diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
index d26601c0de8d6..cfffcee156c3e 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainQtoZ.cpp
@@ -851,11 +851,14 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
         float alpha, gamma;
         Value operand;
         if (binder.tensorOperand(operand) ||
-            binder.f32FloatAttr(alpha, "alpha") ||
-            binder.f32FloatAttr(gamma, "gamma") ||
+            binder.f32FloatAttr(alpha, "alpha", 1.67326) ||
+            binder.f32FloatAttr(gamma, "gamma", 1.0507) ||
             binder.tensorResultType(resultType))
           return failure();
 
+        Torch::ValueTensorType inputType =
+            operand.getType().cast<Torch::ValueTensorType>();
+
         Value vAlpha = rewriter.create<Torch::ConstantFloatOp>(
             binder.getLoc(), rewriter.getType<Torch::FloatType>(),
             rewriter.getFloatAttr(rewriter.getF64Type(), alpha));
@@ -864,12 +867,31 @@ void mlir::torch::onnx_c::populateDefaultDomainQtoZ(
             binder.getLoc(), rewriter.getType<Torch::FloatType>(),
             rewriter.getFloatAttr(rewriter.getF64Type(), gamma));
 
-        Value vInputScale = rewriter.create<Torch::ConstantFloatOp>(
+        Value cstOne = rewriter.create<Torch::ConstantFloatOp>(
             binder.getLoc(), rewriter.getType<Torch::FloatType>(),
             rewriter.getFloatAttr(rewriter.getF64Type(), 1.0));
 
-        rewriter.replaceOpWithNewOp<Torch::AtenEluOp>(
-            binder.op, resultType, operand, vAlpha, vScale, vInputScale);
+        Value cstNone = rewriter.create<Torch::ConstantNoneOp>(binder.getLoc());
+        Value zeroTensor = rewriter.create<Torch::AtenZerosLikeOp>(
+            binder.getLoc(), resultType, operand, cstNone, cstNone, cstNone,
+            cstNone, cstNone);
+        Value exp = rewriter.create<Torch::AtenExpOp>(binder.getLoc(),
+                                                      resultType, operand);
+        Value expMulAlpha = rewriter.create<Torch::AtenMulScalarOp>(
+            binder.getLoc(), resultType, exp, vAlpha);
+        Value expMulAlphaSubAlpha = rewriter.create<Torch::AtenSubScalarOp>(
+            binder.getLoc(), resultType, expMulAlpha, vAlpha, cstOne);
+        Value neg = rewriter.create<Torch::AtenMulScalarOp>(
+            binder.getLoc(), resultType, expMulAlphaSubAlpha, vScale);
+        Value pos = rewriter.create<Torch::AtenMulScalarOp>(
+            binder.getLoc(), resultType, operand, vScale);
+        Type compareType = inputType.getWithSizesAndDtype(
+            inputType.getOptionalSizes(), rewriter.getI1Type());
+        Value xLessThanZero = rewriter.create<Torch::AtenLtTensorOp>(
+            binder.getLoc(), compareType, operand, zeroTensor);
+
+        rewriter.replaceOpWithNewOp<Torch::AtenWhereSelfOp>(
+            binder.op, resultType, xLessThanZero, neg, pos);
         return success();
       });
   patterns.onOp("ReduceL1", 1,
diff --git a/lib/Dialect/Torch/IR/TorchOps.cpp b/lib/Dialect/Torch/IR/TorchOps.cpp
index e768033ac87f9..2cea874f341f9 100644
--- a/lib/Dialect/Torch/IR/TorchOps.cpp
+++ b/lib/Dialect/Torch/IR/TorchOps.cpp
@@ -140,7 +140,7 @@ static Value getScalarIntValue(Value input, Location loc,
     return nullptr;
 
   Type inputDtype = inputTensorType.getOptionalDtype();
-  if (!inputDtype || !inputDtype.isInteger(64))
+  if (!inputDtype || !(inputDtype.isInteger(64) || inputDtype.isInteger(1)))
     return nullptr;
 
   std::optional<unsigned> inputRank = getTensorRank(input);
@@ -148,11 +148,19 @@ static Value getScalarIntValue(Value input, Location loc,
     return nullptr;
 
   if (auto valueTensorLiteralOp = input.getDefiningOp<ValueTensorLiteralOp>()) {
-    auto val = valueTensorLiteralOp.getValue()
-                   .cast<DenseIntElementsAttr>()
-                   .getSplatValue<int64_t>();
-    return rewriter.create<Torch::ConstantIntOp>(
-        loc, rewriter.getI64IntegerAttr(val));
+    if (inputDtype.isInteger(64)) {
+      auto val = valueTensorLiteralOp.getValue()
+                     .cast<DenseIntElementsAttr>()
+                     .getSplatValue<int64_t>();
+      return rewriter.create<Torch::ConstantIntOp>(
+          loc, rewriter.getI64IntegerAttr(val));
+    } else {
+      auto val = valueTensorLiteralOp.getValue()
+                     .cast<DenseIntElementsAttr>()
+                     .getSplatValue<bool>();
+      return rewriter.create<Torch::ConstantIntOp>(
+          loc, rewriter.getI64IntegerAttr(val));
+    }
   } else if (auto primNumToTensorScalarOp =
                  input.getDefiningOp<PrimNumToTensorScalarOp>()) {
     return primNumToTensorScalarOp.getA();
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index e426e998ebe04..f34b5a5e3b2cf 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -2154,7 +2154,6 @@
     "ElementwiseAtenFloorDivideTensorNegativeModule_basic",
     "ElementwiseLog10IntModule_basic",
     "ElementwiseLog2IntModule_basic",
-    "ElementwiseSeluModule_basic",
     "FlipModuleStaticShape_basic",
     "FlipNegativeIndexModule_basic",
     "HardsigmoidModule_basic",
@@ -2669,8 +2668,6 @@
     "CopyWithDifferentDTypesModule_basic",
     "CosineSimilarityStaticBroadcastModule_basic",
     "CumsumInputDtypeInt32Module_basic",
-    "DropoutTrainModule_basic",
-    "DropoutTrainStaticShapeModule_basic",
     "ElementwiseAcosIntModule_basic",
     "ElementwiseAsinIntModule_basic",
     "ElementwiseAtanTensorIntModule_basic",