[FxImporter] Replace local_scalar_dense in fx_importer (#3180)

projects/pt1/e2e_testing/xfail_sets.py

@@ -387,7 +387,6 @@ TORCHDYNAMO_CRASHING_SET = {
 }
 
 FX_IMPORT_XFAIL_SET = {
-    'AddIntModule_basic',
     'AllBoolFalseModule_basic',
     'AllBoolTrueModule_basic',
     'AnyBoolFalseModule_basic',
@@ -399,10 +398,7 @@ FX_IMPORT_XFAIL_SET = {
     'AtenIntBoolOpConstFalseModule_basic',
     'AtenIntBoolOpConstTrueModule_basic',
     'AtenIntBoolOpModule_basic',
-    'AtenIntTensorByteDtypeModule_basic',
-    'AtenIntTensorCharDtypeModule_basic',
     'AtenItemFpOpModule_basic',
-    'AtenItemIntOpModule_basic',
     'AtenMatmulQMixedSigni8Transpose_basic',
     'AtenMatmulQMixedSigni8_basic',
     'AtenMatmulQint8MV_basic',
@@ -465,7 +461,6 @@ FX_IMPORT_XFAIL_SET = {
     'MaxPool3dStaticCeilModeTrueModule_basic',
     'MaxPool3dStaticModule_basic',
     'MulFloatModule_basic',
-    'MulIntModule_basic',
     'NativeGroupNormBackwardModule_basic',
     'NeFloatIntModule_basic',
     'NeIntModule_basic',
@@ -496,9 +491,6 @@ FX_IMPORT_XFAIL_SET = {
     'RsubInt0d_NumToTensor_Module_basic',
     'ScalarConstantTupleModule_basic',
     'ScalarImplicitFloatModule_basic',
-    'ScalarImplicitIntModule_basic',
-    'ScatterValueFloatModule_basic',
-    'ScatterValueIntModule_basic',
     'SortIntListReverse_basic',
     'SortIntList_basic',
     'SplitDimDynamicModule_basic',
@@ -506,14 +498,11 @@ FX_IMPORT_XFAIL_SET = {
     'SqrtIntConstantModule_basic',
     'SqrtIntModule_basic',
     'SubFloatModule_basic',
-    'SubIntModule_basic',
     'TModuleRank0_basic',
     'TensorToBoolZeroRank_basic',
     'TensorToBool_basic',
     'TensorToFloatZeroRank_basic',
     'TensorToFloat_basic',
-    'TensorToIntZeroRank_basic',
-    'TensorToInt_basic',
     'TestMultipleTensorAndPrimitiveTypesReturn_basic',
     'ThresholdBackward2dMixedModule_basic',
     'TorchPrimLoopForLikeModule_basic',

python/torch_mlir/extras/fx_importer.py

@@ -1397,6 +1397,7 @@ class GraphNodeImporter:
     def _import_torch_op_overload(
         self, loc: Location, node: torch_fx.Node, target: TorchOpOverload
     ):
+        # TODO: Convert this cascade of ifs to a table-driven
         # replace lift_fresh_copy with clone op
         if target == torch.ops.aten.lift_fresh_copy.default:
             node.target = target = torch.ops.aten.clone.default
@@ -1420,6 +1421,16 @@ class GraphNodeImporter:
                 for key_node in node.users:
                     if key_node.target == torch.ops.aten.baddbmm.default:
                         node.target = target = torch.ops.aten.zeros.default
+        elif target == torch.ops.aten._local_scalar_dense.default:
+            input_type = node.args[0].meta["tensor_meta"].dtype
+            if input_type.is_floating_point:
+                node.target = target = torch.ops.aten.Float.Tensor
+            else:
+                node.target = target = torch.ops.aten.Int.Tensor
+            node.args = (node.args[0],)
+        elif target == torch.ops.aten._assert_async.msg:
+            # TODO: A more suitable op to replace it?
+            return
 
         schema = target._schema
         assert isinstance(schema, FunctionSchema)