diff --git a/core/conversion/converters/impl/element_wise.cpp b/core/conversion/converters/impl/element_wise.cpp
index fd11246855..0b347c6647 100644
--- a/core/conversion/converters/impl/element_wise.cpp
+++ b/core/conversion/converters/impl/element_wise.cpp
@@ -166,11 +166,11 @@ auto element_wise_registrations TORCHTRT_UNUSED =
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                // Should implement self - alpha * other
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto scalar = args[2].unwrapToScalar().to<float>();
                auto other = args[1].ITensorOrFreeze(ctx);
+               auto scalar = args[2].unwrapToScalar();
 
-               if (1 != scalar) {
-                 auto alphaTensor = tensor_to_const(ctx, torch::tensor({scalar}));
+               if (1 != scalar.to<float>()) {
+                 auto alphaTensor = scalar_to_tensor(ctx, scalar);
                  auto scaleLayer = add_elementwise(
                      ctx,
                      nvinfer1::ElementWiseOperation::kPROD,
@@ -214,11 +214,11 @@ auto element_wise_registrations TORCHTRT_UNUSED =
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                // Should implement self - alpha * other
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto scalar = args[2].unwrapToScalar().to<float>();
                auto other = args[1].ITensorOrFreeze(ctx);
+               auto scalar = args[2].unwrapToScalar();
 
-               if (1 != scalar) {
-                 auto alphaTensor = tensor_to_const(ctx, torch::tensor({scalar}));
+               if (1 != scalar.to<float>()) {
+                 auto alphaTensor = scalar_to_tensor(ctx, scalar);
                  auto scaleLayer = add_elementwise(
                      ctx,
                      nvinfer1::ElementWiseOperation::kPROD,
@@ -351,8 +351,7 @@ auto element_wise_registrations TORCHTRT_UNUSED =
             {"aten::div.Scalar(Tensor self, Scalar other) -> (Tensor)",
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto otherScalar = args[1].unwrapToScalar().to<float>();
-               auto other = tensor_to_const(ctx, torch::tensor({otherScalar}));
+               auto other = scalar_to_tensor(ctx, args[1].unwrapToScalar());
                auto div = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kDIV, self, other, util::node_info(n));
                TORCHTRT_CHECK(div, "Unable to create div layer from node: " << *n);
 
@@ -381,8 +380,7 @@ auto element_wise_registrations TORCHTRT_UNUSED =
             {"aten::div_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)",
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto otherScalar = args[1].unwrapToScalar().to<float>();
-               auto other = tensor_to_const(ctx, torch::tensor({otherScalar}));
+               auto other = scalar_to_tensor(ctx, args[1].unwrapToScalar());
                auto div = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kDIV, self, other, util::node_info(n));
                TORCHTRT_CHECK(div, "Unable to create div layer from node: " << *n);
 
@@ -481,18 +479,12 @@ auto element_wise_registrations TORCHTRT_UNUSED =
             {"aten::ne.Scalar(Tensor self, Scalar other) -> (Tensor)",
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto scalar = args[1].unwrapToScalar();
-               nvinfer1::ITensor* scalar_tensor;
-               if (self->getType() == nvinfer1::DataType::kFLOAT || self->getType() == nvinfer1::DataType::kHALF) {
-                 scalar_tensor = tensor_to_const(ctx, torch::tensor({scalar.to<float>()}));
-               } else {
-                 scalar_tensor = tensor_to_const(ctx, torch::tensor({scalar.to<int>()}));
-               }
+               auto other = scalar_to_tensor(ctx, args[1].unwrapToScalar());
                auto equal = add_elementwise(
                    ctx,
                    nvinfer1::ElementWiseOperation::kEQUAL,
                    self,
-                   scalar_tensor,
+                   other,
                    util::node_info(n) + std::string("is_equal"));
                TORCHTRT_CHECK(equal, "Unable to create elementwise equal layer from node: " << *n);
                // XOR with ones negates and produces not_equal result
@@ -534,8 +526,7 @@ auto element_wise_registrations TORCHTRT_UNUSED =
             {"aten::pow.Tensor_Scalar(Tensor self, Scalar exponent) -> (Tensor)",
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto exponentScalar = args[1].unwrapToScalar().to<float>();
-               auto exponent = tensor_to_const(ctx, torch::tensor({exponentScalar}));
+               auto exponent = scalar_to_tensor(ctx, args[1].unwrapToScalar());
                auto pow =
                    add_elementwise(ctx, nvinfer1::ElementWiseOperation::kPOW, self, exponent, util::node_info(n));
                TORCHTRT_CHECK(pow, "Unable to create Power layer from node: " << *n);
@@ -681,9 +672,9 @@ auto element_wise_registrations TORCHTRT_UNUSED =
             {"aten::eq.Scalar(Tensor self, Scalar other) -> (Tensor)",
              [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
                auto self = args[0].ITensorOrFreeze(ctx);
-               auto otherScalar = args[1].unwrapToScalar().to<float>();
-               auto other = tensor_to_const(ctx, torch::tensor({otherScalar}));
+               auto other = scalar_to_tensor(ctx, args[1].unwrapToScalar());
                if (self->getType() == nvinfer1::DataType::kBOOL) {
+                 auto otherScalar = args[1].unwrapToScalar().to<float>();
                  if (otherScalar == 0 || otherScalar == 1) {
                    LOG_DEBUG("Since input tensor is type bool, casting input tensor and scalar to int32");
                    other = castITensor(ctx, other, nvinfer1::DataType::kINT32);