dtourolle/DarkRoom
1
0
Fork 0
Code Issues 39 Pull Requests Actions Packages Projects Releases 20 Wiki Activity

Feed every input in ep_probe

Browse Source 
The denoiser takes `mosaic` and `sigma`; with only the first fed, every
provider reported the same failure and the model went unmeasured.
This commit is contained in:
dtourolle
2026-10-04 21:00:15 -04:00
parent ef71bb3289
commit 0291b80672
1 changed files with 21 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files
core/dr-inference-engine/examples/ep_probe.rs
+21 -11
View File
@@ -181,19 +181,29 @@ fn migraphx(
/// Median of `runs` timed runs over zeros, in milliseconds, after warm-ups.
fn time(session: &mut ort::session::Session, warmups: usize, runs: usize) -> Result<f64, String> {
let shape: Vec<usize> = session.inputs()[0]
.dtype()
.tensor_shape()
.ok_or("input is not a tensor")?
.iter()
.map(|&d| if d > 0 { d as usize } else { 1 })
.collect();
let zeros = vec![0f32; shape.iter().product()];
// Zeros for every input, not just the first: the denoiser takes
// `mosaic` and `sigma`. A dynamic dimension is read as 1.
let mut inputs = Vec::new();
for input in session.inputs() {
let shape: Vec<usize> = input
.dtype()
.tensor_shape()
.ok_or("input is not a tensor")?
.iter()
.map(|&d| if d > 0 { d as usize } else { 1 })
.collect();
let zeros = vec![0f32; shape.iter().product()];
inputs.push((input.name().to_string(), shape, zeros));
}
let once = |s: &mut ort::session::Session| -> Result<f64, String> {
let input = ort::value::Tensor::from_array((shape.clone(), zeros.clone()))
.map_err(|e| e.to_string())?;
let mut values = Vec::with_capacity(inputs.len());
for (name, shape, zeros) in &inputs {
let value = ort::value::Tensor::from_array((shape.clone(), zeros.clone()))
.map_err(|e| e.to_string())?;
values.push((name.clone(), ort::session::SessionInputValue::from(value)));
}
let t = Instant::now();
let out = s.run(ort::inputs![input]).map_err(|e| e.to_string())?;
let out = s.run(values).map_err(|e| e.to_string())?;
let _ = out[0]
.try_extract_tensor::<f32>()
.map_err(|e| e.to_string())?;