feat!: RunAsyncを使う

Cargo.toml

@@ -99,7 +99,7 @@ zip = "0.6.3"
 
 [workspace.dependencies.voicevox-ort]
 git = "https://github.com/VOICEVOX/ort.git"
-rev = "17f741301db0bb08da0eafe8a338e5efd8a4b5df"
+rev = "09a9fe1619c1561efafc02f68f0bda4aad879771"
 
 [workspace.dependencies.open_jtalk]
 git = "https://github.com/VOICEVOX/open_jtalk-rs.git"

crates/voicevox_core/src/infer.rs

@@ -12,14 +12,39 @@ use ndarray::{Array, ArrayD, Dimension, ShapeError};
 use thiserror::Error;
 
 use crate::{
+    asyncs::{Async, BlockingThreadPool, SingleTasked},
     devices::{DeviceSpec, GpuSpec},
     StyleType, SupportedDevices,
 };
 
+pub(crate) trait AsyncExt: Async {
+    async fn run_session<R: InferenceRuntime>(
+        ctx: R::RunContext,
+    ) -> anyhow::Result<Vec<OutputTensor>>;
+}
+
+impl AsyncExt for SingleTasked {
+    async fn run_session<R: InferenceRuntime>(
+        ctx: R::RunContext,
+    ) -> anyhow::Result<Vec<OutputTensor>> {
+        R::run_blocking(ctx)
+    }
+}
+
+impl AsyncExt for BlockingThreadPool {
+    async fn run_session<R: InferenceRuntime>(
+        ctx: R::RunContext,
+    ) -> anyhow::Result<Vec<OutputTensor>> {
+        R::run_async(ctx).await
+    }
+}
+
 pub(crate) trait InferenceRuntime: 'static {
     // TODO: "session"とは何なのかを定め、ドキュメントを書く。`InferenceSessionSet`も同様。
-    type Session: Sized + Send + 'static;
-    type RunContext<'a>: From<&'a mut Self::Session> + PushInputTensor;
+    type Session;
+
+    // 本当は`From<&'_ Self::Session>`としたいが、 rust-lang/rust#100013 が立ち塞がる
+    type RunContext: From<Arc<Self::Session>> + PushInputTensor;
 
     /// 名前。
     const DISPLAY_NAME: &'static str;
@@ -45,7 +70,9 @@ pub(crate) trait InferenceRuntime: 'static {
         Vec<ParamInfo<OutputScalarKind>>,
     )>;
 
-    fn run(ctx: Self::RunContext<'_>) -> anyhow::Result<Vec<OutputTensor>>;
+    fn run_blocking(ctx: Self::RunContext) -> anyhow::Result<Vec<OutputTensor>>;
+
+    async fn run_async(ctx: Self::RunContext) -> anyhow::Result<Vec<OutputTensor>>;
 }
 
 /// 共に扱われるべき推論操作の集合を示す。
@@ -86,7 +113,7 @@ pub(crate) trait InferenceOperation: Copy + Enum {
 /// `InferenceDomain`の推論操作を表す列挙型。
 ///
 /// `::macros::InferenceOperation`により、具体型ごと生成される。
-pub(crate) trait InferenceSignature: Sized + Send + 'static {
+pub(crate) trait InferenceSignature {
     type Domain: InferenceDomain;
     type Input: InferenceInputSignature<Signature = Self>;
     type Output: InferenceOutputSignature;
@@ -96,20 +123,21 @@ pub(crate) trait InferenceSignature: Sized + Send + 'static {
 /// 推論操作の入力シグネチャ。
 ///
 /// `::macros::InferenceInputSignature`により導出される。
-pub(crate) trait InferenceInputSignature: Send + 'static {
+pub(crate) trait InferenceInputSignature {
     type Signature: InferenceSignature<Input = Self>;
     const PARAM_INFOS: &'static [ParamInfo<InputScalarKind>];
     fn make_run_context<R: InferenceRuntime>(
         self,
-        sess: &mut R::Session,
-    ) -> anyhow::Result<R::RunContext<'_>>;
+        sess: Arc<R::Session>,
+    ) -> anyhow::Result<R::RunContext>;
 }
 
 pub(crate) trait InputScalar: Sized {
     const KIND: InputScalarKind;
 
     // TODO: `Array`ではなく`ArrayView`を取ることができるかもしれない
     fn push_tensor_to_ctx(
+        name: &'static str,
         tensor: Array<Self, impl Dimension + 'static>,
         visitor: &mut impl PushInputTensor,
     ) -> anyhow::Result<()>;
@@ -124,10 +152,11 @@ impl InputScalar for T {
     const KIND: InputScalarKind = KIND_VAL;
 
     fn push_tensor_to_ctx(
+        name: &'static str,
         tensor: Array<Self, impl Dimension + 'static>,
         ctx: &mut impl PushInputTensor,
     ) -> anyhow::Result<()> {
-        ctx.push(tensor)
+        ctx.push(name, tensor)
     }
 }
 
@@ -141,15 +170,24 @@ pub(crate) enum InputScalarKind {
 }
 
 pub(crate) trait PushInputTensor {
-    fn push_int64(&mut self, tensor: Array<i64, impl Dimension + 'static>) -> anyhow::Result<()>;
-    fn push_float32(&mut self, tensor: Array<f32, impl Dimension + 'static>) -> anyhow::Result<()>;
+    fn push_int64(
+        &mut self,
+        name: &'static str,
+        tensor: Array<i64, impl Dimension + 'static>,
+    ) -> anyhow::Result<()>;
+
+    fn push_float32(
+        &mut self,
+        name: &'static str,
+        tensor: Array<f32, impl Dimension + 'static>,
+    ) -> anyhow::Result<()>;
 }
 
 /// 推論操作の出力シグネチャ。
 ///
 /// `::macros::InferenceOutputSignature`により、`TryFrom<OutputTensor>`も含めて導出される。
 pub(crate) trait InferenceOutputSignature:
-    TryFrom<Vec<OutputTensor>, Error = anyhow::Error> + Send
+    TryFrom<Vec<OutputTensor>, Error = anyhow::Error>
 {
     const PARAM_INFOS: &'static [ParamInfo<OutputScalarKind>];
 }

crates/voicevox_core/src/infer/runtimes/onnxruntime.rs

@@ -11,7 +11,7 @@
 // }
 // ```
 
-use std::{fmt::Debug, vec};
+use std::{fmt::Debug, sync::Arc, vec};
 
 use anyhow::{anyhow, bail, ensure};
 use duplicate::duplicate_item;
@@ -32,8 +32,8 @@ use super::super::{
 };
 
 impl InferenceRuntime for self::blocking::Onnxruntime {
-    type Session = ort::Session;
-    type RunContext<'a> = OnnxruntimeRunContext<'a>;
+    type Session = async_lock::Mutex<ort::Session>; // WASMでは`ort`を利用しないので、ここはasync-lockを用いてよいはず
+    type RunContext = OnnxruntimeRunContext;
 
     const DISPLAY_NAME: &'static str = if cfg!(feature = "load-onnxruntime") {
         "現在ロードされているONNX Runtime"
@@ -179,76 +179,90 @@ impl InferenceRuntime for self::blocking::Onnxruntime {
             })
             .collect::<anyhow::Result<_>>()?;
 
-        Ok((sess, input_param_infos, output_param_infos))
+        Ok((sess.into(), input_param_infos, output_param_infos))
     }
 
-    fn run(
-        OnnxruntimeRunContext { sess, inputs }: OnnxruntimeRunContext<'_>,
+    fn run_blocking(
+        OnnxruntimeRunContext { sess, inputs }: Self::RunContext,
     ) -> anyhow::Result<Vec<OutputTensor>> {
-        let outputs = sess.run(&*inputs)?;
-
-        (0..outputs.len())
-            .map(|i| {
-                let output = &outputs[i];
-
-                let ValueType::Tensor { ty, .. } = output.dtype()? else {
-                    bail!(
-                        "unexpected output. currently `ONNX_TYPE_TENSOR` and \
-                         `ONNX_TYPE_SPARSETENSOR` is supported",
-                    );
-                };
+        extract_outputs(&sess.lock_blocking().run(inputs)?)
+    }
 
-                match ty {
-                    TensorElementType::Float32 => {
-                        let output = output.try_extract_tensor::<f32>()?;
-                        Ok(OutputTensor::Float32(output.into_owned()))
-                    }
-                    _ => bail!("unexpected output tensor element data type"),
-                }
-            })
-            .collect()
+    async fn run_async(
+        OnnxruntimeRunContext { sess, inputs }: Self::RunContext,
+    ) -> anyhow::Result<Vec<OutputTensor>> {
+        extract_outputs(&sess.lock().await.run_async(inputs)?.await?)
     }
 }
 
-pub(crate) struct OnnxruntimeRunContext<'sess> {
-    sess: &'sess ort::Session,
-    inputs: Vec<ort::SessionInputValue<'static>>,
+pub(crate) struct OnnxruntimeRunContext {
+    sess: Arc<async_lock::Mutex<ort::Session>>,
+    inputs: Vec<(&'static str, ort::SessionInputValue<'static>)>,
 }
 
-impl OnnxruntimeRunContext<'_> {
+impl OnnxruntimeRunContext {
     fn push_input(
         &mut self,
+        name: &'static str,
         input: Array<
             impl PrimitiveTensorElementType + Debug + Clone + 'static,
             impl Dimension + 'static,
         >,
     ) -> anyhow::Result<()> {
         let input = ort::Value::from_array(input)?.into();
-        self.inputs.push(input);
+        self.inputs.push((name, input));
         Ok(())
     }
 }
 
-impl<'sess> From<&'sess mut ort::Session> for OnnxruntimeRunContext<'sess> {
-    fn from(sess: &'sess mut ort::Session) -> Self {
+impl From<Arc<async_lock::Mutex<ort::Session>>> for OnnxruntimeRunContext {
+    fn from(sess: Arc<async_lock::Mutex<ort::Session>>) -> Self {
         Self {
             sess,
             inputs: vec![],
         }
     }
 }
 
-impl PushInputTensor for OnnxruntimeRunContext<'_> {
+impl PushInputTensor for OnnxruntimeRunContext {
     #[duplicate_item(
         method           T;
         [ push_int64 ]   [ i64 ];
         [ push_float32 ] [ f32 ];
     )]
-    fn method(&mut self, tensor: Array<T, impl Dimension + 'static>) -> anyhow::Result<()> {
-        self.push_input(tensor)
+    fn method(
+        &mut self,
+        name: &'static str,
+        tensor: Array<T, impl Dimension + 'static>,
+    ) -> anyhow::Result<()> {
+        self.push_input(name, tensor)
     }
 }
 
+// FIXME: use ouroboros to reduce copies
+fn extract_outputs(outputs: &ort::SessionOutputs<'_, '_>) -> anyhow::Result<Vec<OutputTensor>> {
+    (0..outputs.len())
+        .map(|i| {
+            let output = &outputs[i];
+
+            let ValueType::Tensor { ty, .. } = output.dtype()? else {
+                bail!(
+                    "unexpected output. currently `ONNX_TYPE_TENSOR` and `ONNX_TYPE_SPARSETENSOR`
+                     is supported",
+                );
+            };
+
+            match ty {
+                TensorElementType::Float32 => {
+                    let output = output.try_extract_tensor::<f32>()?;
+                    Ok(OutputTensor::Float32(output.into_owned()))
+                }
+                _ => bail!("unexpected output tensor element data type"),
+            }
+        })
+        .collect()
+}
+
 pub(crate) mod blocking {
     use ort::EnvHandle;
     use ref_cast::{ref_cast_custom, RefCastCustom};

crates/voicevox_core/src/infer/session_set.rs

@@ -12,7 +12,7 @@ use super::{
 };
 
 pub(crate) struct InferenceSessionSet<R: InferenceRuntime, D: InferenceDomain>(
-    EnumMap<D::Operation, Arc<std::sync::Mutex<R::Session>>>,
+    EnumMap<D::Operation, Arc<R::Session>>,
 );
 
 impl<R: InferenceRuntime, D: InferenceDomain> InferenceSessionSet<R, D> {
@@ -33,7 +33,7 @@ impl<R: InferenceRuntime, D: InferenceDomain> InferenceSessionSet<R, D> {
                 check_param_infos(expected_input_param_infos, &actual_input_param_infos)?;
                 check_param_infos(expected_output_param_infos, &actual_output_param_infos)?;
 
-                Ok((op.into_usize(), std::sync::Mutex::new(sess).into()))
+                Ok((op.into_usize(), sess.into()))
             })
             .collect::<anyhow::Result<HashMap<_, _>>>()?;
 
@@ -84,18 +84,21 @@ impl<R: InferenceRuntime, D: InferenceDomain> InferenceSessionSet<R, D> {
 }
 
 pub(crate) struct InferenceSessionCell<R: InferenceRuntime, I> {
-    inner: Arc<std::sync::Mutex<R::Session>>,
+    inner: Arc<R::Session>,
     marker: PhantomData<fn(I)>,
 }
 
 impl<R: InferenceRuntime, I: InferenceInputSignature> InferenceSessionCell<R, I> {
-    pub(crate) fn run(
+    pub(crate) async fn run<A: super::AsyncExt>(
         self,
         input: I,
     ) -> crate::Result<<I::Signature as InferenceSignature>::Output> {
-        let inner = &mut self.inner.lock().unwrap();
-        (|| R::run(input.make_run_context::<R>(inner)?)?.try_into())()
-            .map_err(ErrorRepr::RunModel)
-            .map_err(Into::into)
+        async {
+            let ctx = input.make_run_context::<R>(self.inner.clone())?;
+            A::run_session::<R>(ctx).await?.try_into()
+        }
+        .await
+        .map_err(ErrorRepr::RunModel)
+        .map_err(Into::into)
     }
 }

crates/voicevox_core/src/status.rs

@@ -9,6 +9,7 @@ use itertools::iproduct;
 use crate::{
     error::{ErrorRepr, LoadModelError, LoadModelErrorKind, LoadModelResult},
     infer::{
+        self,
         domains::{inference_domain_map_values, InferenceDomainMap, TalkDomain},
         session_set::{InferenceSessionCell, InferenceSessionSet},
         InferenceDomain, InferenceInputSignature, InferenceRuntime, InferenceSessionOptions,
@@ -104,17 +105,18 @@ impl<R: InferenceRuntime> Status<R> {
     /// # Panics
     ///
     /// `self`が`model_id`を含んでいないとき、パニックする。
-    pub(crate) fn run_session<I>(
+    pub(crate) async fn run_session<A, I>(
         &self,
         model_id: VoiceModelId,
         input: I,
     ) -> Result<<I::Signature as InferenceSignature>::Output>
     where
+        A: infer::AsyncExt,
         I: InferenceInputSignature,
         <I::Signature as InferenceSignature>::Domain: InferenceDomainExt,
     {
         let sess = self.loaded_models.lock().unwrap().get(model_id);
-        sess.run(input)
+        sess.run::<A>(input).await
     }
 }