[mlir][Linalg] Bugfix in decompose generic by unfolding permutation (#126737)

The pattern was returning success() by default which made the greedy
pattern application act as if the IR was modified and even though
nothing was changed and thus it can prevent it from converging for no
legitimate reason.

The patch makes the rewrite pattern return failure() by default and
success() if and only if the IR changed.

An example of unexpected behavior is by running `mlir-opt input.mlir
--linalg-specialize-generic-ops`, we obtain an empty mlir as output with
`input.mlir` as follows:
```
#map = affine_map<(d0) -> (d0)>
func.func @f(%arg0: tensor<8xi32>, %arg1: tensor<8xi32>) -> tensor<8xi32> {
  %0 = tensor.empty() : tensor<8xi32>
  %1 = linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = ["parallel"]} ins(%arg0, %arg1: tensor<8xi32>, tensor<8xi32>) outs(%0: tensor<8xi32>) {
    ^bb0(%in: i32, %in_0: i32, %out: i32):
      %2 = arith.addi %in, %in_0: i32
      linalg.yield %2: i32
  } -> tensor<8xi32>
  return %1 : tensor<8xi32>
}
```

Author: gdehame

mlir/lib/Dialect/Linalg/Transforms/DecomposeGenericByUnfoldingPermutation.cpp

@@ -223,21 +223,21 @@ LogicalResult DecomposeProjectedPermutation::matchAndRewrite(
     newMap[i] = rewriter.getMultiDimIdentityMap(map.getNumDims());
   }
 
-  if (isChanged) {
-    SmallVector<Value> operands = op->getOperands();
-    ValueRange operandsRef(operands);
-
-    auto newOp = rewriter.create<linalg::GenericOp>(
-        /*location=*/op.getLoc(),
-        /*resultTensorTypes=*/op->getResultTypes(),
-        /*inputs=*/newInitValues,
-        /*outputs=*/operandsRef.drop_front(op.getNumDpsInputs()),
-        /*indexingMaps=*/newMap,
-        /*iteratorTypes=*/op.getIteratorTypesArray());
-
-    newOp.getRegion().takeBody(op->getRegion(0));
-    rewriter.replaceOp(op, newOp->getResults());
-  }
+  if (!isChanged)
+    return failure();
+
+  SmallVector<Value> operands = op->getOperands();
+  ValueRange operandsRef(operands);
+
+  auto newOp = rewriter.create<linalg::GenericOp>(
+      /*location=*/op.getLoc(),
+      /*resultTensorTypes=*/op->getResultTypes(),
+      /*inputs=*/newInitValues,
+      /*outputs=*/operandsRef.drop_front(op.getNumDpsInputs()),
+      /*indexingMaps=*/newMap,
+      /*iteratorTypes=*/op.getIteratorTypesArray());
+  newOp.getRegion().takeBody(op->getRegion(0));
+  rewriter.replaceOp(op, newOp->getResults());
   return success();
 }