mirror of
https://github.com/neodyland/sbv2-api.git
synced 2025-12-25 08:39:57 +00:00
Compare commits
2 Commits
v0.2.0-rc.
...
mecab
| Author | SHA1 | Date | |
|---|---|---|---|
|
4744f02792 | ||
|
|
5de9514546 |
3
.github/FUNDING.yml
vendored
3
.github/FUNDING.yml
vendored
@@ -1,3 +0,0 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
github: [tuna2134]
|
||||
92
.github/workflows/CI.yml
vendored
92
.github/workflows/CI.yml
vendored
@@ -18,10 +18,6 @@ on:
|
||||
permissions:
|
||||
contents: read
|
||||
id-token: write
|
||||
packages: write
|
||||
|
||||
env:
|
||||
GHCR_REPO: ghcr.io/tuna2134/sbv2-api
|
||||
|
||||
jobs:
|
||||
linux:
|
||||
@@ -83,6 +79,8 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
platform:
|
||||
- runner: macos-12
|
||||
target: x86_64
|
||||
- runner: macos-14
|
||||
target: aarch64
|
||||
steps:
|
||||
@@ -133,80 +131,36 @@ jobs:
|
||||
command: upload
|
||||
args: --non-interactive --skip-existing wheels-*/*
|
||||
|
||||
build:
|
||||
runs-on: ${{ matrix.machine.runner }}
|
||||
push-docker:
|
||||
runs-on: ubuntu-latest
|
||||
if: "startsWith(github.ref, 'refs/tags/')"
|
||||
permissions:
|
||||
contents: read
|
||||
packages: write
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
machine:
|
||||
- platform: amd64
|
||||
runner: ubuntu-latest
|
||||
- platform: arm64
|
||||
runner: ubuntu-24.04-arm64
|
||||
tag: [cpu, cuda]
|
||||
platform:
|
||||
- linux/amd64
|
||||
- linux/arm64
|
||||
steps:
|
||||
- name: Prepare
|
||||
run: |
|
||||
platform=${{ matrix.machine.platform }}
|
||||
echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
|
||||
|
||||
- name: Docker meta
|
||||
id: meta
|
||||
uses: docker/metadata-action@v5
|
||||
with:
|
||||
images: |
|
||||
${{ env.GHCR_REPO }}
|
||||
|
||||
- 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: ${{ steps.meta.outputs.labels }}
|
||||
file: docker/${{ matrix.tag }}.Dockerfile
|
||||
push: true
|
||||
tags: |
|
||||
${{ env.GHCR_REPO }}:latest-${{ matrix.tag }}-${{ matrix.machine.platform }}
|
||||
|
||||
merge:
|
||||
runs-on: ubuntu-latest
|
||||
needs:
|
||||
- build
|
||||
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 ${{ env.GHCR_REPO }}:cuda \
|
||||
${{ env.GHCR_REPO }}:latest-cuda-amd64 \
|
||||
${{ env.GHCR_REPO }}:latest-cuda-arm64
|
||||
docker buildx imagetools create -t ${{ env.GHCR_REPO }}:cpu \
|
||||
${{ env.GHCR_REPO }}:latest-cpu-amd64 \
|
||||
${{ env.GHCR_REPO }}:latest-cpu-arm64
|
||||
- name: Build and push image
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
tags: |
|
||||
ghcr.io/${{ github.repository }}:${{ matrix.tag }}
|
||||
file: docker/${{ matrix.tag }}.Dockerfile
|
||||
platforms: ${{ matrix.platform }}
|
||||
|
||||
843
Cargo.lock
generated
843
Cargo.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -1,180 +0,0 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# 音声合成プログラム\n",
|
||||
"\n",
|
||||
"このノートブックでは、`sbv2_bindings` パッケージを使用して音声合成を行います。必要なモデルをダウンロードし、ユーザーが入力したテキストから音声を生成します。音声合成が終わったら、再度テキストの入力を求め、ユーザーが終了するまで繰り返します。"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# 必要なパッケージのインストール\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",
|
||||
"import urllib.request\n",
|
||||
"import time\n",
|
||||
"from sbv2_bindings import TTSModel"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## モデルのダウンロード\n",
|
||||
"\n",
|
||||
"モデルファイルとトークナイザーをダウンロードします。ユーザーが独自のモデルを使用したい場合は、該当するURLまたはローカルパスを指定してください。"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# モデルの URL またはローカルパスの指定\n",
|
||||
"user_sbv2_model_url = \"\" # カスタムモデルのURLがあればここに指定\n",
|
||||
"user_sbv2_model_path = \"\" # カスタムモデルのローカルパスがあればここに指定\n",
|
||||
"\n",
|
||||
"# モデル用のディレクトリを作成\n",
|
||||
"model_dir = 'models'\n",
|
||||
"os.makedirs(model_dir, exist_ok=True)\n",
|
||||
"\n",
|
||||
"# ダウンロードするファイルの URL\n",
|
||||
"file_urls = [\n",
|
||||
" \"https://huggingface.co/googlefan/sbv2_onnx_models/resolve/main/tokenizer.json\",\n",
|
||||
" \"https://huggingface.co/googlefan/sbv2_onnx_models/resolve/main/deberta.onnx\",\n",
|
||||
"]\n",
|
||||
"\n",
|
||||
"# モデルのパス決定\n",
|
||||
"if user_sbv2_model_path:\n",
|
||||
" sbv2_model_path = user_sbv2_model_path # ローカルモデルのパスを使用\n",
|
||||
"elif user_sbv2_model_url:\n",
|
||||
" sbv2_model_filename = os.path.basename(user_sbv2_model_url)\n",
|
||||
" sbv2_model_path = os.path.join(model_dir, sbv2_model_filename)\n",
|
||||
" file_urls.append(user_sbv2_model_url)\n",
|
||||
"else:\n",
|
||||
" # デフォルトのモデルを使用\n",
|
||||
" sbv2_model_filename = \"tsukuyomi.sbv2\"\n",
|
||||
" sbv2_model_path = os.path.join(model_dir, sbv2_model_filename)\n",
|
||||
" file_urls.append(\"https://huggingface.co/googlefan/sbv2_onnx_models/resolve/main/tsukuyomi.sbv2\")\n",
|
||||
"\n",
|
||||
"# ファイルをダウンロード\n",
|
||||
"for url in file_urls:\n",
|
||||
" file_name = os.path.join(model_dir, os.path.basename(url))\n",
|
||||
" if not os.path.exists(file_name):\n",
|
||||
" print(f\"{file_name} をダウンロードしています...\")\n",
|
||||
" urllib.request.urlretrieve(url, file_name)\n",
|
||||
" else:\n",
|
||||
" print(f\"{file_name} は既に存在します。\")\n",
|
||||
"\n",
|
||||
"# ダウンロードまたは使用するファイルを確認\n",
|
||||
"print(\"\\n使用するファイル:\")\n",
|
||||
"for file in os.listdir(model_dir):\n",
|
||||
" print(file)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## モデルの読み込みと音声合成\n",
|
||||
"\n",
|
||||
"モデルを読み込み、ユーザーが入力したテキストから音声を生成します。話者名は使用する `.sbv2` ファイル名から自動的に取得します。音声合成が終わったら、再度テキストの入力を求め、ユーザーが終了するまで繰り返します。"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# 音声合成の実行\n",
|
||||
"def main():\n",
|
||||
" try:\n",
|
||||
" print(\"\\nモデルを読み込んでいます...\")\n",
|
||||
" model = TTSModel.from_path(\n",
|
||||
" os.path.join(model_dir, \"deberta.onnx\"),\n",
|
||||
" os.path.join(model_dir, \"tokenizer.json\")\n",
|
||||
" )\n",
|
||||
" print(\"モデルの読み込みが完了しました！\")\n",
|
||||
" except Exception as e:\n",
|
||||
" print(f\"モデルの読み込みに失敗しました: {e}\")\n",
|
||||
" return\n",
|
||||
"\n",
|
||||
" # 話者名を取得（.sbv2 ファイル名の拡張子を除いた部分）\n",
|
||||
" speaker_name = os.path.splitext(os.path.basename(sbv2_model_path))[0]\n",
|
||||
" \n",
|
||||
" # 指定されたモデルのパスを使用\n",
|
||||
" try:\n",
|
||||
" model.load_sbv2file_from_path(speaker_name, sbv2_model_path)\n",
|
||||
" print(f\"話者 '{speaker_name}' のセットアップが完了しました！\")\n",
|
||||
" except Exception as e:\n",
|
||||
" print(f\"SBV2ファイルの読み込みに失敗しました: {e}\")\n",
|
||||
" return\n",
|
||||
"\n",
|
||||
" # 音声合成を繰り返し実行\n",
|
||||
" while True:\n",
|
||||
" # 合成したいテキストをユーザーから入力\n",
|
||||
" user_input = input(\"\\n音声合成したいテキストを入力してください（終了するには 'exit' と入力）: \")\n",
|
||||
" \n",
|
||||
" if user_input.strip().lower() == 'exit':\n",
|
||||
" print(\"音声合成を終了します。\")\n",
|
||||
" break\n",
|
||||
"\n",
|
||||
" # 出力ファイル名\n",
|
||||
" output_file = \"output.wav\"\n",
|
||||
"\n",
|
||||
" # 音声合成を実行\n",
|
||||
" try:\n",
|
||||
" print(\"\\n音声合成を開始します...\")\n",
|
||||
" start_time = time.time()\n",
|
||||
"\n",
|
||||
" audio_data = model.synthesize(user_input, speaker_name, 0, 0.0, 1)\n",
|
||||
"\n",
|
||||
" with open(output_file, \"wb\") as f:\n",
|
||||
" f.write(audio_data)\n",
|
||||
"\n",
|
||||
" end_time = time.time()\n",
|
||||
" elapsed_time = end_time - start_time\n",
|
||||
"\n",
|
||||
" print(f\"\\n音声が '{output_file}' に保存されました。\")\n",
|
||||
" print(f\"音声合成にかかった時間: {elapsed_time:.2f} 秒\")\n",
|
||||
" except Exception as e:\n",
|
||||
" print(f\"音声合成に失敗しました: {e}\")\n",
|
||||
"\n",
|
||||
"if __name__ == \"__main__\":\n",
|
||||
" main()"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.x"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 4
|
||||
}
|
||||
@@ -94,7 +94,7 @@ model = get_net_g(
|
||||
)
|
||||
|
||||
|
||||
def forward(x, x_len, sid, tone, lang, bert, style, length_scale, sdp_ratio, noise_scale, noise_scale_w):
|
||||
def forward(x, x_len, sid, tone, lang, bert, style, length_scale, sdp_ratio):
|
||||
return model.infer(
|
||||
x,
|
||||
x_len,
|
||||
@@ -105,8 +105,6 @@ def forward(x, x_len, sid, tone, lang, bert, style, length_scale, sdp_ratio, noi
|
||||
style,
|
||||
sdp_ratio=sdp_ratio,
|
||||
length_scale=length_scale,
|
||||
noise_scale=noise_scale,
|
||||
noise_scale_w=noise_scale_w,
|
||||
)
|
||||
|
||||
|
||||
@@ -124,8 +122,6 @@ torch.onnx.export(
|
||||
style_vec_tensor,
|
||||
torch.tensor(1.0),
|
||||
torch.tensor(0.0),
|
||||
torch.tensor(0.6777),
|
||||
torch.tensor(0.8),
|
||||
),
|
||||
f"../models/model_{out_name}.onnx",
|
||||
verbose=True,
|
||||
@@ -148,8 +144,6 @@ torch.onnx.export(
|
||||
"style_vec",
|
||||
"length_scale",
|
||||
"sdp_ratio",
|
||||
"noise_scale",
|
||||
"noise_scale_w"
|
||||
],
|
||||
output_names=["output"],
|
||||
)
|
||||
|
||||
@@ -1,19 +1,19 @@
|
||||
[package]
|
||||
name = "sbv2_api"
|
||||
version = "0.2.0-alpha4"
|
||||
version = "0.2.0-alpha"
|
||||
edition = "2021"
|
||||
|
||||
[dependencies]
|
||||
anyhow.workspace = true
|
||||
axum = "0.8.0"
|
||||
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"] }
|
||||
sbv2_core = { version = "0.2.0-alpha", path = "../sbv2_core" }
|
||||
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 = "0.3.0", features = ["axum"] }
|
||||
utoipa = { version = "4.2.3", features = ["axum_extras"] }
|
||||
utoipa-scalar = { version = "0.1.0", features = ["axum"] }
|
||||
|
||||
[features]
|
||||
coreml = ["sbv2_core/coreml"]
|
||||
|
||||
@@ -40,14 +40,6 @@ fn length_default() -> f32 {
|
||||
1.0
|
||||
}
|
||||
|
||||
fn style_id_default() -> i32 {
|
||||
0
|
||||
}
|
||||
|
||||
fn speaker_id_default() -> i64 {
|
||||
0
|
||||
}
|
||||
|
||||
#[derive(Deserialize, ToSchema)]
|
||||
struct SynthesizeRequest {
|
||||
text: String,
|
||||
@@ -56,10 +48,6 @@ struct SynthesizeRequest {
|
||||
sdp_ratio: f32,
|
||||
#[serde(default = "length_default")]
|
||||
length_scale: f32,
|
||||
#[serde(default = "style_id_default")]
|
||||
style_id: i32,
|
||||
#[serde(default = "speaker_id_default")]
|
||||
speaker_id: i64,
|
||||
}
|
||||
|
||||
#[utoipa::path(
|
||||
@@ -77,18 +65,15 @@ async fn synthesize(
|
||||
ident,
|
||||
sdp_ratio,
|
||||
length_scale,
|
||||
style_id,
|
||||
speaker_id,
|
||||
}): Json<SynthesizeRequest>,
|
||||
) -> AppResult<impl IntoResponse> {
|
||||
log::debug!("processing request: text={text}, ident={ident}, sdp_ratio={sdp_ratio}, length_scale={length_scale}");
|
||||
let buffer = {
|
||||
let mut tts_model = state.tts_model.lock().await;
|
||||
let tts_model = state.tts_model.lock().await;
|
||||
tts_model.easy_synthesize(
|
||||
&ident,
|
||||
&text,
|
||||
style_id,
|
||||
speaker_id,
|
||||
0,
|
||||
SynthesizeOptions {
|
||||
sdp_ratio,
|
||||
length_scale,
|
||||
@@ -109,9 +94,6 @@ impl AppState {
|
||||
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?;
|
||||
@@ -140,20 +122,6 @@ impl AppState {
|
||||
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 {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "sbv2_bindings"
|
||||
version = "0.2.0-alpha4"
|
||||
version = "0.2.0-alpha1"
|
||||
edition = "2021"
|
||||
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
@@ -11,5 +11,5 @@ crate-type = ["cdylib"]
|
||||
[dependencies]
|
||||
anyhow.workspace = true
|
||||
ndarray.workspace = true
|
||||
pyo3 = { version = "0.23.0", features = ["anyhow"] }
|
||||
sbv2_core = { version = "0.2.0-alpha2", path = "../sbv2_core" }
|
||||
pyo3 = { version = "0.22.0", features = ["anyhow"] }
|
||||
sbv2_core = { version = "0.2.0-alpha", path = "../sbv2_core" }
|
||||
|
||||
@@ -23,15 +23,10 @@ pub struct TTSModel {
|
||||
|
||||
#[pymethods]
|
||||
impl TTSModel {
|
||||
#[pyo3(signature = (bert_model_bytes, tokenizer_bytes, max_loaded_models=None))]
|
||||
#[new]
|
||||
fn new(
|
||||
bert_model_bytes: Vec<u8>,
|
||||
tokenizer_bytes: Vec<u8>,
|
||||
max_loaded_models: Option<usize>,
|
||||
) -> anyhow::Result<Self> {
|
||||
fn new(bert_model_bytes: Vec<u8>, tokenizer_bytes: Vec<u8>) -> anyhow::Result<Self> {
|
||||
Ok(Self {
|
||||
model: TTSModelHolder::new(bert_model_bytes, tokenizer_bytes, max_loaded_models)?,
|
||||
model: TTSModelHolder::new(bert_model_bytes, tokenizer_bytes)?,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -43,21 +38,10 @@ impl TTSModel {
|
||||
/// BERTモデルのパス
|
||||
/// tokenizer_path : str
|
||||
/// トークナイザーのパス
|
||||
/// max_loaded_models: int | None
|
||||
/// 同時にVRAMに存在するモデルの数
|
||||
#[pyo3(signature = (bert_model_path, tokenizer_path, max_loaded_models=None))]
|
||||
#[staticmethod]
|
||||
fn from_path(
|
||||
bert_model_path: String,
|
||||
tokenizer_path: String,
|
||||
max_loaded_models: Option<usize>,
|
||||
) -> anyhow::Result<Self> {
|
||||
fn from_path(bert_model_path: String, tokenizer_path: String) -> anyhow::Result<Self> {
|
||||
Ok(Self {
|
||||
model: TTSModelHolder::new(
|
||||
fs::read(bert_model_path)?,
|
||||
fs::read(tokenizer_path)?,
|
||||
max_loaded_models,
|
||||
)?,
|
||||
model: TTSModelHolder::new(fs::read(bert_model_path)?, fs::read(tokenizer_path)?)?,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -137,12 +121,11 @@ impl TTSModel {
|
||||
/// voice_data : bytes
|
||||
/// 音声データ
|
||||
fn synthesize<'p>(
|
||||
&'p mut self,
|
||||
&'p self,
|
||||
py: Python<'p>,
|
||||
text: String,
|
||||
ident: String,
|
||||
style_id: i32,
|
||||
speaker_id: i64,
|
||||
sdp_ratio: f32,
|
||||
length_scale: f32,
|
||||
) -> anyhow::Result<Bound<PyBytes>> {
|
||||
@@ -150,14 +133,13 @@ impl TTSModel {
|
||||
ident.as_str(),
|
||||
&text,
|
||||
style_id,
|
||||
speaker_id,
|
||||
SynthesizeOptions {
|
||||
sdp_ratio,
|
||||
length_scale,
|
||||
..Default::default()
|
||||
},
|
||||
)?;
|
||||
Ok(PyBytes::new(py, &data))
|
||||
Ok(PyBytes::new_bound(py, &data))
|
||||
}
|
||||
|
||||
fn unload(&mut self, ident: String) -> bool {
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "sbv2_core"
|
||||
description = "Style-Bert-VITSの推論ライブラリ"
|
||||
version = "0.2.0-alpha4"
|
||||
version = "0.2.0-alpha1"
|
||||
edition = "2021"
|
||||
license = "MIT"
|
||||
readme = "../README.md"
|
||||
@@ -10,22 +10,21 @@ documentation = "https://docs.rs/sbv2_core"
|
||||
|
||||
[dependencies]
|
||||
anyhow.workspace = true
|
||||
base64 = { version = "0.22.1", optional = true }
|
||||
dotenvy.workspace = true
|
||||
env_logger.workspace = true
|
||||
hound = "3.5.1"
|
||||
jpreprocess = { version = "0.10.0", features = ["naist-jdic"] }
|
||||
ndarray.workspace = true
|
||||
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.8", optional = true }
|
||||
ort = { git = "https://github.com/pykeio/ort.git", version = "2.0.0-rc.6", optional = true }
|
||||
regex = "1.10.6"
|
||||
serde = { version = "1.0.210", features = ["derive"] }
|
||||
serde_json = "1.0.128"
|
||||
tar = "0.4.41"
|
||||
thiserror = "1.0.63"
|
||||
tokenizers = { version = "0.21.0", default-features = false }
|
||||
tokenizers = { version = "0.20.0", default-features = false }
|
||||
vibrato = { version = "0.5.1", optional = true }
|
||||
zstd = "0.13.2"
|
||||
|
||||
[features]
|
||||
@@ -38,5 +37,4 @@ tensorrt = ["ort/tensorrt", "std"]
|
||||
coreml = ["ort/coreml", "std"]
|
||||
default = ["std"]
|
||||
no_std = ["tokenizers/unstable_wasm"]
|
||||
aivmx = ["npyz", "base64"]
|
||||
base64 = ["dep:base64"]
|
||||
mecab = ["vibrato"]
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
use crate::error::Result;
|
||||
use ndarray::{Array2, Ix2};
|
||||
use ndarray::Array2;
|
||||
use ort::Session;
|
||||
|
||||
pub fn predict(
|
||||
@@ -14,10 +14,10 @@ pub fn predict(
|
||||
}?
|
||||
)?;
|
||||
|
||||
let output = outputs["output"]
|
||||
.try_extract_tensor::<f32>()?
|
||||
.into_dimensionality::<Ix2>()?
|
||||
.to_owned();
|
||||
let output = outputs.get("output").unwrap();
|
||||
|
||||
Ok(output)
|
||||
let content = output.try_extract_tensor::<f32>()?.to_owned();
|
||||
let (data, _) = content.clone().into_raw_vec_and_offset();
|
||||
|
||||
Ok(Array2::from_shape_vec((content.shape()[0], content.shape()[1]), data).unwrap())
|
||||
}
|
||||
|
||||
@@ -21,9 +21,6 @@ pub enum Error {
|
||||
HoundError(#[from] hound::Error),
|
||||
#[error("model not found error")]
|
||||
ModelNotFoundError(String),
|
||||
#[cfg(feature = "base64")]
|
||||
#[error("base64 error")]
|
||||
Base64Error(#[from] base64::DecodeError),
|
||||
#[error("other")]
|
||||
OtherError(String),
|
||||
}
|
||||
|
||||
@@ -14,3 +14,6 @@ pub mod tokenizer;
|
||||
pub mod tts;
|
||||
pub mod tts_util;
|
||||
pub mod utils;
|
||||
|
||||
#[cfg(feature = "mecab")]
|
||||
pub mod mecab;
|
||||
@@ -11,26 +11,14 @@ fn main_inner() -> anyhow::Result<()> {
|
||||
let mut tts_holder = tts::TTSModelHolder::new(
|
||||
&fs::read(env::var("BERT_MODEL_PATH")?)?,
|
||||
&fs::read(env::var("TOKENIZER_PATH")?)?,
|
||||
env::var("HOLDER_MAX_LOADED_MODElS")
|
||||
.ok()
|
||||
.and_then(|x| x.parse().ok()),
|
||||
)?;
|
||||
#[cfg(not(feature = "aivmx"))]
|
||||
{
|
||||
tts_holder.load_sbv2file(ident, fs::read(env::var("MODEL_PATH")?)?)?;
|
||||
}
|
||||
#[cfg(feature = "aivmx")]
|
||||
{
|
||||
tts_holder.load_aivmx(ident, fs::read(env::var("MODEL_PATH")?)?)?;
|
||||
}
|
||||
tts_holder.load_sbv2file(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, tts::SynthesizeOptions::default())?;
|
||||
fs::write("output.wav", audio)?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[cfg(not(feature = "std"))]
|
||||
fn main_inner() -> anyhow::Result<()> {
|
||||
Ok(())
|
||||
|
||||
0
sbv2_core/src/mecab.rs
Normal file
0
sbv2_core/src/mecab.rs
Normal file
@@ -1,5 +1,5 @@
|
||||
use crate::error::Result;
|
||||
use ndarray::{array, Array1, Array2, Array3, Axis, Ix3};
|
||||
use ndarray::{array, Array1, Array2, Array3, Axis};
|
||||
use ort::{GraphOptimizationLevel, Session};
|
||||
|
||||
#[allow(clippy::vec_init_then_push, unused_variables)]
|
||||
@@ -52,14 +52,11 @@ 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];
|
||||
@@ -70,21 +67,27 @@ pub fn synthesize(
|
||||
let outputs = session.run(ort::inputs! {
|
||||
"x_tst" => x_tst,
|
||||
"x_tst_lengths" => x_tst_lengths,
|
||||
"sid" => sid,
|
||||
"sid" => array![0_i64],
|
||||
"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"]
|
||||
let audio_array = outputs
|
||||
.get("output")
|
||||
.unwrap()
|
||||
.try_extract_tensor::<f32>()?
|
||||
.into_dimensionality::<Ix3>()?
|
||||
.to_owned();
|
||||
|
||||
Ok(audio_array)
|
||||
Ok(Array3::from_shape_vec(
|
||||
(
|
||||
audio_array.shape()[0],
|
||||
audio_array.shape()[1],
|
||||
audio_array.shape()[2],
|
||||
),
|
||||
audio_array.into_raw_vec_and_offset().0,
|
||||
)?)
|
||||
}
|
||||
|
||||
@@ -1,13 +1,7 @@
|
||||
use crate::error::{Error, Result};
|
||||
use crate::{jtalk, model, style, tokenizer, tts_util};
|
||||
#[cfg(feature = "aivmx")]
|
||||
use base64::prelude::{Engine as _, BASE64_STANDARD};
|
||||
#[cfg(feature = "aivmx")]
|
||||
use ndarray::ShapeBuilder;
|
||||
use ndarray::{concatenate, Array1, Array2, Array3, Axis};
|
||||
use ort::Session;
|
||||
#[cfg(feature = "aivmx")]
|
||||
use std::io::Cursor;
|
||||
use tokenizers::Tokenizer;
|
||||
|
||||
#[derive(PartialEq, Eq, Clone)]
|
||||
@@ -30,10 +24,9 @@ where
|
||||
}
|
||||
|
||||
pub struct TTSModel {
|
||||
vits2: Option<Session>,
|
||||
vits2: Session,
|
||||
style_vectors: Array2<f32>,
|
||||
ident: TTSIdent,
|
||||
bytes: Option<Vec<u8>>,
|
||||
}
|
||||
|
||||
/// High-level Style-Bert-VITS2's API
|
||||
@@ -42,7 +35,6 @@ pub struct TTSModelHolder {
|
||||
bert: Session,
|
||||
models: Vec<TTSModel>,
|
||||
jtalk: jtalk::JTalk,
|
||||
max_loaded_models: Option<usize>,
|
||||
}
|
||||
|
||||
impl TTSModelHolder {
|
||||
@@ -51,13 +43,9 @@ impl TTSModelHolder {
|
||||
/// # Examples
|
||||
///
|
||||
/// ```rs
|
||||
/// let mut tts_holder = TTSModelHolder::new(std::fs::read("deberta.onnx")?, std::fs::read("tokenizer.json")?, None)?;
|
||||
/// let mut tts_holder = TTSModelHolder::new(std::fs::read("deberta.onnx")?, std::fs::read("tokenizer.json")?)?;
|
||||
/// ```
|
||||
pub fn new<P: AsRef<[u8]>>(
|
||||
bert_model_bytes: P,
|
||||
tokenizer_bytes: P,
|
||||
max_loaded_models: Option<usize>,
|
||||
) -> Result<Self> {
|
||||
pub fn new<P: AsRef<[u8]>>(bert_model_bytes: P, tokenizer_bytes: P) -> Result<Self> {
|
||||
let bert = model::load_model(bert_model_bytes, true)?;
|
||||
let jtalk = jtalk::JTalk::new()?;
|
||||
let tokenizer = tokenizer::get_tokenizer(tokenizer_bytes)?;
|
||||
@@ -66,7 +54,6 @@ impl TTSModelHolder {
|
||||
models: vec![],
|
||||
jtalk,
|
||||
tokenizer,
|
||||
max_loaded_models,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -75,53 +62,6 @@ impl TTSModelHolder {
|
||||
self.models.iter().map(|m| m.ident.to_string()).collect()
|
||||
}
|
||||
|
||||
#[cfg(feature = "aivmx")]
|
||||
pub fn load_aivmx<I: Into<TTSIdent>, P: AsRef<[u8]>>(
|
||||
&mut self,
|
||||
ident: I,
|
||||
aivmx_bytes: P,
|
||||
) -> Result<()> {
|
||||
let ident = ident.into();
|
||||
if self.find_model(ident.clone()).is_err() {
|
||||
let mut load = true;
|
||||
if let Some(max) = self.max_loaded_models {
|
||||
if self.models.iter().filter(|x| x.vits2.is_some()).count() >= max {
|
||||
load = false;
|
||||
}
|
||||
}
|
||||
let model = model::load_model(&aivmx_bytes, false)?;
|
||||
let metadata = model.metadata()?;
|
||||
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)?;
|
||||
let style_vectors = {
|
||||
let shape = reader.shape().to_vec();
|
||||
let order = reader.order();
|
||||
let data = reader.into_vec::<f32>()?;
|
||||
let shape = match shape[..] {
|
||||
[i1, i2] => [i1 as usize, i2 as usize],
|
||||
_ => panic!("expected 2D array"),
|
||||
};
|
||||
let true_shape = shape.set_f(order == npyz::Order::Fortran);
|
||||
ndarray::Array2::from_shape_vec(true_shape, data)?
|
||||
};
|
||||
drop(metadata);
|
||||
self.models.push(TTSModel {
|
||||
vits2: if load { Some(model) } else { None },
|
||||
bytes: if self.max_loaded_models.is_some() {
|
||||
Some(aivmx_bytes.as_ref().to_vec())
|
||||
} else {
|
||||
None
|
||||
},
|
||||
ident,
|
||||
style_vectors,
|
||||
})
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Load a .sbv2 file binary
|
||||
///
|
||||
/// # Examples
|
||||
@@ -154,25 +94,10 @@ impl TTSModelHolder {
|
||||
) -> Result<()> {
|
||||
let ident = ident.into();
|
||||
if self.find_model(ident.clone()).is_err() {
|
||||
let mut load = true;
|
||||
if let Some(max) = self.max_loaded_models {
|
||||
if self.models.iter().filter(|x| x.vits2.is_some()).count() >= max {
|
||||
load = false;
|
||||
}
|
||||
}
|
||||
self.models.push(TTSModel {
|
||||
vits2: if load {
|
||||
Some(model::load_model(&vits2_bytes, false)?)
|
||||
} else {
|
||||
None
|
||||
},
|
||||
vits2: model::load_model(vits2_bytes, false)?,
|
||||
style_vectors: style::load_style(style_vectors_bytes)?,
|
||||
ident,
|
||||
bytes: if self.max_loaded_models.is_some() {
|
||||
Some(vits2_bytes.as_ref().to_vec())
|
||||
} else {
|
||||
None
|
||||
},
|
||||
})
|
||||
}
|
||||
Ok(())
|
||||
@@ -220,42 +145,6 @@ impl TTSModelHolder {
|
||||
.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();
|
||||
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 {
|
||||
if self.models.iter().filter(|x| x.vits2.is_some()).count() >= max {
|
||||
self.unload(self.models.first().unwrap().ident.clone());
|
||||
}
|
||||
}
|
||||
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
|
||||
///
|
||||
@@ -278,19 +167,12 @@ impl TTSModelHolder {
|
||||
/// let audio = tts_holder.easy_synthesize("tsukuyomi", "こんにちは", 0, SynthesizeOptions::default())?;
|
||||
/// ```
|
||||
pub fn easy_synthesize<I: Into<TTSIdent> + Copy>(
|
||||
&mut self,
|
||||
&self,
|
||||
ident: I,
|
||||
text: &str,
|
||||
style_id: i32,
|
||||
speaker_id: i64,
|
||||
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();
|
||||
@@ -301,17 +183,14 @@ impl TTSModelHolder {
|
||||
}
|
||||
let (bert_ori, phones, tones, lang_ids) = self.parse_text(t)?;
|
||||
let audio = model::synthesize(
|
||||
vits2,
|
||||
&self.find_model(ident)?.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 {
|
||||
@@ -325,21 +204,47 @@ impl TTSModelHolder {
|
||||
} else {
|
||||
let (bert_ori, phones, tones, lang_ids) = self.parse_text(text)?;
|
||||
model::synthesize(
|
||||
vits2,
|
||||
&self.find_model(ident)?.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)
|
||||
}
|
||||
|
||||
/// Synthesize text to audio
|
||||
///
|
||||
/// # Note
|
||||
/// This function is for low-level usage, use `easy_synthesize` for high-level usage.
|
||||
#[allow(clippy::too_many_arguments)]
|
||||
pub fn synthesize<I: Into<TTSIdent>>(
|
||||
&self,
|
||||
ident: I,
|
||||
bert_ori: Array2<f32>,
|
||||
phones: Array1<i64>,
|
||||
tones: Array1<i64>,
|
||||
lang_ids: Array1<i64>,
|
||||
style_vector: Array1<f32>,
|
||||
sdp_ratio: f32,
|
||||
length_scale: f32,
|
||||
) -> Result<Vec<u8>> {
|
||||
let audio_array = model::synthesize(
|
||||
&self.find_model(ident)?.vits2,
|
||||
bert_ori.to_owned(),
|
||||
phones,
|
||||
tones,
|
||||
lang_ids,
|
||||
style_vector,
|
||||
sdp_ratio,
|
||||
length_scale,
|
||||
)?;
|
||||
tts_util::array_to_vec(audio_array)
|
||||
}
|
||||
}
|
||||
|
||||
/// Synthesize options
|
||||
|
||||
106
sbv2_wasm/pnpm-lock.yaml
generated
106
sbv2_wasm/pnpm-lock.yaml
generated
@@ -10,72 +10,72 @@ importers:
|
||||
dependencies:
|
||||
onnxruntime-web:
|
||||
specifier: ^1.19.2
|
||||
version: 1.20.0
|
||||
version: 1.19.2
|
||||
devDependencies:
|
||||
'@biomejs/biome':
|
||||
specifier: ^1.9.2
|
||||
version: 1.9.4
|
||||
version: 1.9.3
|
||||
'@types/node':
|
||||
specifier: ^22.7.4
|
||||
version: 22.8.0
|
||||
version: 22.7.4
|
||||
esbuild:
|
||||
specifier: ^0.24.0
|
||||
version: 0.24.0
|
||||
typescript:
|
||||
specifier: ^5.6.2
|
||||
version: 5.6.3
|
||||
version: 5.6.2
|
||||
|
||||
packages:
|
||||
|
||||
'@biomejs/biome@1.9.4':
|
||||
resolution: {integrity: sha512-1rkd7G70+o9KkTn5KLmDYXihGoTaIGO9PIIN2ZB7UJxFrWw04CZHPYiMRjYsaDvVV7hP1dYNRLxSANLaBFGpog==}
|
||||
'@biomejs/biome@1.9.3':
|
||||
resolution: {integrity: sha512-POjAPz0APAmX33WOQFGQrwLvlu7WLV4CFJMlB12b6ZSg+2q6fYu9kZwLCOA+x83zXfcPd1RpuWOKJW0GbBwLIQ==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
hasBin: true
|
||||
|
||||
'@biomejs/cli-darwin-arm64@1.9.4':
|
||||
resolution: {integrity: sha512-bFBsPWrNvkdKrNCYeAp+xo2HecOGPAy9WyNyB/jKnnedgzl4W4Hb9ZMzYNbf8dMCGmUdSavlYHiR01QaYR58cw==}
|
||||
'@biomejs/cli-darwin-arm64@1.9.3':
|
||||
resolution: {integrity: sha512-QZzD2XrjJDUyIZK+aR2i5DDxCJfdwiYbUKu9GzkCUJpL78uSelAHAPy7m0GuPMVtF/Uo+OKv97W3P9nuWZangQ==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [arm64]
|
||||
os: [darwin]
|
||||
|
||||
'@biomejs/cli-darwin-x64@1.9.4':
|
||||
resolution: {integrity: sha512-ngYBh/+bEedqkSevPVhLP4QfVPCpb+4BBe2p7Xs32dBgs7rh9nY2AIYUL6BgLw1JVXV8GlpKmb/hNiuIxfPfZg==}
|
||||
'@biomejs/cli-darwin-x64@1.9.3':
|
||||
resolution: {integrity: sha512-vSCoIBJE0BN3SWDFuAY/tRavpUtNoqiceJ5PrU3xDfsLcm/U6N93JSM0M9OAiC/X7mPPfejtr6Yc9vSgWlEgVw==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [x64]
|
||||
os: [darwin]
|
||||
|
||||
'@biomejs/cli-linux-arm64-musl@1.9.4':
|
||||
resolution: {integrity: sha512-v665Ct9WCRjGa8+kTr0CzApU0+XXtRgwmzIf1SeKSGAv+2scAlW6JR5PMFo6FzqqZ64Po79cKODKf3/AAmECqA==}
|
||||
'@biomejs/cli-linux-arm64-musl@1.9.3':
|
||||
resolution: {integrity: sha512-VBzyhaqqqwP3bAkkBrhVq50i3Uj9+RWuj+pYmXrMDgjS5+SKYGE56BwNw4l8hR3SmYbLSbEo15GcV043CDSk+Q==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [arm64]
|
||||
os: [linux]
|
||||
|
||||
'@biomejs/cli-linux-arm64@1.9.4':
|
||||
resolution: {integrity: sha512-fJIW0+LYujdjUgJJuwesP4EjIBl/N/TcOX3IvIHJQNsAqvV2CHIogsmA94BPG6jZATS4Hi+xv4SkBBQSt1N4/g==}
|
||||
'@biomejs/cli-linux-arm64@1.9.3':
|
||||
resolution: {integrity: sha512-vJkAimD2+sVviNTbaWOGqEBy31cW0ZB52KtpVIbkuma7PlfII3tsLhFa+cwbRAcRBkobBBhqZ06hXoZAN8NODQ==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [arm64]
|
||||
os: [linux]
|
||||
|
||||
'@biomejs/cli-linux-x64-musl@1.9.4':
|
||||
resolution: {integrity: sha512-gEhi/jSBhZ2m6wjV530Yy8+fNqG8PAinM3oV7CyO+6c3CEh16Eizm21uHVsyVBEB6RIM8JHIl6AGYCv6Q6Q9Tg==}
|
||||
'@biomejs/cli-linux-x64-musl@1.9.3':
|
||||
resolution: {integrity: sha512-TJmnOG2+NOGM72mlczEsNki9UT+XAsMFAOo8J0me/N47EJ/vkLXxf481evfHLlxMejTY6IN8SdRSiPVLv6AHlA==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [x64]
|
||||
os: [linux]
|
||||
|
||||
'@biomejs/cli-linux-x64@1.9.4':
|
||||
resolution: {integrity: sha512-lRCJv/Vi3Vlwmbd6K+oQ0KhLHMAysN8lXoCI7XeHlxaajk06u7G+UsFSO01NAs5iYuWKmVZjmiOzJ0OJmGsMwg==}
|
||||
'@biomejs/cli-linux-x64@1.9.3':
|
||||
resolution: {integrity: sha512-x220V4c+romd26Mu1ptU+EudMXVS4xmzKxPVb9mgnfYlN4Yx9vD5NZraSx/onJnd3Gh/y8iPUdU5CDZJKg9COA==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [x64]
|
||||
os: [linux]
|
||||
|
||||
'@biomejs/cli-win32-arm64@1.9.4':
|
||||
resolution: {integrity: sha512-tlbhLk+WXZmgwoIKwHIHEBZUwxml7bRJgk0X2sPyNR3S93cdRq6XulAZRQJ17FYGGzWne0fgrXBKpl7l4M87Hg==}
|
||||
'@biomejs/cli-win32-arm64@1.9.3':
|
||||
resolution: {integrity: sha512-lg/yZis2HdQGsycUvHWSzo9kOvnGgvtrYRgoCEwPBwwAL8/6crOp3+f47tPwI/LI1dZrhSji7PNsGKGHbwyAhw==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [arm64]
|
||||
os: [win32]
|
||||
|
||||
'@biomejs/cli-win32-x64@1.9.4':
|
||||
resolution: {integrity: sha512-8Y5wMhVIPaWe6jw2H+KlEm4wP/f7EW3810ZLmDlrEEy5KvBsb9ECEfu/kMWD484ijfQ8+nIi0giMgu9g1UAuuA==}
|
||||
'@biomejs/cli-win32-x64@1.9.3':
|
||||
resolution: {integrity: sha512-cQMy2zanBkVLpmmxXdK6YePzmZx0s5Z7KEnwmrW54rcXK3myCNbQa09SwGZ8i/8sLw0H9F3X7K4rxVNGU8/D4Q==}
|
||||
engines: {node: '>=14.21.3'}
|
||||
cpu: [x64]
|
||||
os: [win32]
|
||||
@@ -254,8 +254,8 @@ packages:
|
||||
'@protobufjs/utf8@1.1.0':
|
||||
resolution: {integrity: sha512-Vvn3zZrhQZkkBE8LSuW3em98c0FwgO4nxzv6OdSxPKJIEKY2bGbHn+mhGIPerzI4twdxaP8/0+06HBpwf345Lw==}
|
||||
|
||||
'@types/node@22.8.0':
|
||||
resolution: {integrity: sha512-84rafSBHC/z1i1E3p0cJwKA+CfYDNSXX9WSZBRopjIzLET8oNt6ht2tei4C7izwDeEiLLfdeSVBv1egOH916hg==}
|
||||
'@types/node@22.7.4':
|
||||
resolution: {integrity: sha512-y+NPi1rFzDs1NdQHHToqeiX2TIS79SWEAw9GYhkkx8bD0ChpfqC+n2j5OXOCpzfojBEBt6DnEnnG9MY0zk1XLg==}
|
||||
|
||||
esbuild@0.24.0:
|
||||
resolution: {integrity: sha512-FuLPevChGDshgSicjisSooU0cemp/sGXR841D5LHMB7mTVOmsEHcAxaH3irL53+8YDIeVNQEySh4DaYU/iuPqQ==}
|
||||
@@ -271,11 +271,11 @@ packages:
|
||||
long@5.2.3:
|
||||
resolution: {integrity: sha512-lcHwpNoggQTObv5apGNCTdJrO69eHOZMi4BNC+rTLER8iHAqGrUVeLh/irVIM7zTw2bOXA8T6uNPeujwOLg/2Q==}
|
||||
|
||||
onnxruntime-common@1.20.0:
|
||||
resolution: {integrity: sha512-9ehS4ul5fBszIcHhfxuDgk45lO+Fqrxmrgwk1Pxb1JRvbQiCB/v9Royv95SRCWHktLMviqNjBsEd/biJhd39cg==}
|
||||
onnxruntime-common@1.19.2:
|
||||
resolution: {integrity: sha512-a4R7wYEVFbZBlp0BfhpbFWqe4opCor3KM+5Wm22Az3NGDcQMiU2hfG/0MfnBs+1ZrlSGmlgWeMcXQkDk1UFb8Q==}
|
||||
|
||||
onnxruntime-web@1.20.0:
|
||||
resolution: {integrity: sha512-IoUf8dqHFJLV4DUSz+Ok+xxyN6cQk57gb20m6PZE5gag3QXuvegYMq9dG8t/QF4JjTKIwvfvnr16ouzCCB9IMA==}
|
||||
onnxruntime-web@1.19.2:
|
||||
resolution: {integrity: sha512-r0ok6KpTUXR4WA+rHvUiZn7JoH02e8iS7XE1p5bXk7q3E0UaRFfYvpMNUHqEPiTBMuIssfBxDCQjUihV8dDFPg==}
|
||||
|
||||
platform@1.3.6:
|
||||
resolution: {integrity: sha512-fnWVljUchTro6RiCFvCXBbNhJc2NijN7oIQxbwsyL0buWJPG85v81ehlHI9fXrJsMNgTofEoWIQeClKpgxFLrg==}
|
||||
@@ -284,8 +284,8 @@ packages:
|
||||
resolution: {integrity: sha512-mRUWCc3KUU4w1jU8sGxICXH/gNS94DvI1gxqDvBzhj1JpcsimQkYiOJfwsPUykUI5ZaspFbSgmBLER8IrQ3tqw==}
|
||||
engines: {node: '>=12.0.0'}
|
||||
|
||||
typescript@5.6.3:
|
||||
resolution: {integrity: sha512-hjcS1mhfuyi4WW8IWtjP7brDrG2cuDZukyrYrSauoXGNgx0S7zceP07adYkJycEr56BOUTNPzbInooiN3fn1qw==}
|
||||
typescript@5.6.2:
|
||||
resolution: {integrity: sha512-NW8ByodCSNCwZeghjN3o+JX5OFH0Ojg6sadjEKY4huZ52TqbJTJnDo5+Tw98lSy63NZvi4n+ez5m2u5d4PkZyw==}
|
||||
engines: {node: '>=14.17'}
|
||||
hasBin: true
|
||||
|
||||
@@ -294,39 +294,39 @@ packages:
|
||||
|
||||
snapshots:
|
||||
|
||||
'@biomejs/biome@1.9.4':
|
||||
'@biomejs/biome@1.9.3':
|
||||
optionalDependencies:
|
||||
'@biomejs/cli-darwin-arm64': 1.9.4
|
||||
'@biomejs/cli-darwin-x64': 1.9.4
|
||||
'@biomejs/cli-linux-arm64': 1.9.4
|
||||
'@biomejs/cli-linux-arm64-musl': 1.9.4
|
||||
'@biomejs/cli-linux-x64': 1.9.4
|
||||
'@biomejs/cli-linux-x64-musl': 1.9.4
|
||||
'@biomejs/cli-win32-arm64': 1.9.4
|
||||
'@biomejs/cli-win32-x64': 1.9.4
|
||||
'@biomejs/cli-darwin-arm64': 1.9.3
|
||||
'@biomejs/cli-darwin-x64': 1.9.3
|
||||
'@biomejs/cli-linux-arm64': 1.9.3
|
||||
'@biomejs/cli-linux-arm64-musl': 1.9.3
|
||||
'@biomejs/cli-linux-x64': 1.9.3
|
||||
'@biomejs/cli-linux-x64-musl': 1.9.3
|
||||
'@biomejs/cli-win32-arm64': 1.9.3
|
||||
'@biomejs/cli-win32-x64': 1.9.3
|
||||
|
||||
'@biomejs/cli-darwin-arm64@1.9.4':
|
||||
'@biomejs/cli-darwin-arm64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-darwin-x64@1.9.4':
|
||||
'@biomejs/cli-darwin-x64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-linux-arm64-musl@1.9.4':
|
||||
'@biomejs/cli-linux-arm64-musl@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-linux-arm64@1.9.4':
|
||||
'@biomejs/cli-linux-arm64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-linux-x64-musl@1.9.4':
|
||||
'@biomejs/cli-linux-x64-musl@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-linux-x64@1.9.4':
|
||||
'@biomejs/cli-linux-x64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-win32-arm64@1.9.4':
|
||||
'@biomejs/cli-win32-arm64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@biomejs/cli-win32-x64@1.9.4':
|
||||
'@biomejs/cli-win32-x64@1.9.3':
|
||||
optional: true
|
||||
|
||||
'@esbuild/aix-ppc64@0.24.0':
|
||||
@@ -424,7 +424,7 @@ snapshots:
|
||||
|
||||
'@protobufjs/utf8@1.1.0': {}
|
||||
|
||||
'@types/node@22.8.0':
|
||||
'@types/node@22.7.4':
|
||||
dependencies:
|
||||
undici-types: 6.19.8
|
||||
|
||||
@@ -461,14 +461,14 @@ snapshots:
|
||||
|
||||
long@5.2.3: {}
|
||||
|
||||
onnxruntime-common@1.20.0: {}
|
||||
onnxruntime-common@1.19.2: {}
|
||||
|
||||
onnxruntime-web@1.20.0:
|
||||
onnxruntime-web@1.19.2:
|
||||
dependencies:
|
||||
flatbuffers: 1.12.0
|
||||
guid-typescript: 1.0.9
|
||||
long: 5.2.3
|
||||
onnxruntime-common: 1.20.0
|
||||
onnxruntime-common: 1.19.2
|
||||
platform: 1.3.6
|
||||
protobufjs: 7.4.0
|
||||
|
||||
@@ -486,9 +486,9 @@ snapshots:
|
||||
'@protobufjs/path': 1.1.2
|
||||
'@protobufjs/pool': 1.1.0
|
||||
'@protobufjs/utf8': 1.1.0
|
||||
'@types/node': 22.8.0
|
||||
'@types/node': 22.7.4
|
||||
long: 5.2.3
|
||||
|
||||
typescript@5.6.3: {}
|
||||
typescript@5.6.2: {}
|
||||
|
||||
undici-types@6.19.8: {}
|
||||
|
||||
Reference in New Issue
Block a user