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/ladder.rs

@@ -0,0 +1,100 @@
+//! Walk the ladder as the app does — probe, engines, then a session — and
+//! say what each step chose. The M5 check of docs/inference.md §6 without
+//! the app around it.
+//!
+//!   DARKROOM_ORT_DIR=/usr/lib \
+//!     cargo run --release -p dr-inference-engine --features native,tract \
+//!     --example ladder -- CACHE_DIR models/face/scrfd_500m_640.onnx [MODEL.onnx ...]
+//!
+//! Every model named is a `Detector` for the config's purposes, which is
+//! enough to see the rung taken, the engines compiled and a session land
+//! on it. Delete `CACHE_DIR` to see the first run again; keep it to see the
+//! second.
+
+use std::path::PathBuf;
+use std::time::{Duration, Instant};
+
+fn main() {
+    env_logger::Builder::from_env(env_logger::Env::default().default_filter_or("info")).init();
+    let mut args = std::env::args_os().skip(1).map(PathBuf::from);
+    let (Some(cache_dir), models) = (args.next(), args.collect::<Vec<_>>()) else {
+        eprintln!("usage: ladder CACHE_DIR MODEL.onnx [MODEL.onnx ...]");
+        std::process::exit(2);
+    };
+    if models.is_empty() {
+        eprintln!("usage: ladder CACHE_DIR MODEL.onnx [MODEL.onnx ...]");
+        std::process::exit(2);
+    }
+
+    let runtime_dirs: Vec<PathBuf> = std::env::var_os("DARKROOM_ORT_DIR")
+        .map(PathBuf::from)
+        .into_iter()
+        .collect();
+    let started = Instant::now();
+    dr_inference_engine::init(dr_inference_engine::Config {
+        runtime_dirs,
+        cache_dir: cache_dir.clone(),
+        models: models
+            .iter()
+            .map(|p| (dr_inference_engine::Role::Detector, p.clone()))
+            .collect(),
+        embedded: Vec::new(),
+        ceiling: None,
+        threads: 0,
+        decay: Duration::ZERO,
+    });
+
+    let mut last = String::new();
+    loop {
+        let s = dr_inference_engine::status();
+        let line = format!(
+            "{} · {} · engines {}/{}{}",
+            s.line(),
+            if s.probing {
+                "probing"
+            } else {
+                s.reason.as_str()
+            },
+            s.engines.0,
+            s.engines.1,
+            if s.failed.is_empty() {
+                String::new()
+            } else {
+                format!(
+                    " · tried {}",
+                    s.failed
+                        .iter()
+                        .map(|(r, why)| format!("{}: {why}", r.label()))
+                        .collect::<Vec<_>>()
+                        .join(" · ")
+                )
+            }
+        );
+        if line != last {
+            println!("{:>6.1} s  {line}", started.elapsed().as_secs_f64());
+            last = line;
+        }
+        if !s.probing && s.engines.0 >= s.engines.1 {
+            break;
+        }
+        std::thread::sleep(Duration::from_millis(500));
+    }
+
+    for path in &models {
+        let bytes = std::fs::read(path).expect("read model");
+        let t = Instant::now();
+        let model = dr_inference_engine::open(
+            dr_inference_engine::Role::Detector,
+            dr_inference_engine::Form::F32,
+            &bytes,
+        )
+        .expect("open model");
+        let acquired = model.acquire().expect("acquire session");
+        println!(
+            "{} on {} in {:.2} s",
+            path.file_name().unwrap().to_string_lossy(),
+            acquired.rung().label(),
+            t.elapsed().as_secs_f64()
+        );
+    }
+}