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chore: remove now-useless benches

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Carson M.
2025-01-02 13:45:41 -06:00
parent 3947043493
commit 5f85c3c196
3 changed files with 1 additions and 80 deletions
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8
.deepsource.toml
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@@ -1,8 +0,0 @@
version = 1
[[analyzers]]
name = "rust"
enabled = true
[analyzers.meta]
msrv = "stable"

6
Cargo.toml
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@@ -39,7 +39,7 @@ authors = [
"pyke.io <contact@pyke.io>",
"Nicolas Bigaouette <nbigaouette@gmail.com>"
]
include = [ "src/", "benches/", "LICENSE-APACHE", "LICENSE-MIT", "README.md" ]
include = [ "src/", "LICENSE-APACHE", "LICENSE-MIT", "README.md" ]
[profile.release]
opt-level = 3
@@ -101,7 +101,3 @@ tracing-subscriber = { version = "0.3", default-features = false, features = [ "
glassbench = "0.4"
tokio = { version = "1.36", features = [ "test-util" ] }
tokio-test = "0.4.3"
[[bench]]
name = "squeezenet"
harness = false

67
benches/squeezenet.rs
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@@ -1,67 +0,0 @@
use std::{path::Path, sync::Arc};
use glassbench::{Bench, pretend_used};
use image::{ImageBuffer, Pixel, Rgb, imageops::FilterType};
use ndarray::{Array4, s};
use ort::{
session::{Session, builder::GraphOptimizationLevel},
value::TensorRef
};
fn load_squeezenet_data() -> ort::Result<(Session, Array4<f32>)> {
const IMAGE_TO_LOAD: &str = "mushroom.png";
ort::init().with_name("integration_test").commit()?;
let session = Session::builder()?
.with_optimization_level(GraphOptimizationLevel::Level1)?
.with_intra_threads(1)?
.commit_from_url("https://parcel.pyke.io/v2/cdn/assetdelivery/ortrsv2/ex_models/squeezenet.onnx")
.expect("Could not download model from file");
let input0_shape: &Vec<i64> = session.inputs[0].input_type.tensor_dimensions().expect("input0 to be a tensor type");
let image_buffer: ImageBuffer<Rgb<u8>, Vec<u8>> = image::open(Path::new(env!("CARGO_MANIFEST_DIR")).join("tests").join("data").join(IMAGE_TO_LOAD))
.unwrap()
.resize(input0_shape[2] as u32, input0_shape[3] as u32, FilterType::Nearest)
.to_rgb8();
let mut array = ndarray::Array::from_shape_fn((1, 3, 224, 224), |(_, c, j, i)| {
let pixel = image_buffer.get_pixel(i as u32, j as u32);
let channels = pixel.channels();
(channels[c] as f32) / 255.0
});
let mean = [0.485, 0.456, 0.406];
let std = [0.229, 0.224, 0.225];
for c in 0..3 {
let mut channel_array = array.slice_mut(s![0, c, .., ..]);
channel_array -= mean[c];
channel_array /= std[c];
}
Ok((session, array))
}
fn bench_squeezenet(bench: &mut Bench) {
let (session, data) = load_squeezenet_data().unwrap();
bench.task("ArrayView", |task| {
task.iter(|| {
pretend_used(session.run(ort::inputs![TensorRef::from_array_view(&data).unwrap()]).unwrap());
})
});
let raw = Arc::new(data.as_standard_layout().as_slice().unwrap().to_owned().into_boxed_slice());
let shape: Vec<i64> = data.shape().iter().map(|c| *c as _).collect();
bench.task("Raw data", |task| {
task.iter(|| {
pretend_used(
session
.run(ort::inputs![TensorRef::from_array_view((shape.clone(), Arc::clone(&raw))).unwrap()])
.unwrap()
);
})
});
}
glassbench::glassbench!("SqueezeNet", bench_squeezenet,);