[BugFix] Align tir.round to ties-to-even across all backends

include/tvm/tirx/op.h

@@ -654,19 +654,25 @@ TVM_DLL PrimExpr floor(PrimExpr x, Span span = Span());
 TVM_DLL PrimExpr ceil(PrimExpr x, Span span = Span());
 
 /*!
- * \brief Calculate round(x)
+ * \brief Round x to the nearest integer, ties to even.
+ *
+ * Uses IEEE 754 default rounding mode (ties-to-even / banker's rounding).
+ * Constant-folding and all backends consistently use std::nearbyint semantics.
+ *
  * \param x The input expression.
  * \param span The location of this operation in the source.
  * \return The result expression.
  */
 TVM_DLL PrimExpr round(PrimExpr x, Span span = Span());
 
 /*!
- * \brief Calculates std::nearbyint(x)
+ * \brief Round x to the nearest integer, ties to even.
+ *
+ * Equivalent to round(). Both use IEEE 754 default rounding mode (ties-to-even).
+ *
  * \param x The input expression.
  * \param span The location of this operation in the source.
  * \return The result expression.
- * This is a faster alternate to round.
  */
 TVM_DLL PrimExpr nearbyint(PrimExpr x, Span span = Span());
 

python/tvm/topi/testing/roi_pool_python.py

@@ -36,10 +36,12 @@ def roi_pool_nchw_python(a_np, rois_np, pooled_size, spatial_scale):
     for i in range(num_roi):
         roi = rois_np[i]
         batch_index = int(roi[0])
-        roi_start_w = round(roi[1] * spatial_scale)
-        roi_start_h = round(roi[2] * spatial_scale)
-        roi_end_w = round(roi[3] * spatial_scale)
-        roi_end_h = round(roi[4] * spatial_scale)
+        # Use ties-away-from-zero rounding to match ONNX runtime (std::round semantics).
+        # Python's built-in round() uses ties-to-even, so use floor(x + 0.5) explicitly.
+        roi_start_w = math.floor(roi[1] * spatial_scale + 0.5)
+        roi_start_h = math.floor(roi[2] * spatial_scale + 0.5)
+        roi_end_w = math.floor(roi[3] * spatial_scale + 0.5)
+        roi_end_h = math.floor(roi[4] * spatial_scale + 0.5)
         roi_h = max(roi_end_h - roi_start_h + 1, 1)
         roi_w = max(roi_end_w - roi_start_w + 1, 1)
 

python/tvm/topi/vision/roi_pool.py

@@ -36,12 +36,19 @@ def roi_pool_nchw(data, rois, pooled_size, spatial_scale):
 
     neg_inf = tvm.tirx.const(float("-inf"), data.dtype)
 
+    def _round_away(x):
+        # ONNX MaxRoiPool spec uses ties-away-from-zero rounding for coordinate
+        # mapping (matching std::round semantics in the reference implementation).
+        # Use floor(x + 0.5) to be explicit and independent of tir.round semantics.
+        half = tvm.tirx.const(0.5, roi_dtype)
+        return te.floor(x + half)
+
     def _bin_bounds(i, ph, pw):
         roi = rois[i]
-        roi_start_w = te.round(roi[1] * spatial_scale).astype("int32")
-        roi_start_h = te.round(roi[2] * spatial_scale).astype("int32")
-        roi_end_w = te.round(roi[3] * spatial_scale).astype("int32")
-        roi_end_h = te.round(roi[4] * spatial_scale).astype("int32")
+        roi_start_w = _round_away(roi[1] * spatial_scale).astype("int32")
+        roi_start_h = _round_away(roi[2] * spatial_scale).astype("int32")
+        roi_end_w = _round_away(roi[3] * spatial_scale).astype("int32")
+        roi_end_h = _round_away(roi[4] * spatial_scale).astype("int32")
 
         roi_h = te.max(roi_end_h - roi_start_h + 1, tvm.tirx.const(1, "int32"))
         roi_w = te.max(roi_end_w - roi_start_w + 1, tvm.tirx.const(1, "int32"))

src/target/llvm/intrin_rule_hexagon.cc

@@ -93,7 +93,7 @@ TVM_REGISTER_OP("tirx.fabs")
 
 TVM_REGISTER_OP("tirx.round")
     .set_attr<FLowerIntrinsic>("hexagon.FLowerIntrinsic",
-                               DispatchLLVMPureIntrin<::llvm::Intrinsic::round, 1>);
+                               DispatchLLVMPureIntrin<::llvm::Intrinsic::nearbyint, 1>);
 
 TVM_REGISTER_OP("tirx.ctpop")
     .set_attr<FLowerIntrinsic>("hexagon.FLowerIntrinsic",

src/target/llvm/intrin_rule_llvm.cc

@@ -90,7 +90,7 @@ TVM_REGISTER_OP("tirx.fabs")
 
 TVM_REGISTER_OP("tirx.round")
     .set_attr<FLowerIntrinsic>("llvm.FLowerIntrinsic",
-                               DispatchLLVMPureIntrin<::llvm::Intrinsic::round, 1>);
+                               DispatchLLVMPureIntrin<::llvm::Intrinsic::nearbyint, 1>);
 
 TVM_REGISTER_OP("tirx.nearbyint")
     .set_attr<FLowerIntrinsic>("llvm.FLowerIntrinsic",

src/target/llvm/intrin_rule_nvptx.cc

@@ -66,7 +66,15 @@ TVM_REGISTER_OP("tirx.ceil")
     .set_attr<FLowerIntrinsic>("nvptx.FLowerIntrinsic", DispatchPureExternLibDevice);
 
 TVM_REGISTER_OP("tirx.round")
-    .set_attr<FLowerIntrinsic>("nvptx.FLowerIntrinsic", DispatchPureExternLibDevice);
+    .set_attr<FLowerIntrinsic>("nvptx.FLowerIntrinsic", [](const PrimExpr& e) -> PrimExpr {
+      // Redirect to nearbyint (ties-to-even) to match constant-folding semantics.
+      using namespace tirx;
+      const CallNode* call = e.as<CallNode>();
+      TVM_FFI_ICHECK(call != nullptr);
+      auto nearbyint_op = Op::Get("tirx.nearbyint");
+      auto new_call = Call(call->dtype, nearbyint_op, call->args);
+      return DispatchPureExternLibDevice(new_call);
+    });
 
 TVM_REGISTER_OP("tirx.nearbyint")
     .set_attr<FLowerIntrinsic>("nvptx.FLowerIntrinsic", DispatchPureExternLibDevice);

src/target/llvm/intrin_rule_rocm.cc

@@ -132,7 +132,7 @@ TVM_REGISTER_OP("tirx.ceil")
 
 TVM_REGISTER_OP("tirx.round")
     .set_attr<FLowerIntrinsic>("rocm.FLowerIntrinsic",
-                               DispatchLLVMPureIntrin<::llvm::Intrinsic::round, 1>);
+                               DispatchLLVMPureIntrin<::llvm::Intrinsic::nearbyint, 1>);
 
 TVM_REGISTER_OP("tirx.nearbyint")
     .set_attr<FLowerIntrinsic>("rocm.FLowerIntrinsic",

src/target/source/codegen_opencl.cc

@@ -526,7 +526,7 @@ void CodeGenOpenCL::VisitExpr_(const CallNode* op, std::ostream& os) {
       this->PrintCallExtern(GetType(ffi::GetRef<PrimExpr>(op)), "atomic_add_float_emu", op->args,
                             true, os);
     } else if (func->value == "nearbyint") {
-      this->PrintCallExtern(GetType(ffi::GetRef<PrimExpr>(op)), "round", op->args, true, os);
+      this->PrintCallExtern(GetType(ffi::GetRef<PrimExpr>(op)), "rint", op->args, true, os);
     } else {
       if (func->value == "atomic_add") {
         enable_atomics_ = true;

src/target/source/intrin_rule_cuda.cc

@@ -37,8 +37,11 @@ struct CUDAMath {
     if (t.is_float()) {
       switch (t.bits()) {
         case 64:
+          // Use nearbyint (ties-to-even) for round to match constant-folding semantics.
+          if (name == "round") return "nearbyint";
           return name;
         case 32:
+          if (name == "round") return "nearbyintf";
           return name + 'f';
         case 16: {
           if (name == "fabs") {

src/target/source/intrin_rule_metal.cc

@@ -68,7 +68,16 @@ TVM_REGISTER_OP("tirx.fabs")
     .set_attr<FLowerIntrinsic>("metal.FLowerIntrinsic", DispatchPureExtern<Direct>);
 
 TVM_REGISTER_OP("tirx.round")
-    .set_attr<FLowerIntrinsic>("metal.FLowerIntrinsic", DispatchPureExtern<Direct>);
+    .set_attr<FLowerIntrinsic>("metal.FLowerIntrinsic", [](const PrimExpr& e) -> PrimExpr {
+      // Metal's rint() uses ties-to-even, matching constant-folding semantics.
+      const tirx::CallNode* call = e.as<tirx::CallNode>();
+      TVM_FFI_ICHECK(call != nullptr);
+      ffi::Array<PrimExpr> new_args = {tirx::StringImm("rint")};
+      for (auto arg : call->args) {
+        new_args.push_back(arg);
+      }
+      return tirx::Call(call->dtype, tirx::builtin::call_pure_extern(), new_args);
+    });
 
 TVM_REGISTER_OP("tirx.nearbyint")
     .set_attr<FLowerIntrinsic>("metal.FLowerIntrinsic", DispatchPureExtern<Direct>);

src/target/source/intrin_rule_opencl.cc

@@ -47,7 +47,16 @@ TVM_REGISTER_OP("tirx.fabs")
     .set_attr<FLowerIntrinsic>("opencl.FLowerIntrinsic", DispatchPureExtern<Direct>);
 
 TVM_REGISTER_OP("tirx.round")
-    .set_attr<FLowerIntrinsic>("opencl.FLowerIntrinsic", DispatchPureExtern<Direct>);
+    .set_attr<FLowerIntrinsic>("opencl.FLowerIntrinsic", [](const PrimExpr& e) -> PrimExpr {
+      // OpenCL's rint() uses ties-to-even, matching constant-folding semantics.
+      const tirx::CallNode* call = e.as<tirx::CallNode>();
+      TVM_FFI_ICHECK(call != nullptr);
+      ffi::Array<PrimExpr> new_args = {tirx::StringImm("rint")};
+      for (auto arg : call->args) {
+        new_args.push_back(arg);
+      }
+      return tirx::Call(call->dtype, tirx::builtin::call_pure_extern(), new_args);
+    });
 
 TVM_REGISTER_OP("tirx.nearbyint")
     .set_attr<FLowerIntrinsic>("opencl.FLowerIntrinsic", DispatchPureExtern<Direct>);

src/target/spirv/intrin_rule_spirv.cc

@@ -68,10 +68,12 @@ TVM_REGISTER_OP("tirx.ceil")
     .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic", DispatchGLSLPureIntrin<GLSLstd450Ceil>);
 
 TVM_REGISTER_OP("tirx.round")
-    .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic", DispatchGLSLPureIntrin<GLSLstd450Round>);
+    .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic",
+                               DispatchGLSLPureIntrin<GLSLstd450RoundEven>);
 
 TVM_REGISTER_OP("tirx.nearbyint")
-    .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic", DispatchGLSLPureIntrin<GLSLstd450Round>);
+    .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic",
+                               DispatchGLSLPureIntrin<GLSLstd450RoundEven>);
 
 TVM_REGISTER_OP("tirx.trunc")
     .set_attr<FLowerIntrinsic>("vulkan.FLowerIntrinsic", DispatchGLSLPureIntrin<GLSLstd450Trunc>);

tests/python/tirx-base/test_tir_intrin.py

@@ -56,6 +56,27 @@ def test_nearbyint():
     tvm.testing.assert_allclose(a_rounded.numpy(), np.rint(a.numpy()))
 
 
+def test_round_ties_to_even():
+    """Test that tir.round uses ties-to-even (banker's rounding) semantics."""
+    m = te.var("m")
+    A = te.placeholder((m,), name="A")
+    A_rounded = te.compute((m,), lambda *i: tvm.tirx.round(A(*i)), name="A")
+
+    mod = te.create_prim_func([A, A_rounded])
+    sch = tvm.s_tir.Schedule(mod)
+    func = tvm.compile(sch.mod, target="llvm")
+
+    dev = tvm.cpu(0)
+    # Midpoint values where ties-to-even and ties-away differ
+    test_values = np.array([0.5, 1.5, 2.5, 3.5, -0.5, -1.5, -2.5, -3.5], dtype="float32")
+    expected = np.array([0.0, 2.0, 2.0, 4.0, 0.0, -2.0, -2.0, -4.0], dtype="float32")
+
+    a = tvm.runtime.tensor(test_values, dev)
+    a_rounded = tvm.runtime.tensor(np.zeros(len(test_values), dtype="float32"), dev)
+    func(a, a_rounded)
+    tvm.testing.assert_allclose(a_rounded.numpy(), expected)
+
+
 def test_round_intrinsics_on_int():
     i = tvm.tirx.Var("i", "int32")
     for op in [tvm.tirx.round, tvm.tirx.trunc, tvm.tirx.ceil, tvm.tirx.floor, tvm.tirx.nearbyint]: