with_execution_providers(exp)?
.with_optimization_level(GraphOptimizationLevel::Level3)?
.with_intra_threads(num_cpus::get_physical())?
.with_parallel_execution(true)?
.with_inter_threads(num_cpus::get_physical())?
.commit_from_memory(model_file.as_ref())?)
}
#[allow(clippy::too_many_arguments)]
pub fn synthesize(
session: &Session,
bert_ori: Array2<f32>,
x_tst: Array1<i64>,
sid: Array1<i64>,
tones: Array1<i64>,
lang_ids: Array1<i64>,
style_vector: Array1<f32>,
sdp_ratio: f32,
length_scale: f32,
noise_scale: f32,
noise_scale_w: f32,
) -> Result<Array3<f32>> {
let bert = bert_ori.insert_axis(Axis(0));
let x_tst_lengths: Array1<i64> = array![x_tst.shape()[0] as i64];
let x_tst = x_tst.insert_axis(Axis(0));
let lang_ids = lang_ids.insert_axis(Axis(0));
let tones = tones.insert_axis(Axis(0));
let style_vector = style_vector.insert_axis(Axis(0));
let outputs = session.run(ort::inputs! {
"x_tst" => x_tst,
"x_tst_lengths" => x_tst_lengths,
"sid" => sid,
"tones" => tones,
"language" => lang_ids,
"bert" => bert,
"style_vec" => style_vector,
"sdp_ratio" => array![sdp_ratio],
"length_scale" => array![length_scale],
"noise_scale" => array![noise_scale],
"noise_scale_w" => array![noise_scale_w]
}?)?;
let audio_array = outputs["output"]
.try_extract_tensor::<f32>()?
.into_dimensionality::<Ix3>()?
.to_owned();
Ok(audio_array)
}

23
crates/sbv2_core/src/mora.rs → sbv2_core/src/mora.rs
View File

@@ -25,21 +25,6 @@ static MORA_LIST_ADDITIONAL: Lazy<Vec<Mora>> = Lazy::new(|| {
data.additional
});
pub static MORA_PHONEMES_TO_MORA_KATA: Lazy<HashMap<String, String>> = Lazy::new(|| {
let mut map = HashMap::new();
for mora in MORA_LIST_MINIMUM.iter() {
map.insert(
format!(
"{}{}",
mora.consonant.clone().unwrap_or("".to_string()),
mora.vowel
),
mora.mora.clone(),
);
}
map
});
pub static MORA_KATA_TO_MORA_PHONEMES: Lazy<HashMap<String, (Option<String>, String)>> =
Lazy::new(|| {
let mut map = HashMap::new();
@@ -52,12 +37,4 @@ pub static MORA_KATA_TO_MORA_PHONEMES: Lazy<HashMap<String, (Option<String>, Str
map
});
pub static CONSONANTS: Lazy<Vec<String>> = Lazy::new(|| {
let consonants = MORA_KATA_TO_MORA_PHONEMES
.values()
.filter_map(|(consonant, _)| consonant.clone())
.collect::<Vec<_>>();
consonants
});
pub const VOWELS: [&str; 6] = ["a", "i", "u", "e", "o", "N"];

0
crates/sbv2_core/src/mora_list.json → sbv2_core/src/mora_list.json
View File

0
crates/sbv2_core/src/nlp.rs → sbv2_core/src/nlp.rs
View File

0
crates/sbv2_core/src/norm.rs → sbv2_core/src/norm.rs
View File

0
crates/sbv2_core/src/sbv2file.rs → sbv2_core/src/sbv2file.rs
View File

14
crates/sbv2_core/src/style.rs → sbv2_core/src/style.rs
View File

@@ -1,4 +1,4 @@
use crate::error::{Error, Result};
use crate::error::Result;
use ndarray::{s, Array1, Array2};
use serde::Deserialize;
@@ -21,18 +21,6 @@ pub fn get_style_vector(
style_id: i32,
weight: f32,
) -> Result<Array1<f32>> {
if style_vectors.shape().len() != 2 {
return Err(Error::StyleError(
"Invalid shape for style vectors".to_string(),
));
}
if style_id < 0 || style_id >= style_vectors.shape()[0] as i32 {
return Err(Error::StyleError(format!(
"Invalid style ID: {}. Max ID: {}",
style_id,
style_vectors.shape()[0] - 1
)));
}
let mean = style_vectors.slice(s![0, ..]).to_owned();
let style_vector = style_vectors.slice(s![style_id as usize, ..]).to_owned();
let diff = (style_vector - &mean) * weight;

0
crates/sbv2_core/src/tokenizer.rs → sbv2_core/src/tokenizer.rs
View File

188
crates/sbv2_core/src/tts.rs → sbv2_core/src/tts.rs
View File

@@ -5,7 +5,7 @@ use base64::prelude::{Engine as _, BASE64_STANDARD};
#[cfg(feature = "aivmx")]
use ndarray::ShapeBuilder;
use ndarray::{concatenate, Array1, Array2, Array3, Axis};
use ort::session::Session;
use ort::Session;
#[cfg(feature = "aivmx")]
use std::io::Cursor;
use tokenizers::Tokenizer;
@@ -41,7 +41,7 @@ pub struct TTSModelHolder {
tokenizer: Tokenizer,
bert: Session,
models: Vec<TTSModel>,
pub jtalk: jtalk::JTalk,
jtalk: jtalk::JTalk,
max_loaded_models: Option<usize>,
}
@@ -91,7 +91,7 @@ impl TTSModelHolder {
}
let model = model::load_model(&aivmx_bytes, false)?;
let metadata = model.metadata()?;
if let Some(aivm_style_vectors) = metadata.custom("aivm_style_vectors") {
if let Some(aivm_style_vectors) = metadata.custom("aivm_style_vectors")? {
let aivm_style_vectors = BASE64_STANDARD.decode(aivm_style_vectors)?;
let style_vectors = Cursor::new(&aivm_style_vectors);
let reader = npyz::NpyFile::new(style_vectors)?;
@@ -200,83 +200,61 @@ impl TTSModelHolder {
/// This function is for low-level usage, use `easy_synthesize` for high-level usage.
#[allow(clippy::type_complexity)]
pub fn parse_text(
&mut self,
&self,
text: &str,
) -> Result<(Array2<f32>, Array1<i64>, Array1<i64>, Array1<i64>)> {
crate::tts_util::parse_text_blocking(
text,
None,
&self.jtalk,
&self.tokenizer,
|token_ids, attention_masks| {
crate::bert::predict(&mut self.bert, token_ids, attention_masks)
crate::bert::predict(&self.bert, token_ids, attention_masks)
},
)
}
#[allow(clippy::type_complexity)]
pub fn parse_text_neo(
&mut self,
text: String,
given_tones: Option<Vec<i32>>,
) -> Result<(Array2<f32>, Array1<i64>, Array1<i64>, Array1<i64>)> {
crate::tts_util::parse_text_blocking(
&text,
given_tones,
&self.jtalk,
&self.tokenizer,
|token_ids, attention_masks| {
crate::bert::predict(&mut self.bert, token_ids, attention_masks)
},
)
}
fn find_model<I: Into<TTSIdent>>(&mut self, ident: I) -> Result<&mut TTSModel> {
fn find_model<I: Into<TTSIdent>>(&self, ident: I) -> Result<&TTSModel> {
let ident = ident.into();
self.models
.iter_mut()
.iter()
.find(|m| m.ident == ident)
.ok_or(Error::ModelNotFoundError(ident.to_string()))
}
fn find_and_load_model<I: Into<TTSIdent>>(&mut self, ident: I) -> Result<bool> {
let ident = ident.into();
// Locate target model entry
let target_index = self
.models
.iter()
.position(|m| m.ident == ident)
.ok_or(Error::ModelNotFoundError(ident.to_string()))?;
// Already loaded
if self.models[target_index].vits2.is_some() {
return Ok(true);
}
// Get bytes to build a Session
let bytes = self.models[target_index]
.bytes
.clone()
.ok_or(Error::ModelNotFoundError(ident.to_string()))?;
// Enforce max loaded models by evicting a different loaded model's session, not removing the entry
let (bytes, style_vectors) = {
let model = self
.models
.iter()
.find(|m| m.ident == ident)
.ok_or(Error::ModelNotFoundError(ident.to_string()))?;
if model.vits2.is_some() {
return Ok(true);
}
(model.bytes.clone().unwrap(), model.style_vectors.clone())
};
self.unload(ident.clone());
let s = model::load_model(&bytes, false)?;
if let Some(max) = self.max_loaded_models {
let loaded_count = self.models.iter().filter(|m| m.vits2.is_some()).count();
if loaded_count >= max {
if let Some(evict_index) = self
.models
.iter()
.position(|m| m.vits2.is_some() && m.ident != ident)
{
// Drop only the session to free memory; keep bytes/style for future reload
self.models[evict_index].vits2 = None;
}
if self.models.iter().filter(|x| x.vits2.is_some()).count() >= max {
self.unload(self.models.first().unwrap().ident.clone());
}
}
// Build and set session in-place for the target model
let s = model::load_model(&bytes, false)?;
self.models[target_index].vits2 = Some(s);
Ok(true)
self.models.push(TTSModel {
bytes: Some(bytes.to_vec()),
vits2: Some(s),
style_vectors,
ident: ident.clone(),
});
let model = self
.models
.iter()
.find(|m| m.ident == ident)
.ok_or(Error::ModelNotFoundError(ident.to_string()))?;
if model.vits2.is_some() {
return Ok(true);
}
Err(Error::ModelNotFoundError(ident.to_string()))
}
/// Get style vector by style id and weight
@@ -284,7 +262,7 @@ impl TTSModelHolder {
/// # Note
/// This function is for low-level usage, use `easy_synthesize` for high-level usage.
pub fn get_style_vector<I: Into<TTSIdent>>(
&mut self,
&self,
ident: I,
style_id: i32,
weight: f32,
@@ -308,6 +286,11 @@ impl TTSModelHolder {
options: SynthesizeOptions,
) -> Result<Vec<u8>> {
self.find_and_load_model(ident)?;
let vits2 = &self
.find_model(ident)?
.vits2
.as_ref()
.ok_or(Error::ModelNotFoundError(ident.into().to_string()))?;
let style_vector = self.get_style_vector(ident, style_id, options.style_weight)?;
let audio_array = if options.split_sentences {
let texts: Vec<&str> = text.split('\n').collect();
@@ -317,12 +300,6 @@ impl TTSModelHolder {
continue;
}
let (bert_ori, phones, tones, lang_ids) = self.parse_text(t)?;
let vits2 = self
.find_model(ident)?
.vits2
.as_mut()
.ok_or(Error::ModelNotFoundError(ident.into().to_string()))?;
let audio = model::synthesize(
vits2,
bert_ori.to_owned(),
@@ -347,85 +324,6 @@ impl TTSModelHolder {
)?
} else {
let (bert_ori, phones, tones, lang_ids) = self.parse_text(text)?;
let vits2 = self
.find_model(ident)?
.vits2
.as_mut()
.ok_or(Error::ModelNotFoundError(ident.into().to_string()))?;
model::synthesize(
vits2,
bert_ori.to_owned(),
phones,
Array1::from_vec(vec![speaker_id]),
tones,
lang_ids,
style_vector,
options.sdp_ratio,
options.length_scale,
0.677,
0.8,
)?
};
tts_util::array_to_vec(audio_array)
}
pub fn easy_synthesize_neo<I: Into<TTSIdent> + Copy>(
&mut self,
ident: I,
text: &str,
given_tones: Option<Vec<i32>>,
style_id: i32,
speaker_id: i64,
options: SynthesizeOptions,
) -> Result<Vec<u8>> {
self.find_and_load_model(ident)?;
let style_vector = self.get_style_vector(ident, style_id, options.style_weight)?;
let audio_array = if options.split_sentences {
let texts: Vec<&str> = text.split('\n').collect();
let mut audios = vec![];
for (i, t) in texts.iter().enumerate() {
if t.is_empty() {
continue;
}
let (bert_ori, phones, tones, lang_ids) =
self.parse_text_neo(t.to_string(), given_tones.clone())?;
let vits2 = self
.find_model(ident)?
.vits2
.as_mut()
.ok_or(Error::ModelNotFoundError(ident.into().to_string()))?;
let audio = model::synthesize(
vits2,
bert_ori.to_owned(),
phones,
Array1::from_vec(vec![speaker_id]),
tones,
lang_ids,
style_vector.clone(),
options.sdp_ratio,
options.length_scale,
0.677,
0.8,
)?;
audios.push(audio.clone());
if i != texts.len() - 1 {
audios.push(Array3::zeros((1, 1, 22050)));
}
}
concatenate(
Axis(2),
&audios.iter().map(|x| x.view()).collect::<Vec<_>>(),
)?
} else {
let (bert_ori, phones, tones, lang_ids) = self.parse_text(text)?;
let vits2 = self
.find_model(ident)?
.vits2
.as_mut()
.ok_or(Error::ModelNotFoundError(ident.into().to_string()))?;
model::synthesize(
vits2,
bert_ori.to_owned(),

65
crates/sbv2_core/src/tts_util.rs → sbv2_core/src/tts_util.rs
View File

@@ -1,22 +1,10 @@
use std::io::Cursor;
use crate::error::Result;
use crate::jtalk::JTalkProcess;
use crate::mora::MORA_KATA_TO_MORA_PHONEMES;
use crate::norm::PUNCTUATIONS;
use crate::{jtalk, nlp, norm, tokenizer, utils};
use hound::{SampleFormat, WavSpec, WavWriter};
use ndarray::{concatenate, s, Array, Array1, Array2, Array3, Axis};
use tokenizers::Tokenizer;
pub fn preprocess_parse_text(text: &str, jtalk: &jtalk::JTalk) -> Result<(String, JTalkProcess)> {
let text = jtalk.num2word(text)?;
let normalized_text = norm::normalize_text(&text);
let process = jtalk.process_text(&normalized_text)?;
Ok((normalized_text, process))
}
/// Parse text and return the input for synthesize
///
/// # Note
@@ -33,9 +21,13 @@ pub async fn parse_text(
Box<dyn std::future::Future<Output = Result<ndarray::Array2<f32>>>>,
>,
) -> Result<(Array2<f32>, Array1<i64>, Array1<i64>, Array1<i64>)> {
let (normalized_text, process) = preprocess_parse_text(text, jtalk)?;
let text = jtalk.num2word(text)?;
let normalized_text = norm::normalize_text(&text);
let process = jtalk.process_text(&normalized_text)?;
let (phones, tones, mut word2ph) = process.g2p()?;
let (phones, tones, lang_ids) = nlp::cleaned_text_to_sequence(phones, tones);
let phones = utils::intersperse(&phones, 0);
let tones = utils::intersperse(&tones, 0);
let lang_ids = utils::intersperse(&lang_ids, 0);
@@ -100,7 +92,6 @@ pub async fn parse_text(
#[allow(clippy::type_complexity)]
pub fn parse_text_blocking(
text: &str,
given_tones: Option<Vec<i32>>,
jtalk: &jtalk::JTalk,
tokenizer: &Tokenizer,
bert_predict: impl FnOnce(Vec<i64>, Vec<i64>) -> Result<ndarray::Array2<f32>>,
@@ -109,10 +100,7 @@ pub fn parse_text_blocking(
let normalized_text = norm::normalize_text(&text);
let process = jtalk.process_text(&normalized_text)?;
let (phones, mut tones, mut word2ph) = process.g2p()?;
if let Some(given_tones) = given_tones {
tones = given_tones;
}
let (phones, tones, mut word2ph) = process.g2p()?;
let (phones, tones, lang_ids) = nlp::cleaned_text_to_sequence(phones, tones);
let phones = utils::intersperse(&phones, 0);
@@ -173,15 +161,8 @@ pub fn parse_text_blocking(
}
pub fn array_to_vec(audio_array: Array3<f32>) -> Result<Vec<u8>> {
// If SBV2_FORCE_STEREO is set ("1"/"true"), duplicate mono to stereo
let force_stereo = std::env::var("SBV2_FORCE_STEREO")
.ok()
.map(|v| matches!(v.as_str(), "1" | "true" | "TRUE" | "True"))
.unwrap_or(false);
let channels: u16 = if force_stereo { 2 } else { 1 };
let spec = WavSpec {
channels,
channels: 1,
sample_rate: 44100,
bits_per_sample: 32,
sample_format: SampleFormat::Float,
@@ -190,38 +171,10 @@ pub fn array_to_vec(audio_array: Array3<f32>) -> Result<Vec<u8>> {
let mut writer = WavWriter::new(&mut cursor, spec)?;
for i in 0..audio_array.shape()[0] {
let output = audio_array.slice(s![i, 0, ..]).to_vec();
if force_stereo {
for sample in output {
// Write to Left and Right channels
writer.write_sample(sample)?;
writer.write_sample(sample)?;
}
} else {
for sample in output {
writer.write_sample(sample)?;
}
for sample in output {
writer.write_sample(sample)?;
}
}
writer.finalize()?;
Ok(cursor.into_inner())
}
pub fn kata_tone2phone_tone(kata_tone: Vec<(String, i32)>) -> Vec<(String, i32)> {
let mut results = vec![("_".to_string(), 0)];
for (mora, tone) in kata_tone {
if PUNCTUATIONS.contains(&mora.as_str()) {
results.push((mora, 0));
continue;
} else {
let (consonant, vowel) = MORA_KATA_TO_MORA_PHONEMES.get(&mora).unwrap();
if let Some(consonant) = consonant {
results.push((consonant.to_string(), tone));
results.push((vowel.to_string(), tone));
} else {
results.push((vowel.to_string(), tone));
}
}
}
results.push(("_".to_string(), 0));
results
}

0
crates/sbv2_core/src/utils.rs → sbv2_core/src/utils.rs
View File

15
crates/sbv2_wasm/Cargo.toml → sbv2_wasm/Cargo.toml
View File

@@ -1,12 +1,7 @@
[package]
name = "sbv2_wasm"
version.workspace = true
edition.workspace = true
description.workspace = true
readme.workspace = true
repository.workspace = true
documentation.workspace = true
license.workspace = true
version = "0.1.0"
edition = "2021"
[lib]
crate-type = ["cdylib", "rlib"]
@@ -17,4 +12,8 @@ sbv2_core = { path = "../sbv2_core", default-features = false, features = ["no_s
once_cell.workspace = true
js-sys = "0.3.70"
ndarray.workspace = true
wasm-bindgen-futures = "0.4.56"
wasm-bindgen-futures = "0.4.43"
[profile.release]
lto = true
opt-level = "s"

2
sbv2_wasm/README.md Normal file
View File

@@ -0,0 +1,2 @@
# StyleBertVITS2 wasm
refer to https://github.com/tuna2134/sbv2-api

0
crates/sbv2_wasm/biome.json → sbv2_wasm/biome.json
View File

4
sbv2_wasm/build.sh Executable file
View File

@@ -0,0 +1,4 @@
wasm-pack build --target web sbv2_wasm
wasm-opt -O3 -o sbv2_wasm/pkg/sbv2_wasm_bg.wasm sbv2_wasm/pkg/sbv2_wasm_bg.wasm
mkdir -p sbv2_wasm/dist
cp sbv2_wasm/sbv2_wasm/pkg/sbv2_wasm_bg.wasm sbv2_wasm/dist/sbv2_wasm_bg.wasm

51
sbv2_wasm/example.html Normal file
View File

@@ -0,0 +1,51 @@
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Style Bert VITS2 Web</title>
<script type="importmap">
{
"imports": {
"onnxruntime-web": "https://cdn.jsdelivr.net/npm/onnxruntime-web@1.19.2/dist/ort.all.min.mjs",
"sbv2": "https://cdn.jsdelivr.net/npm/sbv2@0.1.1+esm"
}
}
</script>
<script type="module" async defer>
import { ModelHolder } from "sbv2";
await ModelHolder.globalInit(
await (
await fetch("https://esm.sh/sbv2@0.1.1/dist/sbv2_wasm_bg.wasm", { cache: "force-cache" })
).arrayBuffer(),
);
const holder = await ModelHolder.create(
await (
await fetch("/models/tokenizer.json", { cache: "force-cache" })
).text(),
await (
await fetch("/models/deberta.onnx", { cache: "force-cache" })
).arrayBuffer(),
);
if (typeof window.onready == "function") {
window.onready(holder);
}
</script>
<script type="module" async defer>
window.onready = async function (holder) {
await holder.load(
"amitaro",
await (await fetch("/models/amitaro.sbv2")).arrayBuffer(),
);
const wave = await holder.synthesize("amitaro", "おはよう");
console.log(wave);
};
</script>
</head>
<body>
<div id="root"></div>
</body>
</html>

9
crates/sbv2_wasm/example.js → sbv2_wasm/example.js
View File

@@ -3,12 +3,9 @@ import fs from "node:fs/promises";
ModelHolder.globalInit(await fs.readFile("./dist/sbv2_wasm_bg.wasm"));
const holder = await ModelHolder.create(
(await fs.readFile("../../models/tokenizer.json")).toString("utf-8"),
await fs.readFile("../../models/deberta.onnx"),
);
await holder.load(
"tsukuyomi",
await fs.readFile("../../models/tsukuyomi.sbv2"),
(await fs.readFile("../models/tokenizer.json")).toString("utf-8"),
await fs.readFile("../models/deberta.onnx"),
);
await holder.load("tsukuyomi", await fs.readFile("../models/iroha2.sbv2"));
await fs.writeFile("out.wav", await holder.synthesize("tsukuyomi", "おはよう"));
holder.unload("tsukuyomi");

15
crates/sbv2_wasm/package.json → sbv2_wasm/package.json
View File

@@ -1,6 +1,6 @@
{
"name": "sbv2",
"version": "0.2.0-alpha6",
"version": "0.1.1",
"description": "Style Bert VITS2 wasm",
"main": "dist/index.js",
"types": "dist/index.d.ts",
@@ -11,16 +11,15 @@
},
"keywords": [],
"author": "tuna2134",
"contributes": ["neodyland"],
"license": "MIT",
"devDependencies": {
"@biomejs/biome": "^1.9.4",
"@types/node": "^22.13.5",
"esbuild": "^0.25.0",
"typescript": "^5.7.3"
"@biomejs/biome": "^1.9.2",
"@types/node": "^22.7.4",
"esbuild": "^0.24.0",
"typescript": "^5.6.2"
},
"dependencies": {
"onnxruntime-web": "^1.20.1"
"onnxruntime-web": "^1.19.2"
},
"files": ["dist/*", "package.json", "README.md", "pkg/*.ts", "pkg/*.js"]
"files": ["dist/*", "package.json", "README.md"]
}

272
crates/sbv2_wasm/pnpm-lock.yaml → sbv2_wasm/pnpm-lock.yaml generated
View File

@@ -9,21 +9,21 @@ importers:
.:
dependencies:
onnxruntime-web:
specifier: ^1.20.1
version: 1.20.1
specifier: ^1.19.2
version: 1.20.0
devDependencies:
'@biomejs/biome':
specifier: ^1.9.4
specifier: ^1.9.2
version: 1.9.4
'@types/node':
specifier: ^22.13.5
version: 22.13.5
specifier: ^22.7.4
version: 22.8.0
esbuild:
specifier: ^0.25.0
version: 0.25.0
specifier: ^0.24.0
version: 0.24.0
typescript:
specifier: ^5.7.3
version: 5.8.3
specifier: ^5.6.2
version: 5.6.3
packages:
@@ -80,152 +80,146 @@ packages:
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os: [win32]
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engines: {node: '>=18'}
cpu: [ppc64]
os: [aix]
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engines: {node: '>=18'}
cpu: [arm64]
os: [android]
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engines: {node: '>=18'}
cpu: [arm]
os: [android]
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resolution: {integrity: sha512-ZUAc2YK6JW89xTbXvftxdnYy3m4iHIkDtK3CLce8wg8M2L+YZhIvO1DKpxrd0Yr59AeNNkTiic9YLf6FTtXWMw==}
'@esbuild/win32-arm64@0.24.0':
resolution: {integrity: sha512-iKc8GAslzRpBytO2/aN3d2yb2z8XTVfNV0PjGlCxKo5SgWmNXx82I/Q3aG1tFfS+A2igVCY97TJ8tnYwpUWLCA==}
engines: {node: '>=18'}
cpu: [arm64]
os: [win32]
'@esbuild/win32-ia32@0.25.0':
resolution: {integrity: sha512-eSNxISBu8XweVEWG31/JzjkIGbGIJN/TrRoiSVZwZ6pkC6VX4Im/WV2cz559/TXLcYbcrDN8JtKgd9DJVIo8GA==}
'@esbuild/win32-ia32@0.24.0':
resolution: {integrity: sha512-vQW36KZolfIudCcTnaTpmLQ24Ha1RjygBo39/aLkM2kmjkWmZGEJ5Gn9l5/7tzXA42QGIoWbICfg6KLLkIw6yw==}
engines: {node: '>=18'}
cpu: [ia32]
os: [win32]
'@esbuild/win32-x64@0.25.0':
resolution: {integrity: sha512-ZENoHJBxA20C2zFzh6AI4fT6RraMzjYw4xKWemRTRmRVtN9c5DcH9r/f2ihEkMjOW5eGgrwCslG/+Y/3bL+DHQ==}
'@esbuild/win32-x64@0.24.0':
resolution: {integrity: sha512-7IAFPrjSQIJrGsK6flwg7NFmwBoSTyF3rl7If0hNUFQU4ilTsEPL6GuMuU9BfIWVVGuRnuIidkSMC+c0Otu8IA==}
engines: {node: '>=18'}
cpu: [x64]
os: [win32]
@@ -260,11 +254,11 @@ packages:
'@protobufjs/utf8@1.1.0':
resolution: {integrity: sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw==}
'@types/node@22.13.5':
resolution: {integrity: sha512-+lTU0PxZXn0Dr1NBtC7Y8cR21AJr87dLLU953CWA6pMxxv/UDc7jYAY90upcrie1nRcD6XNG5HOYEDtgW5TxAg==}
'@types/node@22.8.0':
resolution: {integrity: sha512-84rafSBHC/z1i1E3p0cJwKA+CfYDNSXX9WSZBRopjIzLET8oNt6ht2tei4C7izwDeEiLLfdeSVBv1egOH916hg==}
esbuild@0.25.0:
resolution: {integrity: sha512-BXq5mqc8ltbaN34cDqWuYKyNhX8D/Z0J1xdtdQ8UcIIIyJyz+ZMKUt58tF3SrZ85jcfN/PZYhjR5uDQAYNVbuw==}
esbuild@0.24.0:
resolution: {integrity: sha512-FuLPevChGDshgSicjisSooU0cemp/sGXR841D5LHMB7mTVOmsEHcAxaH3irL53+8YDIeVNQEySh4DaYU/iuPqQ==}
engines: {node: '>=18'}
hasBin: true
@@ -274,14 +268,14 @@ packages:
guid-typescript@1.0.9:
resolution: {integrity: sha512-Y8T4vYhEfwJOTbouREvG+3XDsjr8E3kIr7uf+JZ0BYloFsttiHU0WfvANVsR7TxNUJa/WpCnw/Ino/p+DeBhBQ==}
long@5.3.1:
resolution: {integrity: sha512-ka87Jz3gcx/I7Hal94xaN2tZEOPoUOEVftkQqZx2EeQRN7LGdfLlI3FvZ+7WDplm+vK2Urx9ULrvSowtdCieng==}
long@5.2.3:
resolution: {integrity: sha512-lcHwpNoggQTObv5apGNCTdJrO69eHOZMi4BNC+rTLER8iHAqGrUVeLh/irVIM7zTw2bOXA8T6uNPeujwOLg/2Q==}
onnxruntime-common@1.20.1:
resolution: {integrity: sha512-YiU0s0IzYYC+gWvqD1HzLc46Du1sXpSiwzKb63PACIJr6LfL27VsXSXQvt68EzD3V0D5Bc0vyJTjmMxp0ylQiw==}
onnxruntime-common@1.20.0:
resolution: {integrity: sha512-9ehS4ul5fBszIcHhfxuDgk45lO+Fqrxmrgwk1Pxb1JRvbQiCB/v9Royv95SRCWHktLMviqNjBsEd/biJhd39cg==}
onnxruntime-web@1.20.1:
resolution: {integrity: sha512-TePF6XVpLL1rWVMIl5Y9ACBQcyCNFThZON/jgElNd9Txb73CIEGlklhYR3UEr1cp5r0rbGI6nDwwrs79g7WjoA==}
onnxruntime-web@1.20.0:
resolution: {integrity: sha512-IoUf8dqHFJLV4DUSz+Ok+xxyN6cQk57gb20m6PZE5gag3QXuvegYMq9dG8t/QF4JjTKIwvfvnr16ouzCCB9IMA==}
platform@1.3.6:
resolution: {integrity: sha512-fnWVljUchTro6RiCFvCXBbNhJc2NijN7oIQxbwsyL0buWJPG85v81ehlHI9fXrJsMNgTofEoWIQeClKpgxFLrg==}
@@ -290,13 +284,13 @@ packages:
resolution: {integrity: sha512-mRUWCc3KUU4w1jU8sGxICXH/gNS94DvI1gxqDvBzhj1JpcsimQkYiOJfwsPUykUI5ZaspFbSgmBLER8IrQ3tqw==}
engines: {node: '>=12.0.0'}
typescript@5.8.3:
resolution: {integrity: sha512-p1diW6TqL9L07nNxvRMM7hMMw4c5XOo/1ibL4aAIGmSAt9slTE1Xgw5KWuof2uTOvCg9BY7ZRi+GaF+7sfgPeQ==}
typescript@5.6.3:
resolution: {integrity: sha512-hjcS1mhfuyi4WW8IWtjP7brDrG2cuDZukyrYrSauoXGNgx0S7zceP07adYkJycEr56BOUTNPzbInooiN3fn1qw==}
engines: {node: '>=14.17'}
hasBin: true
undici-types@6.20.0:
resolution: {integrity: sha512-Ny6QZ2Nju20vw1SRHe3d9jVu6gJ+4e3+MMpqu7pqE5HT6WsTSlce++GQmK5UXS8mzV8DSYHrQH+Xrf2jVcuKNg==}
undici-types@6.19.8:
resolution: {integrity: sha512-ve2KP6f/JnbPBFyobGHuerC9g1FYGn/F8n1LWTwNxCEzd6IfqTwUQcNXgEtmmQ6DlRrC1hrSrBnCZPokRrDHjw==}
snapshots:
@@ -335,79 +329,76 @@ snapshots:
'@biomejs/cli-win32-x64@1.9.4':
optional: true
'@esbuild/aix-ppc64@0.25.0':
'@esbuild/aix-ppc64@0.24.0':
optional: true
'@esbuild/android-arm64@0.25.0':
'@esbuild/android-arm64@0.24.0':
optional: true
'@esbuild/android-arm@0.25.0':
'@esbuild/android-arm@0.24.0':
optional: true
'@esbuild/android-x64@0.25.0':
'@esbuild/android-x64@0.24.0':
optional: true
'@esbuild/darwin-arm64@0.25.0':
'@esbuild/darwin-arm64@0.24.0':
optional: true
'@esbuild/darwin-x64@0.25.0':
'@esbuild/darwin-x64@0.24.0':
optional: true
'@esbuild/freebsd-arm64@0.25.0':
'@esbuild/freebsd-arm64@0.24.0':
optional: true
'@esbuild/freebsd-x64@0.25.0':
'@esbuild/freebsd-x64@0.24.0':
optional: true
'@esbuild/linux-arm64@0.25.0':
'@esbuild/linux-arm64@0.24.0':
optional: true
'@esbuild/linux-arm@0.25.0':
'@esbuild/linux-arm@0.24.0':
optional: true
'@esbuild/linux-ia32@0.25.0':
'@esbuild/linux-ia32@0.24.0':
optional: true
'@esbuild/linux-loong64@0.25.0':
'@esbuild/linux-loong64@0.24.0':
optional: true
'@esbuild/linux-mips64el@0.25.0':
'@esbuild/linux-mips64el@0.24.0':
optional: true
'@esbuild/linux-ppc64@0.25.0':
'@esbuild/linux-ppc64@0.24.0':
optional: true
'@esbuild/linux-riscv64@0.25.0':
'@esbuild/linux-riscv64@0.24.0':
optional: true
'@esbuild/linux-s390x@0.25.0':
'@esbuild/linux-s390x@0.24.0':
optional: true
'@esbuild/linux-x64@0.25.0':
'@esbuild/linux-x64@0.24.0':
optional: true
'@esbuild/netbsd-arm64@0.25.0':
'@esbuild/netbsd-x64@0.24.0':
optional: true
'@esbuild/netbsd-x64@0.25.0':
'@esbuild/openbsd-arm64@0.24.0':
optional: true
'@esbuild/openbsd-arm64@0.25.0':
'@esbuild/openbsd-x64@0.24.0':
optional: true
'@esbuild/openbsd-x64@0.25.0':
'@esbuild/sunos-x64@0.24.0':
optional: true
'@esbuild/sunos-x64@0.25.0':
'@esbuild/win32-arm64@0.24.0':
optional: true
'@esbuild/win32-arm64@0.25.0':
'@esbuild/win32-ia32@0.24.0':
optional: true
'@esbuild/win32-ia32@0.25.0':
optional: true
'@esbuild/win32-x64@0.25.0':
'@esbuild/win32-x64@0.24.0':
optional: true
'@protobufjs/aspromise@1.1.2': {}
@@ -433,52 +424,51 @@ snapshots:
'@protobufjs/utf8@1.1.0': {}
'@types/node@22.13.5':
'@types/node@22.8.0':
dependencies:
undici-types: 6.20.0
undici-types: 6.19.8
esbuild@0.25.0:
esbuild@0.24.0:
optionalDependencies:
'@esbuild/aix-ppc64': 0.25.0
'@esbuild/android-arm': 0.25.0
'@esbuild/android-arm64': 0.25.0
'@esbuild/android-x64': 0.25.0
'@esbuild/darwin-arm64': 0.25.0
'@esbuild/darwin-x64': 0.25.0
'@esbuild/freebsd-arm64': 0.25.0
'@esbuild/freebsd-x64': 0.25.0
'@esbuild/linux-arm': 0.25.0
'@esbuild/linux-arm64': 0.25.0
'@esbuild/linux-ia32': 0.25.0
'@esbuild/linux-loong64': 0.25.0
'@esbuild/linux-mips64el': 0.25.0
'@esbuild/linux-ppc64': 0.25.0
'@esbuild/linux-riscv64': 0.25.0
'@esbuild/linux-s390x': 0.25.0
'@esbuild/linux-x64': 0.25.0
'@esbuild/netbsd-arm64': 0.25.0
'@esbuild/netbsd-x64': 0.25.0
'@esbuild/openbsd-arm64': 0.25.0
'@esbuild/openbsd-x64': 0.25.0
'@esbuild/sunos-x64': 0.25.0
'@esbuild/win32-arm64': 0.25.0
'@esbuild/win32-ia32': 0.25.0
'@esbuild/win32-x64': 0.25.0
'@esbuild/aix-ppc64': 0.24.0
'@esbuild/android-arm': 0.24.0
'@esbuild/android-arm64': 0.24.0
'@esbuild/android-x64': 0.24.0
'@esbuild/darwin-arm64': 0.24.0
'@esbuild/darwin-x64': 0.24.0
'@esbuild/freebsd-arm64': 0.24.0
'@esbuild/freebsd-x64': 0.24.0
'@esbuild/linux-arm': 0.24.0
'@esbuild/linux-arm64': 0.24.0
'@esbuild/linux-ia32': 0.24.0
'@esbuild/linux-loong64': 0.24.0
'@esbuild/linux-mips64el': 0.24.0
'@esbuild/linux-ppc64': 0.24.0
'@esbuild/linux-riscv64': 0.24.0
'@esbuild/linux-s390x': 0.24.0
'@esbuild/linux-x64': 0.24.0
'@esbuild/netbsd-x64': 0.24.0
'@esbuild/openbsd-arm64': 0.24.0
'@esbuild/openbsd-x64': 0.24.0
'@esbuild/sunos-x64': 0.24.0
'@esbuild/win32-arm64': 0.24.0
'@esbuild/win32-ia32': 0.24.0
'@esbuild/win32-x64': 0.24.0
flatbuffers@1.12.0: {}
guid-typescript@1.0.9: {}
long@5.3.1: {}
long@5.2.3: {}
onnxruntime-common@1.20.1: {}
onnxruntime-common@1.20.0: {}
onnxruntime-web@1.20.1:
onnxruntime-web@1.20.0:
dependencies:
flatbuffers: 1.12.0
guid-typescript: 1.0.9
long: 5.3.1
onnxruntime-common: 1.20.1
long: 5.2.3
onnxruntime-common: 1.20.0
platform: 1.3.6
protobufjs: 7.4.0
@@ -496,9 +486,9 @@ snapshots:
'@protobufjs/path': 1.1.2
'@protobufjs/pool': 1.1.0
'@protobufjs/utf8': 1.1.0
'@types/node': 22.13.5
long: 5.3.1
'@types/node': 22.8.0
long: 5.2.3
typescript@5.8.3: {}
typescript@5.6.3: {}
undici-types@6.20.0: {}
undici-types@6.19.8: {}

2
crates/sbv2_wasm/src-js/index.ts → sbv2_wasm/src-js/index.ts
View File

@@ -74,8 +74,6 @@ export class ModelHolder {
style_vec: e,
sdp_ratio: new Tensor("float32", [f]),
length_scale: new Tensor("float32", [g]),
noise_scale: new Tensor("float32", [0.677]),
noise_scale_w: new Tensor("float32", [0.8]),
})
).output;
return [new Uint32Array(res.dims), await res.getData(true)];

0
crates/sbv2_wasm/src/array_helper.rs → sbv2_wasm/src/array_helper.rs
View File

0
crates/sbv2_wasm/src/lib.rs → sbv2_wasm/src/lib.rs
View File

0
crates/sbv2_wasm/tsconfig.json → sbv2_wasm/tsconfig.json
View File

5
scripts/.gitignore vendored
View File

@@ -1,5 +0,0 @@
*.json
venv/
tmp/
*.safetensors
*.npy

1
scripts/convert/.python-version
View File

@@ -1 +0,0 @@
3.11

6
scripts/convert/requirements.txt
View File

@@ -1,6 +0,0 @@
git+https://github.com/neodyland/style-bert-vits2-ref
onnxsim
numpy<2
zstandard
onnxruntime
cmake<4

17
scripts/docker/cpu.Dockerfile
View File

@@ -1,17 +0,0 @@
FROM rust AS builder
WORKDIR /work
COPY . .
RUN cargo build -r --bin sbv2_api
FROM ubuntu AS upx
WORKDIR /work
RUN apt update && apt-get install -y upx binutils
COPY --from=builder /work/target/release/sbv2_api /work/main
COPY --from=builder /work/target/release/*.so /work
RUN upx --best --lzma /work/main
RUN find /work -maxdepth 1 -name "*.so" -exec strip --strip-unneeded {} +
RUN find /work -maxdepth 1 -name "*.so" -exec upx --best --lzma {} +
FROM gcr.io/distroless/cc-debian12
WORKDIR /work
COPY --from=upx /work/main /work/main
COPY --from=upx /work/*.so /work
CMD ["/work/main"]

14
scripts/make_dict.sh
View File

@@ -1,14 +0,0 @@
#!/bin/bash
set -e
git clone https://github.com/Aivis-Project/AivisSpeech-Engine ./scripts/tmp --filter=blob:none -n
cd ./scripts/tmp
git checkout 168b2a1144afe300b0490d9a6dd773ec6e927667 -- resources/dictionaries/*.csv
cd ../..
rm -rf ./crates/sbv2_core/src/dic
cp -r ./scripts/tmp/resources/dictionaries ./crates/sbv2_core/src/dic
rm -rf ./scripts/tmp
for file in ./crates/sbv2_core/src/dic/0*.csv; do
/usr/bin/cat "$file"
echo
done > ./crates/sbv2_core/src/all.csv
lindera build ./crates/sbv2_core/src/all.csv ./crates/sbv2_core/src/dic/all.dic -u -k ipadic

8
scripts/sbv2-test-api.py
View File

@@ -1,8 +0,0 @@
import requests
res = requests.post(
"http://localhost:3000/synthesize",
json={"text": "おはようございます", "ident": "tsukuyomi"},
)
with open("output.wav", "wb") as f:
f.write(res.content)

23
test.py
View File

@@ -1,19 +1,8 @@
import requests
data = (requests.get("http://localhost:8080/audio_query", params={
"text": "こんにちは、今日はいい天気ですね。",
})).json()
print(data)
data = (requests.post("http://localhost:8080/synthesis", json={
"text": data["text"],
"ident": "tsukuyomi",
"speaker_id": 0,
"style_id": 0,
"sdp_ratio": 0.5,
"length_scale": 0.5,
"audio_query": data["audio_query"],
})).content
with open("test.wav", "wb") as f:
f.write(data)
res = requests.post(
"http://localhost:3000/synthesize",
json={"text": "おはようございます", "ident": "tsukuyomi"},
)
with open("output.wav", "wb") as f:
f.write(res.content)