[mlir][tosa] Set explicit benefit for tosa.reshape to linalg

[rsuderman]

Summary

The patterns used to lower tosa.reshape to linalg are order
dependent which varies depending on platform. Setting the
benefit appropriately guarantees compilation executes the
rewriters in the correct ordering.

mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp

matchAndRewrite(tosa::ReshapeOp reshape, OpAdaptor adaptor,
     ShapedType resultTy = reshape.getType().template cast<ShapedType>();
     bool isDynamic = !operandTy.hasStaticShape();
 
     if (isDynamic && resultTy.getRank() != 1) {
       return rewriter.notifyMatchFailure(
           reshape, "Cannot collapse dynamic dims to more than one dimension");
     }
 
-    if (operandTy == resultTy) {
-      rewriter.replaceOp(reshape, adaptor.getOperands()[0]);
-      return success();
-    }
-
     SmallVector<ReassociationExprs, 4> reassociationMap;
     if (!createReassociationMapsForCollapse(rewriter, operandTy.getShape(),
                                             resultTy.getShape(),
                                             reassociationMap, isDynamic)) {
       return rewriter.notifyMatchFailure(
           reshape,
           "tosa.reshape Attempting to collapse into an incompatible shape");
     }
public:
 
   LogicalResult
   matchAndRewrite(tosa::ReshapeOp reshape, OpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const final {
     ShapedType operandTy = adaptor.getInput1().getType().cast<ShapedType>();
     ShapedType resultTy = reshape.getType().template cast<ShapedType>();
     bool isDynamic = !operandTy.hasStaticShape();
 
-    if (operandTy == resultTy) {
-      rewriter.replaceOp(reshape, adaptor.getOperands()[0]);
-      return success();
-    }
-
     if (isDynamic && operandTy.getRank() != 1) {
       return rewriter.notifyMatchFailure(
           reshape, "Cannot expand dynamic dims from more than one dimension");
     }
 
     SmallVector<ReassociationExprs, 4> reassociationMap;
     if (!createReassociationMapsForCollapse(rewriter, resultTy.getShape(),
                                             operandTy.getShape(),
public:
 
   LogicalResult
   matchAndRewrite(tosa::ReshapeOp reshape, OpAdaptor adaptor,
                   ConversionPatternRewriter &rewriter) const final {
     ShapedType operandTy = adaptor.getInput1().getType().cast<ShapedType>();
     ShapedType resultTy = reshape.getType().template cast<ShapedType>();
     bool isDynamic = !operandTy.hasStaticShape();
 
-    if (operandTy == resultTy) {
-      rewriter.replaceOp(reshape, adaptor.getOperands()[0]);
-      return success();
-    }
-
     SmallVector<int64_t> intermediateShape;
     if (!findIntermediateShape(resultTy.getShape(), operandTy.getShape(),
                                intermediateShape, isDynamic)) {
       return rewriter.notifyMatchFailure(
           reshape, "tosa.reshape Cannot identify an intermediate shape between "
                    "the given two shapes");
     }
 
void mlir::tosa::populateTosaToLinalgConversionPatterns(
   // We have multiple resize coverters to handle degenerate cases.
   patterns->add<GenericResizeConverter>(patterns->getContext(),
                                         /*benefit=*/100);
   patterns->add<ResizeUnaryConverter>(patterns->getContext(),
                                       /*benefit=*/200);
   patterns->add<MaterializeResizeBroadcast>(patterns->getContext(),
                                             /*benefit=*/300);
 
+  patterns->add<ReshapeConverterCollapse>(patterns->getContext(),
+                                          /*benefit=*/100);
+  patterns->add<ReshapeConverterExpand>(patterns->getContext(),
+                                        /*benefit=*/200);
+  patterns->add<ReshapeConverterCollapseExpand>(patterns->getContext(),
+                                                /*benefit=*/300);
+
   patterns->add<
       // clang-format off
       PointwiseConverter<tosa::AddOp>,
       PointwiseConverter<tosa::SubOp>,
       PointwiseConverter<tosa::MulOp>,
       PointwiseConverter<tosa::DivOp>,
       PointwiseConverter<tosa::NegateOp>,
       PointwiseConverter<tosa::PowOp>,
patterns->add<
       ReduceConverter<tosa::ReduceAnyOp>,
       ReduceConverter<tosa::ReduceMinOp>,
       ReduceConverter<tosa::ReduceMaxOp>,
       ReduceConverter<tosa::ReduceSumOp>,
       ReduceConverter<tosa::ReduceProdOp>,
       ArgMaxConverter,
       ConcatConverter,
       GatherConverter,
-      ReshapeConverterCollapse,
-      ReshapeConverterExpand,
-      ReshapeConverterCollapseExpand,
       RescaleConverter,
       ReverseConverter,
       TableConverter,
       TileConverter,
       TransposeConverter>(patterns->getContext());
   // clang-format on
 }