Add the MIGraphX rung for AMD GPUs

Measured on a Radeon RX 7900 XT against Arch's onnxruntime-rocm 1.29
(docs/inference.md §1.3): MIGraphX fp16 runs the detectors at 2.4–3.4 ms
against 10–58 ms on the CPU provider, the inpainter at 8 ms against 514,
with a 15–135 s compile per graph the first time and under a second from
its cache after. A compiling rung on TensorRT's terms, wired the same way.

The ROCm execution provider is gone (removed in ONNX Runtime 1.23), so the
AMD ladder is MIGraphX then the CPU, with no non-compiling rung between.

MIGraphX is registered through the runtime's generic key/value entry
point rather than ort's builder: 1.29 reads the legacy options struct for
its precision flags only, and the compiled-program cache directory
(`migraphx_model_cache_dir`) only travels the generic way. The provider's
cache key omits the precision, so f32 and fp16 programs get their own
directories. The probe fingerprint now includes the provider libraries
beside the runtime and the ROCm version, since a distribution's CPU and
ROCm builds are the same file at the same path.

`status().failed` reports only the rungs above the selection, so an AMD
desktop's About line says why MIGraphX won rather than that the NVIDIA
providers are not in the build.

Two examples: `ep_probe` times each provider cold and from cache, and
`ladder` drives `init` as the app does to watch the first-run sequence.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

core/dr-inference-engine/examples/ep_probe.rs

@@ -0,0 +1,207 @@
+//! Time each execution provider a runtime offers, on the models this
+//! repository ships — the measurement docs/inference.md §1 requires before a
+//! rung is added to §2's ladder.
+//!
+//!   DARKROOM_ORT_DIR=/usr/lib \
+//!     cargo run --release -p dr-inference-engine --features native,tract \
+//!     --example ep_probe -- models/face/scrfd_500m_640.onnx ...
+//!
+//! Prints one row per (model, provider): the median of timed runs after
+//! warm-ups, and the build time, which for a compiling provider is the
+//! number that decides whether it needs an engine cache. MIGraphX is built
+//! twice per precision — cold, then again from the cache it just wrote —
+//! so both numbers are on the page.
+//!
+//! The ROCm provider is not in the list: ONNX Runtime removed it in 1.23,
+//! and 1.29's `onnxruntime-rocm` ships `libonnxruntime_providers_migraphx.so`
+//! and nothing else for AMD.
+
+use std::path::{Path, PathBuf};
+use std::time::Instant;
+
+#[derive(Clone, Copy, PartialEq)]
+enum Ep {
+    Cpu,
+    MiGraphX,
+    MiGraphXFp16,
+}
+
+impl Ep {
+    fn label(self) -> &'static str {
+        match self {
+            Ep::Cpu => "CPU",
+            Ep::MiGraphX => "MIGraphX f32",
+            Ep::MiGraphXFp16 => "MIGraphX fp16",
+        }
+    }
+}
+
+fn build(ep: Ep, bytes: &[u8], threads: usize, cache: &Path) -> ort::Result<ort::session::Session> {
+    let mut b = ort::session::Session::builder()?.with_intra_threads(threads)?;
+    match ep {
+        Ep::Cpu => {}
+        Ep::MiGraphX => migraphx(&mut b, false, &cache.join("f32"))?,
+        Ep::MiGraphXFp16 => migraphx(&mut b, true, &cache.join("fp16"))?,
+    }
+    b.commit_from_memory(bytes)
+}
+
+/// Register MIGraphX through the generic key/value API. `ort`'s own
+/// builder fills the legacy `OrtMIGraphXProviderOptions`, which 1.29 reads
+/// for its precision flags and nothing else: the model cache directory —
+/// the difference between a 40 s load and a 0.3 s one — only travels this
+/// way. The cache key is the graph, the GPU and the MIGraphX version, not
+/// the precision, so each precision gets its own directory.
+fn migraphx(
+    b: &mut ort::session::builder::SessionBuilder,
+    fp16: bool,
+    cache: &Path,
+) -> ort::Result<()> {
+    use ort::AsPointer;
+    use std::ffi::CString;
+    std::fs::create_dir_all(cache).map_err(|e| ort::Error::new(e.to_string()))?;
+    let keys = [c"migraphx_fp16_enable", c"migraphx_model_cache_dir"];
+    let values = [
+        CString::new(if fp16 { "1" } else { "0" }).unwrap(),
+        CString::new(cache.to_string_lossy().as_bytes()).unwrap(),
+    ];
+    let key_ptrs: Vec<_> = keys.iter().map(|k| k.as_ptr()).collect();
+    let value_ptrs: Vec<_> = values.iter().map(|v| v.as_ptr()).collect();
+    // SAFETY: the documented C call, over arrays that outlive it; the
+    // runtime copies the strings into its own options map.
+    unsafe {
+        let status = (ort::api().SessionOptionsAppendExecutionProvider)(
+            b.ptr_mut(),
+            c"MIGraphX".as_ptr(),
+            key_ptrs.as_ptr(),
+            value_ptrs.as_ptr(),
+            keys.len(),
+        );
+        ort::Error::result_from_status(status)
+    }
+}
+
+/// 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()];
+    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 t = Instant::now();
+        let out = s.run(ort::inputs![input]).map_err(|e| e.to_string())?;
+        let _ = out[0]
+            .try_extract_tensor::<f32>()
+            .map_err(|e| e.to_string())?;
+        Ok(t.elapsed().as_secs_f64() * 1e3)
+    };
+    for _ in 0..warmups {
+        once(session)?;
+    }
+    let mut times = Vec::with_capacity(runs);
+    for _ in 0..runs {
+        times.push(once(session)?);
+    }
+    times.sort_by(|a, b| a.partial_cmp(b).unwrap());
+    Ok(times[times.len() / 2])
+}
+
+fn first_line(s: &str) -> String {
+    s.lines().next().unwrap_or("").chars().take(120).collect()
+}
+
+fn main() {
+    env_logger::Builder::from_env(env_logger::Env::default().default_filter_or("info")).init();
+
+    let models: Vec<PathBuf> = std::env::args_os().skip(1).map(PathBuf::from).collect();
+    if models.is_empty() {
+        eprintln!("usage: ep_probe MODEL.onnx [MODEL.onnx ...]");
+        std::process::exit(2);
+    }
+
+    dr_inference_engine::ensure_runtime();
+    let runtime = dr_inference_engine::status().runtime;
+    println!("runtime: {}", runtime.label());
+    if !runtime.is_native() {
+        println!("(tract: no provider to compare; set DARKROOM_ORT_DIR)");
+    }
+
+    let threads = std::thread::available_parallelism()
+        .map(|n| n.get().saturating_sub(2).max(1))
+        .unwrap_or(1);
+    println!("intra-op threads: {threads}");
+    let cache = std::env::temp_dir().join("darkroom-ep-probe");
+    let _ = std::fs::remove_dir_all(&cache);
+    println!("compiled-program cache: {}\n", cache.display());
+
+    println!(
+        "{:<28} {:<15} {:>10} {:>10}",
+        "model", "provider", "build s", "median ms"
+    );
+    for model in &models {
+        let bytes = match std::fs::read(model) {
+            Ok(b) => b,
+            Err(e) => {
+                println!("{:<28} read failed: {e}", name(model));
+                continue;
+            }
+        };
+        // A compiling provider is built twice: the second build reads the
+        // program the first wrote, and its time is what a launch after the
+        // first costs.
+        let plan = [
+            (Ep::Cpu, false),
+            (Ep::MiGraphX, false),
+            (Ep::MiGraphX, true),
+            (Ep::MiGraphXFp16, false),
+            (Ep::MiGraphXFp16, true),
+        ];
+        for (ep, cached) in plan {
+            let started = Instant::now();
+            match build(ep, &bytes, threads, &cache) {
+                Ok(mut session) => {
+                    let built = started.elapsed().as_secs_f64();
+                    match time(&mut session, 3, 15) {
+                        Ok(ms) => println!(
+                            "{:<28} {:<15} {:>10.1} {:>10.1}{}",
+                            name(model),
+                            ep.label(),
+                            built,
+                            ms,
+                            if cached { "  (from cache)" } else { "" }
+                        ),
+                        Err(e) => println!(
+                            "{:<28} {:<15} {:>10.1} {:>10}  {}",
+                            name(model),
+                            ep.label(),
+                            built,
+                            "ran ✗",
+                            first_line(&e)
+                        ),
+                    }
+                }
+                Err(e) => println!(
+                    "{:<28} {:<15} {:>21}  {}",
+                    name(model),
+                    ep.label(),
+                    "build ✗",
+                    first_line(&e.to_string())
+                ),
+            }
+        }
+        println!();
+    }
+}
+
+fn name(p: &Path) -> String {
+    p.file_name()
+        .unwrap_or(p.as_os_str())
+        .to_string_lossy()
+        .into_owned()
+}