feat: make the harness backend-agnostic

Everything about which accelerator a run targets was previously spelled CUDA:
device discovery went through nvidia-smi, pinning through CUDA_VISIBLE_DEVICES,
the vendor guard only recognised NVIDIA, and the -p plugin list was hardcoded in
run_pytest.sh with no way to drop the CUDA-only members. Running the same
operator corpus on another vendor's device therefore meant editing the drivers.

The selection now hangs off one ZL_BACKEND variable (cuda/musa/rocm/ascend, with
the usual aliases):

- backends/ owns per-backend device enumeration, visibility env keys and
  capability flags, so nothing above it names a vendor;
- plugin_plan.py derives the -p list from those capabilities instead of a
  hardcoded array, which is what lets a non-CUDA run omit the graph-capture and
  cluster-fix plugins rather than watch them fail;
- _timing_plugin selects the timer from the same capabilities: CUDA keeps
  graph capture with its per-shape fallback, other backends stay on upstream
  do_bench and record timer=direct, because capture-then-fallback on a device
  without graph support only produces noise;
- _device_setup_plugin replaces the NVIDIA-only vendor guard;
- providers/flaggems.py resolves the pytest node, so a caller may pass TEST_NODE
  directly instead of the OP/OP_FILE pair, and SHAPE_MODE=upstream can defer to
  FlagGems' own core_shapes;
- _run_identity.py writes run_identity.json next to each run, recording backend,
  device, timer, autotune mode and the resolved test node. Two runs whose
  calibers differ are otherwise indistinguishable after the fact.

run_batch gains --backend and --devices (--gpus kept as an alias) and carries
backend/device/timer into ops_status.csv. test_backends.py covers the registry,
alias resolution, visibility env and plugin planning.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

_cudagraph_plugin.py

@@ -1,7 +1,9 @@
 """pytest plugin: swap `triton.testing.do_bench` for cudagraph-based timing.
 
-Loaded via `-p _cudagraph_plugin` in run_pytest.sh's PLUGINS list (comment that
-line out to time with plain do_bench). Monkey-patches do_bench →
+Invoked by `_timing_plugin` when the active backend declares
+`supports_cuda_graph` (CUDA only). Do not put this module on the default `-p`
+list for MUSA/ROCm/Ascend: those backends must start on plain do_bench, not
+attempt capture-then-fallback. Monkey-patches do_bench →
 do_bench_cudagraph (kernel-only latency) at session configure, after Triton is
 loaded but before any benchmark calls it. Kernels that can't be graph-captured
 fall back to plain do_bench and print a BENCHMARK_DIRECT_NO_CUDAGRAPH marker
@@ -167,6 +169,17 @@ def _patched_do_bench(fn, warmup=25, rep=100, grad_to_none=None,
 
 def pytest_configure(config):
     from _term_style import tag
+    try:
+        from backends import get_backend
+        if not get_backend().supports_cuda_graph:
+            print(f"{tag('[cudagraph-plugin]')} skipped: backend "
+                  f"{get_backend().name!r} does not support CUDA Graph",
+                  file=sys.stderr, flush=True)
+            return
+    except Exception as exc:
+        print(f"{tag('[cudagraph-plugin]')} backend probe failed ({exc}); "
+              "not patching do_bench", file=sys.stderr, flush=True)
+        return
     _tt.do_bench = _patched_do_bench
     print(f"{tag('[cudagraph-plugin]')} triton.testing.do_bench → do_bench_cudagraph",
           file=sys.stderr, flush=True)