From e9e4afe2c7930508c2cb399946ad8afb7d01b6c5 Mon Sep 17 00:00:00 2001
From: Andrew Brown <andrew.brown@intel.com>
Date: Tue, 13 Apr 2021 12:16:15 -0700
Subject: [PATCH] wasi-nn: use the MobileNet model instead of AlexNet

The MobileNet model is significantly smaller in size (14MB) than the AlexNet model (233MB); this change should reduce bandwidth used during CI.
---
 ci/run-wasi-nn-example.sh                         | 10 +++++-----
 .../examples/classification-example/src/main.rs   | 15 +++++++++------
 2 files changed, 14 insertions(+), 11 deletions(-)

diff --git a/ci/run-wasi-nn-example.sh b/ci/run-wasi-nn-example.sh
index e24ffa75ac..49c472c95e 100755
--- a/ci/run-wasi-nn-example.sh
+++ b/ci/run-wasi-nn-example.sh
@@ -7,7 +7,7 @@
 # executed with the Wasmtime CLI.
 set -e
 WASMTIME_DIR=$(dirname "$0" | xargs dirname)
-FIXTURE=https://github.com/intel/openvino-rs/raw/main/crates/openvino/tests/fixtures/alexnet
+FIXTURE=https://github.com/intel/openvino-rs/raw/main/crates/openvino/tests/fixtures/mobilenet
 if [ -z "${1+x}" ]; then
     # If no temporary directory is specified, create one.
     TMP_DIR=$(mktemp -d -t ci-XXXXXXXXXX)
@@ -26,9 +26,9 @@ source /opt/intel/openvino/bin/setupvars.sh
 OPENVINO_INSTALL_DIR=/opt/intel/openvino cargo build -p wasmtime-cli --features wasi-nn
 
 # Download all necessary test fixtures to the temporary directory.
-wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/alexnet.bin
-wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/alexnet.xml
-wget --no-clobber --directory-prefix=$TMP_DIR $FIXTURE/tensor-1x3x227x227-f32.bgr
+wget --no-clobber $FIXTURE/mobilenet.bin --output-document=$TMP_DIR/model.bin
+wget --no-clobber $FIXTURE/mobilenet.xml --output-document=$TMP_DIR/model.xml
+wget --no-clobber $FIXTURE/tensor-1x224x224x3-f32.bgr --output-document=$TMP_DIR/tensor.bgr
 
 # Now build an example that uses the wasi-nn API.
 pushd $WASMTIME_DIR/crates/wasi-nn/examples/classification-example
@@ -42,4 +42,4 @@ OPENVINO_INSTALL_DIR=/opt/intel/openvino cargo run --features wasi-nn -- run --m
 # Clean up the temporary directory only if it was not specified (users may want to keep the directory around).
 if [[ $REMOVE_TMP_DIR -eq 1 ]]; then
     rm -rf $TMP_DIR
-fi
\ No newline at end of file
+fi
diff --git a/crates/wasi-nn/examples/classification-example/src/main.rs b/crates/wasi-nn/examples/classification-example/src/main.rs
index 5f0a7f4e5a..6b415fb96b 100644
--- a/crates/wasi-nn/examples/classification-example/src/main.rs
+++ b/crates/wasi-nn/examples/classification-example/src/main.rs
@@ -3,10 +3,10 @@ use std::fs;
 use wasi_nn;
 
 pub fn main() {
-    let xml = fs::read_to_string("fixture/alexnet.xml").unwrap();
+    let xml = fs::read_to_string("fixture/model.xml").unwrap();
     println!("Read graph XML, first 50 characters: {}", &xml[..50]);
 
-    let weights = fs::read("fixture/alexnet.bin").unwrap();
+    let weights = fs::read("fixture/model.bin").unwrap();
     println!("Read graph weights, size in bytes: {}", weights.len());
 
     let graph = unsafe {
@@ -24,10 +24,10 @@ pub fn main() {
 
     // Load a tensor that precisely matches the graph input tensor (see
     // `fixture/frozen_inference_graph.xml`).
-    let tensor_data = fs::read("fixture/tensor-1x3x227x227-f32.bgr").unwrap();
+    let tensor_data = fs::read("fixture/tensor.bgr").unwrap();
     println!("Read input tensor, size in bytes: {}", tensor_data.len());
     let tensor = wasi_nn::Tensor {
-        dimensions: &[1, 3, 227, 227],
+        dimensions: &[1, 3, 224, 224],
         r#type: wasi_nn::TENSOR_TYPE_F32,
         data: &tensor_data,
     };
@@ -42,7 +42,7 @@ pub fn main() {
     println!("Executed graph inference");
 
     // Retrieve the output.
-    let mut output_buffer = vec![0f32; 1000];
+    let mut output_buffer = vec![0f32; 1001];
     unsafe {
         wasi_nn::get_output(
             context,
@@ -60,10 +60,13 @@ pub fn main() {
 
 // Sort the buffer of probabilities. The graph places the match probability for each class at the
 // index for that class (e.g. the probability of class 42 is placed at buffer[42]). Here we convert
-// to a wrapping InferenceResult and sort the results.
+// to a wrapping InferenceResult and sort the results. It is unclear why the MobileNet output
+// indices are "off by one" but the `.skip(1)` below seems necessary to get results that make sense
+// (e.g. 763 = "revolver" vs 762 = "restaurant")
 fn sort_results(buffer: &[f32]) -> Vec<InferenceResult> {
     let mut results: Vec<InferenceResult> = buffer
         .iter()
+        .skip(1)
         .enumerate()
         .map(|(c, p)| InferenceResult(c, *p))
         .collect();