Update wasi-nn version

.github/workflows/main.yaml

@@ -21,7 +21,7 @@ jobs:
 
       - name: Build Wasmtime + wasi-nn
         run: |
-          rustup target add wasm32-wasi
+          rustup target add wasm32-wasip1
           rustup target add wasm32-unknown-unknown
           git clone https://github.com/bytecodealliance/wasmtime --branch v16.0.0 --depth 1 --recursive
           cd wasmtime
@@ -52,13 +52,13 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-      - run: rustup target add wasm32-wasi
+      - run: rustup target add wasm32-wasip1
       - name: Run tests on native architecture
         working-directory: rust
         run: cargo test
-      - name: Build on wasm32-wasi
+      - name: Build on wasm32-wasip1
         working-directory: rust
-        run: cargo build --target=wasm32-wasi
+        run: cargo build --target=wasm32-wasip1
       - name: Check dry-run publish to crates.io
         working-directory: rust
         run: cargo publish --dry-run
@@ -68,10 +68,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
-      - run: rustup target add wasm32-wasi
-      - name: Build for wasm32-wasi
+      - run: rustup target add wasm32-wasip1
+      - name: Build for wasm32-wasip1
         working-directory: image2tensor
-        run: cargo build --target=wasm32-wasi
+        run: cargo build --target=wasm32-wasip1
       - name: Check dry-run publish to crates.io
         working-directory: image2tensor
         run: cargo publish --dry-run

build.sh

@@ -24,13 +24,13 @@ else
                 echo "The first argument: $1"
                 FIXTURE=https://github.com/intel/openvino-rs/raw/main/crates/openvino/tests/fixtures/mobilenet
                 pushd $WASI_NN_DIR/rust/
-                cargo build --release --target=wasm32-wasi
+                cargo build --release --target=wasm32-wasip1
                 mkdir -p $WASI_NN_DIR/rust/examples/classification-example/build
                 RUST_BUILD_DIR=$(realpath $WASI_NN_DIR/rust/examples/classification-example/build/)
                 cp -rn examples/images $RUST_BUILD_DIR
                 pushd examples/classification-example
-                cargo build --release --target=wasm32-wasi
-                cp target/wasm32-wasi/release/wasi-nn-example.wasm $RUST_BUILD_DIR
+                cargo build --release --target=wasm32-wasip1
+                cp target/wasm32-wasip1/release/wasi-nn-example.wasm $RUST_BUILD_DIR
                 pushd build
                 wget --no-clobber --directory-prefix=$RUST_BUILD_DIR $FIXTURE/mobilenet.bin
                 wget --no-clobber --directory-prefix=$RUST_BUILD_DIR $FIXTURE/mobilenet.xml

rust/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "wasi-nn"
-version = "0.7.0"
+version = "0.8.0"
 authors = ["The Bytecode Alliance Developers"]
 description = "High-level Rust bindings for wasi-nn"
 license = "Apache-2.0"

rust/examples/classification-example/src/main.rs

@@ -37,16 +37,18 @@ fn main() {
         TensorType::Fp32,
         &data,
     );
-    exec_context.set_input("data", tensor).unwrap();
-    println!("Set input tensor");
 
-    // Execute the inferencing
-    exec_context.compute().unwrap();
+    let output_tensor_vec = exec_context.compute(vec![("data".to_string(), tensor)]).unwrap();
     println!("Executed graph inference");
 
-    // Get the inferencing result (bytes) and convert it to f32
-    println!("Getting inferencing output");
-    let output_data = exec_context.get_output("squeezenet0_flatten0_reshape0").unwrap().data();
+    let output_tensor = output_tensor_vec.iter().find_map(|(tensor_name, tensor)| {
+        if tensor_name == "squeezenet0_flatten0_reshape0" {
+            Some(tensor)
+        } else {
+            None
+        }
+    });
+    let output_data = output_tensor.expect("No output tensor").data();
 
     println!("Retrieved output data with length: {}", output_data.len());
     let output_f32 = bytes_to_f32_vec(output_data);

rust/wit/wasi-nn.wit

@@ -1,4 +1,4 @@
-package wasi:[email protected]08-19;
+package wasi:[email protected]10-28;
 
 /// `wasi-nn` is a WASI API for performing machine learning (ML) inference. The API is not (yet)
 /// capable of performing ML training. WebAssembly programs that want to use a host's ML
@@ -110,25 +110,19 @@ interface graph {
 /// `graph` to input tensors before `compute`-ing an inference:
 interface inference {
     use errors.{error};
-    use tensor.{tensor, tensor-data};
+    use tensor.{tensor};
+
+    /// Identify a tensor by name; this is necessary to associate tensors to
+    /// graph inputs and outputs.
+    type named-tensor = tuple<string, tensor>;
 
     /// Bind a `graph` to the input and output tensors for an inference.
     ///
     /// TODO: this may no longer be necessary in WIT
     /// (https://github.com/WebAssembly/wasi-nn/issues/43)
     resource graph-execution-context {
-        /// Define the inputs to use for inference.
-        set-input: func(name: string, tensor: tensor) -> result<_, error>;
-
         /// Compute the inference on the given inputs.
-        ///
-        /// Note the expected sequence of calls: `set-input`, `compute`, `get-output`. TODO: this
-        /// expectation could be removed as a part of
-        /// https://github.com/WebAssembly/wasi-nn/issues/43.
-        compute: func() -> result<_, error>;
-
-        /// Extract the outputs after inference.
-        get-output: func(name: string) -> result<tensor, error>;
+        compute: func(inputs: list<named-tensor>) -> result<list<named-tensor>, error>;
     }
 }
 
@@ -163,4 +157,4 @@ interface errors {
         /// Errors can propagated with backend specific status through a string value.
         data: func() -> string;
     }
-}
+}