[StableHlo] Fix AtenWhereSelfOp convert rule (#2093)

* fix whereself convert rule

* use int to test promotion

* add dynamo failing test

---------

Co-authored-by: zhekun.zhang <zhekun.zhang@bytedance.com>

e2e_testing/xfail_sets.py

@@ -54,6 +54,8 @@ TORCHDYNAMO_XFAIL_SET = {
     "ElementwiseWhereScalarModule_basic",
     "ElementwiseWhereScalarOtherModule_basic",
     "ElementwiseWhereScalarSelfModule_basic",
+    "ElementwiseWhereScalarOtherStaticModule_basic",
+    "ElementwiseWhereScalarSelfStaticModule_basic",
     # %7 = torch.operator "aten._index_put_impl_.hacked_twin"(%1, %6, %5, %true, %false) : (!torch.tensor<*,f32>, !torch.list<tensor>, !torch.tensor<*,f32>, !torch.bool, !torch.bool) -> !torch.tensor
     "IndexPutImpl1DFloatAccumulateModule_basic",
     "IndexPutImpl1DFloatNonAccumulateModule_basic",
@@ -267,6 +269,8 @@ STABLEHLO_PASS_SET = {
     "ElementwiseAtenLogicalOrOpPromoteBroadcastStaticShapeModule_basic",
     "ElementwiseAtenLogicalXorOpPromoteBroadcastStaticShapeModule_basic",
     "ElementwiseAtenWhereSelfModule_basic",
+    "ElementwiseWhereScalarOtherStaticModule_basic",
+    "ElementwiseWhereScalarSelfStaticModule_basic",
     "ElementwiseBitwiseAndStaticShapeModule_basic",
     "ElementwiseBitwiseNotInt64Module_basic",
     "ElementwiseBitwiseNotInt32Module_basic",

lib/Conversion/TorchToStablehlo/Basic.cpp

@@ -606,6 +606,12 @@ LogicalResult ConvertAtenOp<AtenWhereSelfOp>::matchAndRewrite(
   Value cond = adaptor.getCondition();
   Value other = adaptor.getOther();
 
+  auto outType =
+      getTypeConverter()->convertType(op.getType()).cast<RankedTensorType>();
+  // promote self and other types
+  self = hlo::promoteType(rewriter, self, outType);
+  other = hlo::promoteType(rewriter, other, outType);
+
   if (failed(
           broadcastRanks(rewriter, op, self, cond, options.dimSizeIndexBits)))
     return op.emitError("failed broadcast self and condition ranks");

python/torch_mlir_e2e_test/test_suite/elementwise.py

@@ -227,6 +227,29 @@ def ElementwiseWhereScalarOtherModule_basic(module, tu: TestUtils):
 # ==============================================================================
 
 
+class ElementwiseWhereScalarOtherStaticModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([3, 4, 5], torch.float64, True),
+        ([4, 5], torch.float64, True),
+    ])
+    def forward(self, a, b):
+        return torch.where(a > 0.5, b, 8)
+
+
+@register_test_case(module_factory=lambda: ElementwiseWhereScalarOtherStaticModule())
+def ElementwiseWhereScalarOtherStaticModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(3, 4, 5).double(), tu.rand(4, 5).double())
+
+
+# ==============================================================================
+
+
 class ElementwiseWhereScalarSelfModule(torch.nn.Module):
 
     def __init__(self):
@@ -246,6 +269,28 @@ class ElementwiseWhereScalarSelfModule(torch.nn.Module):
 def ElementwiseWhereScalarSelfModule_basic(module, tu: TestUtils):
     module.forward(tu.rand(3, 4, 5).double(), tu.rand(4, 5).double())
 
+# ==============================================================================
+
+
+class ElementwiseWhereScalarSelfStaticModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([3, 4, 5], torch.float64, True),
+        ([4, 5], torch.float64, True),
+    ])
+    def forward(self, a, b):
+        return torch.where(a > 0.5, 4.0, b)
+
+
+@register_test_case(module_factory=lambda: ElementwiseWhereScalarSelfStaticModule())
+def ElementwiseWhereScalarSelfStaticModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(3, 4, 5).double(), tu.rand(4, 5).double())
+
 
 # ==============================================================================