test: minimal nvvm.inline_ptx isolation test

tests/unit/test_ptx_minimal.py

@@ -0,0 +1,45 @@
+"""Minimal test: just nvvm.inline_ptx in isolation, no other CuTeDSL ops."""
+import torch
+import cutlass
+import cutlass.cute as cute
+import cutlass.torch as cutlass_torch
+from cutlass.cutlass_dsl import dsl_user_op, T
+from cutlass._mlir.dialects import nvvm
+from cutlass.cute.typing import Float32, Int32
+
+
+@dsl_user_op
+def f32_to_i32_rni(x: Float32, *, loc=None, ip=None) -> Int32:
+    result = nvvm.inline_ptx(
+        write_only_args=[T.i32()],
+        read_only_args=[Float32(x).ir_value(loc=loc, ip=ip)],
+        ptx_code="cvt.rni.s32.f32 $0, $1;",
+        loc=loc,
+        ip=ip,
+    )
+    return Int32(result)
+
+
+@cute.kernel
+def minimal_test_kernel(
+    input_f32: cute.Tensor,
+    output_i32: cute.Tensor,
+):
+    tidx, _, _ = cute.arch.thread_idx()
+    if tidx == cutlass.Int32(0):
+        x = cute.arch.load(input_f32.iterator, cutlass.Float32)
+        result = f32_to_i32_rni(x)
+        cute.arch.store(output_i32.iterator, result)
+
+
+if __name__ == "__main__":
+    x = torch.tensor([3.7], dtype=torch.float32, device='cuda')
+    out = torch.zeros(1, dtype=torch.int32, device='cuda')
+    xc = cutlass_torch.from_dlpack(x).mark_layout_dynamic(leading_dim=0)
+    oc = cutlass_torch.from_dlpack(out).mark_layout_dynamic(leading_dim=0)
+    
+    print("Compiling...")
+    compiled = cute.compile(minimal_test_kernel, xc, oc)
+    print("Running...")
+    compiled(xc, oc)
+    print(f'f32_to_i32_rni(3.7) = {out.item()} (expected 4)')