[torch] Supporting `torch.aten.mul.float` lowering to `arith` (#2833)

Simple missing scalar operation for multiply floats was missing.

lib/Conversion/TorchToArith/TorchToArith.cpp

@@ -443,9 +443,11 @@ public:
         typeConverter, context);
     patterns.add<ConvertAtenBinaryOp<AtenMulIntOp, arith::MulIOp>>(
         typeConverter, context);
-    target.addIllegalOp<AtenSubFloatOp>();
+    target.addIllegalOp<AtenSubFloatOp, AtenMulFloatOp>();
     patterns.add<ConvertAtenBinaryOp<AtenSubFloatOp, arith::SubFOp>>(
         typeConverter, context);
+    patterns.add<ConvertAtenBinaryOp<AtenMulFloatOp, arith::MulFOp>>(
+        typeConverter, context);
     target.addIllegalOp<AtenDivIntOp>();
     patterns.add<ConvertAtenDivIntOp>(typeConverter, context);
     target.addIllegalOp<AtenDivFloatOp>();

projects/pt1/e2e_testing/xfail_sets.py

@@ -100,6 +100,7 @@ TORCHDYNAMO_XFAIL_SET = {
 
     # START tests failing due to: torch._dynamo.exc.Unsupported: call_function BuiltinVariable(float) [TensorVariable()] {}
     'AtenSubFloatModule_basic',
+    'AtenMulFloatModule_basic',
     'BoolFloatFalseModule_basic',
     'BoolFloatTrueModule_basic',
     'CeilFloatModule_basic',
@@ -109,6 +110,7 @@ TORCHDYNAMO_XFAIL_SET = {
     'GtFloatIntModule_basic',
     'NeFloatIntModule_basic',
     'SubFloatModule_basic',
+    'MulFloatModule_basic',
     'TensorToFloatZeroRank_basic',
     'TensorToFloat_basic',
     # END tests failing due to: torch._dynamo.exc.Unsupported: call_function BuiltinVariable(float) [TensorVariable()] {}
@@ -1489,6 +1491,7 @@ LTC_XFAIL_SET = {
     "SliceStartEqEndModule_basic",
     "SqrtIntModule_basic",
     "SubFloatModule_basic",
+    "MulFloatModule_basic",
     "SubIntModule_basic",
     "TensorsStackPromoteDTypeModule_basic",
     "TensorToBoolZeroRank_basic",

projects/pt1/python/torch_mlir_e2e_test/test_suite/scalar.py

@@ -78,6 +78,28 @@ def SubFloatModule_basic(module, tu: TestUtils):
     module.forward(tu.rand().double(), tu.rand().double())
 
 
+# ==============================================================================
+
+class MulFloatModule(torch.nn.Module):
+
+    def __init__(self):
+        super().__init__()
+
+    @export
+    @annotate_args([
+        None,
+        ([], torch.float64, True),
+        ([], torch.float64, True),
+    ])
+    def forward(self, lhs, rhs):
+        return float(lhs) * float(rhs)
+
+
+@register_test_case(module_factory=lambda: MulFloatModule())
+def MulFloatModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand().double(), tu.rand().double())
+
+
 # ==============================================================================