wasi-nn: use resources

ci/vendor-wit.sh

@@ -36,5 +36,9 @@ cp -r $dst crates/wasi-http/wit
 # slightly different than above.
 repo=https://raw.githubusercontent.com/WebAssembly/wasi-nn
 revision=e2310b
-curl -L $repo/$revision/wit/wasi-nn.wit -o crates/wasi-nn/wit/wasi-nn.wit
 curl -L $repo/$revision/wasi-nn.witx -o crates/wasi-nn/witx/wasi-nn.witx
+# TODO: the in-tree `wasi-nn` implementation does not yet fully support the
+# latest WIT specification on `main`. To create a baseline for moving forward,
+# the in-tree WIT incorporates some but not all of the upstream changes. This
+# TODO can be removed once the implementation catches up with the spec.
+# curl -L $repo/$revision/wit/wasi-nn.wit -o crates/wasi-nn/wit/wasi-nn.wit

crates/bench-api/src/lib.rs

@@ -418,7 +418,7 @@ struct BenchState {
 struct HostState {
     wasi: WasiCtx,
     #[cfg(feature = "wasi-nn")]
-    wasi_nn: wasmtime_wasi_nn::WasiNnCtx,
+    wasi_nn: wasmtime_wasi_nn::witx::WasiNnCtx,
 }
 
 impl BenchState {
@@ -509,7 +509,7 @@ impl BenchState {
             #[cfg(feature = "wasi-nn")]
             wasi_nn: {
                 let (backends, registry) = wasmtime_wasi_nn::preload(&[])?;
-                wasmtime_wasi_nn::WasiNnCtx::new(backends, registry)
+                wasmtime_wasi_nn::witx::WasiNnCtx::new(backends, registry)
             },
         };
 

crates/test-programs/artifacts/build.rs

@@ -90,7 +90,10 @@ fn build_and_generate_tests() {
         }
 
         // Generate a component from each test.
-        if kind == "nn" || target == "dwarf_imported_memory" || target == "dwarf_shared_memory" {
+        if target == "dwarf_imported_memory"
+            || target == "dwarf_shared_memory"
+            || target.starts_with("nn_witx")
+        {
             continue;
         }
         let adapter = match target.as_str() {

crates/test-programs/src/bin/nn_image_classification_onnx.rs → crates/test-programs/src/bin/nn_wit_image_classification_onnx.rs

@@ -1,18 +1,20 @@
 use anyhow::{Context, Result};
 use std::fs;
-use test_programs::nn::{classify, sort_results};
-use wasi_nn::{ExecutionTarget, GraphBuilder, GraphEncoding};
+use test_programs::nn::{sort_results, wit};
 
 pub fn main() -> Result<()> {
     let model = fs::read("fixture/model.onnx")
         .context("the model file to be mapped to the fixture directory")?;
-    let graph =
-        GraphBuilder::new(GraphEncoding::Onnx, ExecutionTarget::CPU).build_from_bytes([&model])?;
+    let graph = wit::load(
+        &[model],
+        wit::GraphEncoding::Onnx,
+        wit::ExecutionTarget::Cpu,
+    )?;
     let tensor = fs::read("fixture/000000062808.rgb")
         .context("the tensor file to be mapped to the fixture directory")?;
-    let results = classify(graph, tensor)?;
+    let results = wit::classify(graph, ("input", tensor), "output")?;
     let top_five = &sort_results(&results)[..5];
-    // 963 is meat loaf, meatloaf.
+    // 963 is "meat loaf, meatloaf."
     // https://github.com/onnx/models/blob/bec48b6a70e5e9042c0badbaafefe4454e072d08/validated/vision/classification/synset.txt#L963
     assert_eq!(top_five[0].class_id(), 963);
     println!("found results, sorted top 5: {:?}", top_five);

crates/test-programs/src/bin/nn_wit_image_classification_openvino.rs

@@ -0,0 +1,25 @@
+use anyhow::{Context, Result};
+use std::fs;
+use test_programs::nn::{sort_results, wit};
+
+pub fn main() -> Result<()> {
+    let xml = fs::read("fixture/model.xml")
+        .context("the model file to be mapped to the fixture directory")?;
+    let weights = fs::read("fixture/model.bin")
+        .context("the weights file to be mapped to the fixture directory")?;
+    let graph = wit::load(
+        &[xml, weights],
+        wit::GraphEncoding::Openvino,
+        wit::ExecutionTarget::Cpu,
+    )?;
+    let tensor = fs::read("fixture/tensor.bgr")
+        .context("the tensor file to be mapped to the fixture directory")?;
+    let results = wit::classify(
+        graph,
+        ("input", tensor),
+        "MobilenetV2/Predictions/Reshape_1",
+    )?;
+    let top_five = &sort_results(&results)[..5];
+    println!("found results, sorted top 5: {:?}", top_five);
+    Ok(())
+}

crates/test-programs/src/bin/nn_wit_image_classification_openvino_named.rs

@@ -0,0 +1,17 @@
+use anyhow::{Context, Result};
+use std::fs;
+use test_programs::nn::{sort_results, wit};
+
+pub fn main() -> Result<()> {
+    let graph = wit::load_by_name("fixtures")?;
+    let tensor: Vec<u8> = fs::read("fixture/tensor.bgr")
+        .context("the tensor file to be mapped to the fixture directory")?;
+    let results = wit::classify(
+        graph,
+        ("input", tensor),
+        "MobilenetV2/Predictions/Reshape_1",
+    )?;
+    let top_five = &sort_results(&results)[..5];
+    println!("found results, sorted top 5: {:?}", top_five);
+    Ok(())
+}

crates/test-programs/src/bin/nn_image_classification_named.rs → crates/test-programs/src/bin/nn_wit_image_classification_winml_named.rs

@@ -1,15 +1,14 @@
 use anyhow::{Context, Result};
 use std::fs;
-use test_programs::nn::{classify, sort_results};
-use wasi_nn::{ExecutionTarget, GraphBuilder, GraphEncoding};
+use test_programs::nn::{sort_results, wit};
 
 pub fn main() -> Result<()> {
-    let graph = GraphBuilder::new(GraphEncoding::Openvino, ExecutionTarget::CPU)
-        .build_from_cache("fixtures")?;
+    let graph = wit::load_by_name("mobilenet")?;
     let tensor = fs::read("fixture/tensor.bgr")
         .context("the tensor file to be mapped to the fixture directory")?;
-    let results = classify(graph, tensor)?;
+    let results = wit::classify(graph, ("input", tensor), "output")?;
     let top_five = &sort_results(&results)[..5];
     println!("found results, sorted top 5: {:?}", top_five);
+    assert_eq!(top_five[0].class_id(), 284);
     Ok(())
 }

crates/test-programs/src/bin/nn_witx_image_classification_onnx.rs

@@ -0,0 +1,22 @@
+use anyhow::{Context, Result};
+use std::fs;
+use test_programs::nn::{sort_results, witx};
+
+pub fn main() -> Result<()> {
+    let model = fs::read("fixture/model.onnx")
+        .context("the model file to be mapped to the fixture directory")?;
+    let graph = witx::load(
+        &[&model],
+        witx::GraphEncoding::Onnx,
+        witx::ExecutionTarget::CPU,
+    )?;
+    let tensor = fs::read("fixture/000000062808.rgb")
+        .context("the tensor file to be mapped to the fixture directory")?;
+    let results = witx::classify(graph, tensor)?;
+    let top_five = &sort_results(&results)[..5];
+    // 963 is "meat loaf, meatloaf."
+    // https://github.com/onnx/models/blob/bec48b6a70e5e9042c0badbaafefe4454e072d08/validated/vision/classification/synset.txt#L963
+    assert_eq!(top_five[0].class_id(), 963);
+    println!("found results, sorted top 5: {:?}", top_five);
+    Ok(())
+}

crates/test-programs/src/bin/nn_image_classification.rs → crates/test-programs/src/bin/nn_witx_image_classification_openvino.rs

@@ -1,18 +1,20 @@
 use anyhow::{Context, Result};
 use std::fs;
-use test_programs::nn::{classify, sort_results};
-use wasi_nn::{ExecutionTarget, GraphBuilder, GraphEncoding};
+use test_programs::nn::{sort_results, witx};
 
 pub fn main() -> Result<()> {
     let xml = fs::read("fixture/model.xml")
         .context("the model file to be mapped to the fixture directory")?;
     let weights = fs::read("fixture/model.bin")
         .context("the weights file to be mapped to the fixture directory")?;
-    let graph = GraphBuilder::new(GraphEncoding::Openvino, ExecutionTarget::CPU)
-        .build_from_bytes([&xml, &weights])?;
+    let graph = witx::load(
+        &[&xml, &weights],
+        witx::GraphEncoding::Openvino,
+        witx::ExecutionTarget::CPU,
+    )?;
     let tensor = fs::read("fixture/tensor.bgr")
         .context("the tensor file to be mapped to the fixture directory")?;
-    let results = classify(graph, tensor)?;
+    let results = witx::classify(graph, tensor)?;
     let top_five = &sort_results(&results)[..5];
     println!("found results, sorted top 5: {:?}", top_five);
     Ok(())

crates/test-programs/src/bin/nn_witx_image_classification_openvino_named.rs

@@ -0,0 +1,17 @@
+use anyhow::{Context, Result};
+use std::fs;
+use test_programs::nn::{sort_results, witx};
+
+pub fn main() -> Result<()> {
+    let graph = witx::load_by_name(
+        "fixtures",
+        witx::GraphEncoding::Openvino,
+        witx::ExecutionTarget::CPU,
+    )?;
+    let tensor: Vec<u8> = fs::read("fixture/tensor.bgr")
+        .context("the tensor file to be mapped to the fixture directory")?;
+    let results = witx::classify(graph, tensor)?;
+    let top_five = &sort_results(&results)[..5];
+    println!("found results, sorted top 5: {:?}", top_five);
+    Ok(())
+}

crates/test-programs/src/bin/nn_witx_image_classification_winml_named.rs

@@ -0,0 +1,18 @@
+use anyhow::{Context, Result};
+use std::fs;
+use test_programs::nn::{sort_results, witx};
+
+pub fn main() -> Result<()> {
+    let graph = witx::load_by_name(
+        "mobilenet",
+        witx::GraphEncoding::Onnx,
+        witx::ExecutionTarget::CPU,
+    )?;
+    let tensor = fs::read("fixture/tensor.bgr")
+        .context("the tensor file to be mapped to the fixture directory")?;
+    let results = witx::classify(graph, tensor)?;
+    let top_five = &sort_results(&results)[..5];
+    println!("found results, sorted top 5: {:?}", top_five);
+    assert_eq!(top_five[0].class_id(), 284);
+    Ok(())
+}