diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
index 2cddbee97dff2..a2ee31bfd4637 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -1196,9 +1196,9 @@ def Tosa_SelectOp : Tosa_ElementwiseOp<"select"> {
   }];
 
   let arguments = (ins
-    Tosa_I1Tensor:$pred,
-    Tosa_Tensor:$on_true,
-    Tosa_Tensor:$on_false
+    Tosa_I1Tensor:$input1,
+    Tosa_Tensor:$input2,
+    Tosa_Tensor:$input3
   );
 
   let results = (outs
@@ -1208,7 +1208,7 @@ def Tosa_SelectOp : Tosa_ElementwiseOp<"select"> {
   let hasFolder = 1;
 
   let assemblyFormat = [{
-    operands attr-dict `:` `(` type($pred) `,` type($on_true) `,` type($on_false)
+    operands attr-dict `:` `(` type($input1) `,` type($input2) `,` type($input3)
     `)` `->` type($output)
   }];
 }
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
index 22447e49fb3ea..3d4d7ccf5ebb2 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
@@ -221,12 +221,12 @@ struct SelectLogicalNotOptimization : public OpRewritePattern<tosa::SelectOp> {
   using OpRewritePattern::OpRewritePattern;
   LogicalResult matchAndRewrite(tosa::SelectOp op,
                                 PatternRewriter &rewriter) const override {
-    auto notOp = op.getPred().getDefiningOp<tosa::LogicalNotOp>();
+    auto notOp = op.getInput1().getDefiningOp<tosa::LogicalNotOp>();
     if (!notOp)
       return failure();
     rewriter.modifyOpInPlace(op, [&]() {
       op.getOperation()->setOperands(
-          {notOp.getInput1(), op.getOnFalse(), op.getOnTrue()});
+          {notOp.getInput1(), op.getInput3(), op.getInput2()});
     });
     return success();
   }
@@ -247,7 +247,7 @@ struct SelectToClampOptimization : public OpRewritePattern<tosa::SelectOp> {
   LogicalResult matchAndRewrite(tosa::SelectOp op,
                                 PatternRewriter &rewriter) const override {
 
-    auto geq = op.getPred().getDefiningOp<tosa::GreaterEqualOp>();
+    auto geq = op.getInput1().getDefiningOp<tosa::GreaterEqualOp>();
     if (!geq) {
       return rewriter.notifyMatchFailure(op,
                                          "Predicate is not a GreaterEqualOp");
@@ -297,8 +297,8 @@ struct SelectToClampOptimization : public OpRewritePattern<tosa::SelectOp> {
       return a.getSplatValue<APFloat>() == b.getSplatValue<APFloat>();
     };
 
-    auto onFalse = op.getOnFalse();
-    auto onTrue = op.getOnTrue();
+    auto onFalse = op.getInput3();
+    auto onTrue = op.getInput2();
     DenseElementsAttr onFalseAttr;
     DenseElementsAttr onTrueAttr;
 
@@ -1722,18 +1722,18 @@ OpFoldResult SliceOp::fold(FoldAdaptor adaptor) {
 }
 
 OpFoldResult tosa::SelectOp::fold(FoldAdaptor adaptor) {
-  if (getOnTrue() == getOnFalse())
-    return getOnTrue();
+  if (getInput2() == getInput3())
+    return getInput2();
 
   auto predicate =
-      llvm::dyn_cast_if_present<DenseIntElementsAttr>(adaptor.getPred());
+      llvm::dyn_cast_if_present<DenseIntElementsAttr>(adaptor.getInput1());
   if (!predicate)
     return {};
 
   if (!predicate.isSplat())
     return {};
-  return predicate.getSplatValue<APInt>().getBoolValue() ? getOnTrue()
-                                                         : getOnFalse();
+  return predicate.getSplatValue<APInt>().getBoolValue() ? getInput2()
+                                                         : getInput3();
 }
 
 OpFoldResult TileOp::fold(FoldAdaptor adaptor) {
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
index 79afc75fd6c8e..87b2a2695351b 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaMakeBroadcastable.cpp
@@ -169,9 +169,9 @@ struct ConvertTosaOp<tosa::SelectOp> : public OpRewritePattern<tosa::SelectOp> {
   LogicalResult matchAndRewrite(tosa::SelectOp tosaOp,
                                 PatternRewriter &rewriter) const override {
 
-    Value input1 = tosaOp.getPred();
-    Value input2 = tosaOp.getOnTrue();
-    Value input3 = tosaOp.getOnFalse();
+    Value input1 = tosaOp.getInput1();
+    Value input2 = tosaOp.getInput2();
+    Value input3 = tosaOp.getInput3();
     Value output = tosaOp.getResult();
 
     auto outputType = dyn_cast<RankedTensorType>(output.getType());