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

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Merged
merged 1 commit into from
Sep 26, 2024
Merged

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

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8 changes: 4 additions & 4 deletions mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
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Original file line number Diff line number Diff line change
Expand Up @@ -881,7 +881,7 @@ def Tosa_TableOp : Tosa_InferShapedTypeOp<"table"> {
}];

let arguments = (ins
Tosa_Tensor: $input,
Tosa_Tensor: $input1,
Tosa_Tensor1D: $table
);

Expand All @@ -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;
Expand Down Expand Up @@ -1640,7 +1640,7 @@ def Tosa_ReverseOp: Tosa_Op<"reverse", [
}];

let arguments = (ins
Tosa_Tensor:$input,
Tosa_Tensor:$input1,
I32Attr:$axis
);

Expand All @@ -1667,7 +1667,7 @@ def Tosa_SliceOp : Tosa_InferShapedTypeOp<"slice"> {
}];

let arguments = (ins
Tosa_Tensor:$input,
Tosa_Tensor:$input1,
DenseI64ArrayAttr:$start,
DenseI64ArrayAttr:$size
);
Expand Down
4 changes: 2 additions & 2 deletions mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
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Expand Up @@ -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();
Expand Down Expand Up @@ -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());
Expand Down
4 changes: 2 additions & 2 deletions mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp
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Expand Up @@ -144,7 +144,7 @@ TensorType inferReshapeCollapsedType(TensorType lhsType, TensorType rhsType) {
for (; currRhsDim < rhsShape.size(); currRhsDim++) {
assert(rhsShape[currRhsDim] == 1);
}

return lhsType.clone(intermediateShape);
}

Expand Down Expand Up @@ -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();
Expand Down
14 changes: 7 additions & 7 deletions mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -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(
Expand Down Expand Up @@ -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;

Expand All @@ -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>());
}
Expand Down
8 changes: 4 additions & 4 deletions mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
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Expand Up @@ -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();

Expand All @@ -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());
Expand All @@ -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() &&
Expand Down Expand Up @@ -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();

Expand Down
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