Update input names from input to input1 for Table, Reverse, Slice (#109807)

- For input naming consistency, updated the inputs to input1 for Table,
Reverse and Slice operator

Signed-off-by: Jerry Ge <[email protected]>

Author: Jerry-Ge

mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td

@@ -881,7 +881,7 @@ def Tosa_TableOp : Tosa_InferShapedTypeOp<"table"> {
   }];
 
   let arguments = (ins
-    Tosa_Tensor: $input,
+    Tosa_Tensor: $input1,
     Tosa_Tensor1D: $table
   );
 
@@ -890,7 +890,7 @@ def Tosa_TableOp : Tosa_InferShapedTypeOp<"table"> {
   );
 
   let assemblyFormat = [{
-    $input `,` $table attr-dict `:` `(` type($input) `,` type($table) `)` `->` type($output)
+    $input1 `,` $table attr-dict `:` `(` type($input1) `,` type($table) `)` `->` type($output)
   }];
 
   let hasVerifier = 1;
@@ -1640,7 +1640,7 @@ def Tosa_ReverseOp: Tosa_Op<"reverse", [
   }];
 
   let arguments = (ins
-    Tosa_Tensor:$input,
+    Tosa_Tensor:$input1,
     I32Attr:$axis
   );
 
@@ -1667,7 +1667,7 @@ def Tosa_SliceOp : Tosa_InferShapedTypeOp<"slice"> {
   }];
 
   let arguments = (ins
-    Tosa_Tensor:$input,
+    Tosa_Tensor:$input1,
     DenseI64ArrayAttr:$start,
     DenseI64ArrayAttr:$size
   );

mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp

@@ -1830,7 +1830,7 @@ class ReverseConverter : public OpRewritePattern<tosa::ReverseOp> {
   LogicalResult matchAndRewrite(tosa::ReverseOp op,
                                 PatternRewriter &rewriter) const final {
     auto loc = op.getLoc();
-    Value input = op.getInput();
+    Value input = op.getInput1();
     auto inputTy = cast<ShapedType>(input.getType());
     auto resultTy = cast<ShapedType>(op.getType());
     auto axis = op.getAxis();
@@ -2161,7 +2161,7 @@ class TableConverter : public OpRewritePattern<tosa::TableOp> {
   LogicalResult matchAndRewrite(tosa::TableOp op,
                                 PatternRewriter &rewriter) const final {
     auto loc = op.getLoc();
-    Value input = op.getInput();
+    Value input = op.getInput1();
     Value table = op.getTable();
     auto inputTy = cast<ShapedType>(input.getType());
     auto tableTy = cast<ShapedType>(table.getType());

mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp

@@ -144,7 +144,7 @@ TensorType inferReshapeCollapsedType(TensorType lhsType, TensorType rhsType) {
   for (; currRhsDim < rhsShape.size(); currRhsDim++) {
     assert(rhsShape[currRhsDim] == 1);
   }
-  
+
   return lhsType.clone(intermediateShape);
 }
 
@@ -264,7 +264,7 @@ class SliceConverter : public OpConversionPattern<tosa::SliceOp> {
   matchAndRewrite(tosa::SliceOp sliceOp, OpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const final {
     Location loc = sliceOp.getLoc();
-    Value input = adaptor.getInput();
+    Value input = adaptor.getInput1();
     ShapedType resultType = cast<ShapedType>(sliceOp.getType());
     if (llvm::isa<UnrankedTensorType>(resultType))
       return failure();

mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp

@@ -380,7 +380,7 @@ struct ConcatSliceOptimization : public OpRewritePattern<tosa::SliceOp> {
 
   LogicalResult matchAndRewrite(tosa::SliceOp sliceOp,
                                 PatternRewriter &rewriter) const override {
-    Value sliceInput = sliceOp.getInput();
+    Value sliceInput = sliceOp.getInput1();
     auto concatOp = sliceInput.getDefiningOp<tosa::ConcatOp>();
     if (!concatOp)
       return rewriter.notifyMatchFailure(
@@ -919,11 +919,11 @@ OpFoldResult ResizeOp::fold(FoldAdaptor adaptor) {
 }
 
 OpFoldResult ReverseOp::fold(FoldAdaptor adaptor) {
-  auto operand = getInput();
+  auto operand = getInput1();
   auto operandTy = llvm::cast<ShapedType>(operand.getType());
   auto axis = getAxis();
   auto operandAttr =
-      llvm::dyn_cast_if_present<SplatElementsAttr>(adaptor.getInput());
+      llvm::dyn_cast_if_present<SplatElementsAttr>(adaptor.getInput1());
   if (operandAttr)
     return operandAttr;
 
@@ -936,24 +936,24 @@ OpFoldResult ReverseOp::fold(FoldAdaptor adaptor) {
 }
 
 OpFoldResult SliceOp::fold(FoldAdaptor adaptor) {
-  auto inputTy = llvm::dyn_cast<RankedTensorType>(getInput().getType());
+  auto inputTy = llvm::dyn_cast<RankedTensorType>(getInput1().getType());
   auto outputTy = llvm::dyn_cast<RankedTensorType>(getType());
 
   if (!inputTy || !outputTy)
     return {};
 
   if (inputTy == outputTy && inputTy.hasStaticShape())
-    return getInput();
+    return getInput1();
 
-  if (!adaptor.getInput())
+  if (!adaptor.getInput1())
     return {};
 
   // Cannot create an ElementsAttr from non-int/float/index types
   if (!inputTy.getElementType().isIntOrIndexOrFloat() ||
       !outputTy.getElementType().isIntOrIndexOrFloat())
     return {};
 
-  auto operand = llvm::cast<ElementsAttr>(adaptor.getInput());
+  auto operand = llvm::cast<ElementsAttr>(adaptor.getInput1());
   if (operand.isSplat() && outputTy.hasStaticShape()) {
     return SplatElementsAttr::get(outputTy, operand.getSplatValue<Attribute>());
   }

mlir/lib/Dialect/Tosa/IR/TosaOps.cpp

@@ -850,7 +850,7 @@ LogicalResult tosa::SliceOp::inferReturnTypeComponents(
 }
 
 LogicalResult tosa::SliceOp::verify() {
-  auto inputType = llvm::dyn_cast<RankedTensorType>(getInput().getType());
+  auto inputType = llvm::dyn_cast<RankedTensorType>(getInput1().getType());
   if (!inputType)
     return success();
 
@@ -869,7 +869,7 @@ LogicalResult tosa::TableOp::inferReturnTypeComponents(
     MLIRContext *context, ::std::optional<Location> location,
     TableOp::Adaptor adaptor,
     SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) {
-  ShapeAdaptor inputShape(adaptor.getInput().getType());
+  ShapeAdaptor inputShape(adaptor.getInput1().getType());
 
   if (!inputShape.hasRank()) {
     inferredReturnShapes.push_back(ShapedTypeComponents());
@@ -882,7 +882,7 @@ LogicalResult tosa::TableOp::inferReturnTypeComponents(
 }
 
 LogicalResult tosa::TableOp::verify() {
-  TensorType inputType = getInput().getType();
+  TensorType inputType = getInput1().getType();
   TensorType outputType = getOutput().getType();
 
   if (inputType.hasRank() && outputType.hasRank() &&
@@ -1973,7 +1973,7 @@ void IfOp::print(OpAsmPrinter &p) {
 }
 
 LogicalResult ReverseOp::verify() {
-  TensorType inputType = getInput().getType();
+  TensorType inputType = getInput1().getType();
   TensorType outputType = getOutput().getType();
   int32_t reverseAxis = getAxis();